Toward the Patient-Centred Development of Cancer Therapeutics: a Focus on Nanomedicines

Toward the patient-centred development of cancer therapeutics: A focus on nanomedicines

Michael Welch Freeman

A thesis submitted in conformity with the requirements for the degree of Master of Applied Science Department of Chemical Engineering and Applied Chemistry University of Toronto

Michael Welch Freeman

Master of Applied Science

Department of Chemical Engineering and Applied Chemistry University of Toronto

2018 Abstract

Inspired by early work indicating nanometre-scale macromolecules can accumulate in tumours, nanomedicines were developed with intentions of improving cancer-killing efficacy and reducing systemic toxicity typical of traditional chemotherapies. This research first evaluates evidence provided to FDA and EMA regulators in order for cancer nanomedicines to be granted marketing approval, and then consults mature clinical data via health technology assessments to synthesize judgments of clinical benefit with respect to overall survival, safety, and health- related quality of life (HRQOL). Findings indicate that every marketed cancer nanomedicine— eight of nine being liposome technologies—demonstrates comparative clinical benefit on at least one dimension, that improvements in overall survival frequently come at the expense of safety, and that HRQOL is generally conserved or improved versus comparator therapies. Sparse data and inconsistency in HRQOL reporting practices were major deficiencies among the documents consulted and represent key barriers to providing patients evidence that can inform treatment decision-making.

Dedication

For Dad, who inspired this work without ever knowing so.

His maxim, make each day count, acts as both my guide for life and the lens through which I view cancer care. Thanks for everything.

iii Acknowledgments

First, I would like to acknowledge the sacred land on which the University of Toronto operates and upon which I had the privilege to study for many rich years. It has been a site of human activity for 15,000 years. This land is the territory of the Huron-Wendat and Petun First Nations, the Seneca, and most recently, the Mississaugas of the Credit River. The territory was the subject of the Dish With One Spoon Wampum Belt Covenant, an agreement between the Iroquois Confederacy and Confederacy of the Ojibwe and allied nations to peaceably share and care for the resources around the Great Lakes. Today, Toronto is still the home to many Indigenous people from across Turtle Island and I am grateful to work in the community, on this territory.

I would like to acknowledge my supervisor, Professor Christine Allen, without whom, the wild development and extreme evolution of this thesis would not have been possible. Thank you for your encouragement, patience, grace, and for sharing your world-class expertise.

I would like to acknowledge the outstanding members of the Christine Allen Laboratory, past and present, with whom I have had the great privilege of working and living alongside for many wonderful, turbulent, and proud years, ordered here by last name:

Hilary Boucher Brittany Epp- Sungmin Jung Max Regenold Lei Cui Ducharme Frantz Le Russell Shen Nancy Dou Jamie Evans Dévédec Alexandros Sofias Michael Dunne Justin Grant Xinpei Li Lucy Wang Sina Eetezadi Sohyoung Her Changhai Lu Jinzi Zheng Sandra Ekdawi Loujin Houdaihed Juliette Mérian Dario Jeginovic Mozhgan Nazari

I would like to acknowledge my committee members, Professor Warren Chan and Professor Timothy Bender, who have supported my work and my interests over many years.

I would like to acknowledge Professor Elise Paradis, whose boundless energy and great passion for her science continues to inspire. Thank you for sharing your guidance and knowledge.

I would like to acknowledge Siddhartha Mukherjee, Atul Gawande, Paul Kalanithi, and Susan Sontag, whose incomparable writings on science and cancer and illness provided much of the literary motivation for this thesis.

I would like to acknowledge members of my immediate and extended family, who were constant in their love and confidence in me, even when—especially when—I was not. Thank you for incredible support and for making up such a rich, interconnected network of support and warmth.

Thank you, Dad, for your big life and your brightly coloured legacy. Thank you, Mom, for your strength and joy. Thank you, Brit, for your inspiration and vibrance. Thank you, Denis, for your equanimity and humour. Thank you, Brit and Denis’ unborn baby—my first niece or nephew— who made it clear that capital-L LIFE is fast approaching, so I’d better push on with this thesis.

I would like to acknowledge Amanda, my partner in adventure, in academia, in love, and through a whole lot of life. Thank you for your kindness, your wisdom, your strength, and your heart. Thank you for all of you.

v Table of contents

Acknowledgments ...... iv

Table of contents ...... vi

List of tables ...... viii

List of figures ...... ix

List of appendices ...... x

Chapter 1 Introduction ...... 1

1 Cancer ...... 1 1.1 Characteristics of cancer ...... 5 1.2 Cancer care ...... 5

2 Cancer nanomedicine ...... 6 2.1 The enhanced permeability and retention effect ...... 8 2.2 Nanomedicine technologies featured in this thesis ...... 9

3 The difficulty with delivery ...... 13 3.1 Beyond the EPR effect: Addressing multifactor heterogeneity ...... 13 3.2 Indicators of nanomedicine delivery ...... 16 3.3 Performance measures ...... 17

4 Toxicity reduction ...... 18

5 Quality of life ...... 19 5.1 Measuring HRQOL ...... 21

6 Regulatory approval process for cancer medicines ...... 22 6.1 Patient-centred drug development ...... 23

7 Rationale ...... 25 7.1 Grounding in engineering design ...... 25

Chapter 2 Analysis of anticancer efficacy, quality of life, and safety benefits associated with marketed nanomedicines ...... 27

1 Introduction to analysis ...... 27

2 Methods...... 28

2.1 Inclusion and exclusion criteria ...... 28 2.2 Regulatory approvals ...... 29 2.3 Health technology assessments (HTAs) ...... 31 2.4 Data extraction and synthesis ...... 32

3 Results ...... 33 3.1 Basis for approval of nanomedicines ...... 33 3.2 HTA of nanomedicines ...... 39

Chapter 3 Discussion ...... 51

1 Basis for regulatory approval of nanomedicines ...... 51

2 HTA of nanomedicines ...... 55

3 Emphasizing the intentional collection, analysis, and communication of HRQOL data in cancer nanomedicine ...... 58

Chapter 4 Limitations, future work, and conclusions ...... 61

1 Limitations ...... 61

2 Future work ...... 63 2.1 Updated survey of cancer nanomedicine HRQOL effects ...... 63 2.2 Cancer nanomedicine-specific clinical trial design ...... 64 2.3 Study of patient experiences with cancer nanomedicines with view toward development of HRQOL assessment tool ...... 66

3 Conclusions ...... 67

References ...... 69

vii

List of tables

Table 1: Eligible Cancer Nanomedicines and their Original Bases for FDA or EMA Marketing Approval ...... 34

Table 2: Nanomedicine Approvals By Region and Health Technology Assessment Coverage By Agency ...... 40

Table 3: Therapeutic Profile of FDA- or EMA-Approved Cancer Nanomedicines According to Health Technology Assessment Agencies ...... 43

Table 4: Abraxane Health Technology Assessment Summary ...... 91

Table 5: Doxil/Caelyx Health Technology Assessment Summary ...... 92

Table 6: Daunoxome Health Technology Assessment Summary ...... 93

Table 7: Depocyt Health Technology Assessment Summary ...... 94

Table 8: Myocet Health Technology Assessment Summary ...... 95

Table 9: Mepact Health Technology Assessment Summary ...... 96

Table 10: Marqibo Health Technology Assessment Summary ...... 98

Table 11: Onivyde Health Technology Assessment Summary ...... 99

Table 12: Vyxeos Health Technology Assessment Summary ...... 101

Table 13: Survey of Investigations in Nanomedicines’ Effects on Quality of Life ...... 104

Table 14: Interpretivist-Constructionist Research Paradigm ...... 108

Table 15: Information Power Determination ...... 111

Table 16: Risk-Vulnerability Matrix and Explanation ...... 115

viii

List of figures

Figure 1 | Distribution of new cancer cases and cancer deaths by age group in Canada...... 2

Figure 2 | Five-year survival rates among Canadians aged 15-99, 2006-2008 versus 1992-1994* 4

Figure 3 | The rise of cancer nanomedicine research ...... 7

Figure 4 | Structure of pegylated liposomal doxorubicin (Doxil/Caelyx) ...... 10

Figure 5 | Structure of Abraxane and depiction of in vivo particle dissociation ...... 12

Figure 6 | Example of tumour microenvironment composition and organization ...... 15

Figure 7 | Breakdown of approved cancer NDDS types, APIs delivered, API anticancer action categories, and general cancer indications covered...... 37

Figure 8 | Timeline of cancer nanomedicine approvals, accelerated approvals, and approval conversions granted by the FDA and EMA...... 52

Figure 9 | Proposed patient-centred clinical trial for cancer nanomedicines...... 65

ix List of appendices

Appendix A Quality of life measurement instrument specimens ...... 88

Appendix B Health technology assessment of approved cancer nanomedicines ...... 91

Appendix C Search protocol for nanomedicine quality of life literature survey ...... 102

Appendix D Proposal for study of patient experiences with cancer nanomedicines ...... 105 Appendix D-I: Deconstruction of research question ...... 117 Appendix D-II: Interview guide ...... 118

Chapter 1 Introduction 1 Cancer

Cancer seems to touch all corners of life. Drawing on the author’s lived experience of studying in Toronto, Canada and growing up in its suburbs, stories detailing personal experiences with cancer or stories of friends or colleagues or family members recently diagnosed with cancer or news of one who recently passed away as a result of cancer are ubiquitously and frequently heard. Perhaps as a result of its persistence and pervasiveness in contemporary culture, cancer has grown from a biological and medical issue to be a political, economic, and social one as well1–5. Concurrently, aims of work around cancer treatment are evolving from those focused solely on curing disease to those focused also on controlling the tolerability of treatment and conserving a patient’s quality of life (QOL) during and after treatment: a patient-centred approach to oncology, where patient voices inform treatment6–8.

The colloquial impressions of cancer’s pervasiveness expressed here echo national surveys and modeling performed by the Canadian Cancer Society, who predictψ that approximately 50% of

Canadians will develop cancer through the course of their lives—one in two males and one in 2.2 females—and one in four will die of the disease9. During the year 2017, the same model estimates that 206,200 Canadians will be diagnosed with cancer and 80,800 will die from it:

0.59% and 0.22% of Canada’s population∗, respectively9. Cancer is Canada’s leading cause of death in general (30.2% of deaths in 2012) and of premature death (1.5M potential years of life lost over 2010-2012)9. Figure 1 visualizes the distribution of newly diagnosed cancer cases (1A) and cancer deaths (1B) in Canada by age range over five years.

ψ The Canadian Cancer Society drew on data from the Canadian Cancer Registry, the National Cancer Incidence Reporting System, and Canadian Vital Statistics Death database to develop predictions included in the Canadian Cancer Statistics 2017 publication9. ∗ Canada’s 2016 population according to Statistics Canada: 35,151,728269. 1

(1A) (1B)

Figure 1 | Distribution of new cancer cases and cancer deaths by age group in Canada. Figure 1A shows the distribution of newly diagnosed cancer cases over five years (2009-2013) for all age groups except ages 0-14, which reports new cases over 2006-2010. Figure 1B shows the distribution of cancer deaths over five years (2008-2012) for all age groups. Columns are sorted by cancer type in order of descending incidence per age group. N = total number of cases (1A) or deaths (1B) over five years; CNS = central nervous system; PNC = peripheral nervous cell tumours; NOS = not otherwise specified.

Figures 1A and 1B and caption notes adapted from “Canadian Cancer Statistics 2017,” by the Canadian Cancer Society Advisory Committee, 2017 (http://www.cancer.ca/~/media/cancer.ca/CW/cancer%20information/cancer%20101/Canadian%20cancer%20statistics/Canadian-Cancer-Statistics-2017-EN.pdf?la=en). In the public domain.

The pairing of cancer incidence and cancer death data in Figure 1 gives clues about the nature of a given disease and the availability of effective treatments for it. For instance, thyroid cancer appears as one of the two most frequently diagnosed cancers in age groups 15-29 and 30-49— 17% and 12% incidence, respectively—yet this disease does not appear in the chart describing mortality rates for either age group, indicating that it accounts for no more than 4% of the total cancer-caused deaths in either of these populations. Indeed, thyroid cancer is an example of a disease that is generally non-aggressive10 and well-controlled by treatment that takes advantage of the thyroid’s specific physiology*. Conversely, brain and other central nervous system cancers demonstrated an outsize effect on mortality with respect to their rates of incidence in younger populations. Similarly, pancreatic cancer was diagnosed in small enough proportions of the population to not appear in all but one age group’s—85+ years—cancer incidence distributions, but appeared in four of six age groups’ cancer mortality distributions. Prognoses for patients diagnosed with these cancers tend to be poor on account of limited avenues for early detection, dangers and limited benefit associated with surgery, and difficulties inherent to treatment with chemotherapeutic drugs at these disease sites: physical blockade by the blood-brain barrier and therapeutic resistance engendered by sophisticated cellular and molecular pathways, respectively, regularly undermine the cancer-killing potential of administered chemotherapies11,12.

The combined five-year overall survival (OS) rate for Canadians diagnosed with cancer is approximately 60% in 2017, but this measure shows great variation across specific cancer types: the five-year OS rate of people with thyroid cancer, for example, is 98%, while for people diagnosed with pancreatic cancer five-year OS is just 8%, with fewer than 50% of patients surviving four months beyond diagnosis9. Figure 2 renders five-year survival rates of those diagnosed with different cancers during 2006-2008 versus 1992-1994.

* Iodine is known to passively accumulate in the thyroid. Leveraging this physiological phenomenon and the known capacity of radiation to kill living cells led to the development of radioactive iodine therapy for thyroid cancer: iodine-131 is ingested by patients, is naturally absorbed by the thyroid, and then ablates tissues via concentrated, local doses of radiation. This treatment is typically given following surgery and to patients with advanced disease270. 3

Figure 2 | Five-year survival rates among Canadians aged 15-99, 2006-2008 versus 1992-1994* *Data from Quebec excluded from entire analysis on account of disparate cancer diagnosis methodologies. ✝ Data from Ontario excluded: no reports of in situ bladder cancer during time periods of interest. Error bars give range of 95% confidence intervals; CNS = central nervous system; NOS = not otherwise specified.

Figure 2 and caption notes adapted from “Canadian Cancer Statistics 2017,” by the Canadian Cancer Society Advisory Committee, 2017 (http://www.cancer.ca/~/media/cancer.ca/CW/cancer%20information/cancer%20101/Canadian%20cancer%20statistics/Canad ian-Cancer-Statistics-2017-EN.pdf?la=en). In the public domain.

The combination of Canadian five-year survival rates for all cancers improved by 7.3% during the time intervening 2006-2008 and 1992-1994, with the greatest improvements seen in non- Hodgkin lymphoma (+16%) and leukaemia (+15%), generally owing to the availability of new treatments—rituximab for non-Hodgkin lymphoma13 and imatinib for chronic myeloid

leukaemia14—and to reductions in the incidence of instigating conditions, like the role of human immunodeficiency virus (HIV) in non-Hodgkin lymphoma13.

The total number of new cancer cases has been increasing in Canada over the last 30 years, which can be attributed partially to a population that is steadily expanding and agingς.

Concurrently, though, mortality rates have been gradually declining as a result of improved strategies for the prevention, detection, and treatment of cancer9.

1.1 Characteristics of cancer

Cancer refers to a broad collection of diseases associated with the uncontrolled proliferation of cells. By way of genetic inheritance or environmental exposure, cancer cells have developed an advanced evolutionarily toolbox to ensure their own survival, including the capacity to source their own blood supply through angiogenesis, to sustain proliferative signaling, to enable replicative immortality, to resist programmed cell death, to evade growth suppressors, to mount invasions and metastasis15, to deregulate cellular energy systems, and to avoid destruction by the immune system16. This set of features, all optimized for persistence over millenia17, makes cancer a great challenge to treat and has contributed to cancer becoming significant risk to public health in the developed18 and developing19 worlds.

1.2 Cancer care

In the treatment of cancers manifested as solid tumours, patients typically undergo surgical resection of the mass, radiotherapy, and chemotherapy. Surgery is the historical standard of treatment for solid tumours20, while radiotherapy and chemotherapy are more recent innovations21 designed with the aim of potentiating surgery and treating surgically inaccessible or widespread disease. Neoadjuvant applications of radiotherapy and chemotherapy are meant to

ς 96% of Canadian deaths attributed to cancer occur in people more than 50 years age, and 63% of those deaths occur in people more than 70 years of age9. 5

reduce the size of a malignancy ahead of surgery, while adjuvant treatments occur after surgery with the aim of killing cancer cells that remain, thereby diminishing the probability that the cancer will return. In the case of ‘liquid tumours’—blood cancers like leukaemia—there is no tumour to resect, so chemotherapy and radiation therapy are particularly important (along with stem cell therapy for the replacement of diseased bone marrow)22,23.

Chemotherapy of cancer generally involves the systemic administration of chemical agents that capitalize on a cancer cell’s tendency to divide rapidly by targeting the cellular machinery involved in this division (e.g. via DNA intercalation and microtubule growth inhibition)24. While highly proliferative cancer cells are typically most sensitive to the activity of chemotherapeutic drugs, healthy cells are killed in the process too—they use the same machinery for replication, but usually at a lesser frequency—causing patients to experience significant symptoms of treatment toxicity. These symptoms can include, but are not limited to, nausea, vomiting, alopecia, infection, anemia, loss of appetite, diarrhea, and nerve and muscle pain25. Traditional chemotherapies, as a result of indiscriminately exposing healthy and malignant tissues to toxic agents, are poorly tolerated at doses necessary to achieve therapeutic effects and may result in further degradation of the QOL of cancer patients26,27, frequently resulting in patients discontinuing potentially life-prolonging treatment28–32.

2 Cancer nanomedicine

Nanotechnology is defined as the “intentional design, characterization, production, and applications of materials, structures, devices, and systems by controlling their size and shape in the nanoscale range (1 to 100 nm).”33 Famed American physicist Richard Feynman proposed in 1960 the concept of applying nanotechnology to the field of medicine, encouraging the development of nanoscale devices that would facilitate deliberate interactions with the body on the cellular level34. Over the following five decades and into the present, this concept evolved into a full-fledged field of research and practice, nanomedicine, from which thousands of research papers have been produced—over 18,500 PubMed publications returned with the keyword “nanomedicine” since 1999 (Figure 3)—and a burgeoning market has developed,

having a value projected at 412 billion USD by 201935. The field has yielded technologies that include nanopharmaceuticals for drug delivery, nanodiagnostics for diagnostics and imaging, nanotheranostics for combined therapy and diagnostics, and nanobiomaterials for medical implants36. In 2015, nanopharmaceuticals represented 75% of the market share of approved nanomedicines, and nanopharmaceuticals with applications in oncology represent the greatest share of that market, at 35% (estimated 140 billion USD value by 2019)35. This thesis focuses on the application of nanopharmaceuticals in oncology and refers to these entities generally as cancer nanomedicines*.

3500

3000

2500 N, 10 N&C, 2

N, 5 2000 N&C, 0

N, 3 N&C, 0 Nanomedicine 1500 N, 0 (N) N&C, 0 1000 (PubMed) Publications N, 2 N&C, 1 N, 1 Nanomedicine 500 N&C, 0 AND cancer (N&C) 0

Year

Figure 3 | The rise of cancer nanomedicine research Count of PubMed publications returned using the search terms “nanomedicine” (black) or “nanomedicine” AND “cancer” (red) between the years 1999 and 2017. Before 1999, the name “nanomedicine” was less commonplace.

* Nanodiagnostics are discussed as companions of cancer nanomedicines employed for the purposes of patient selection and elucidation of tumour physiology, but details of their physical characteristics and imaging-related properties are beyond the scope of this work. 7

Many traditional anticancer agents suffer from low solubility, poor pharmacokinetic profiles, and high off-target toxicity37. Cancer nanomedicines were designed with the intention of improving the therapeutic index of chemotherapeutic drugs: enhancing their cancer-killing efficacy and reducing their off-target toxicity. By delivering small molecule cytotoxic agents systemically using the protection of nano-sized drug delivery vehicles, the solubility of the drugs are improved and their pharmacokinetics and biodistribution can be altered to facilitate enhanced localized delivery to solid tumours, thereby reducing toxicity in other tissues36,38,39.

Common nanomedicines used for drug delivery, like liposomes and polymer micelles, comprise a central drug-encapsulating compartment and an external coating of long-chain polymers, like poly(ethylene glycol)(PEG)40. This ‘pegylation’ of nanoparticles acts to inhibit protein adsorption in the systemic circulation, thus improving their ability to avoid recognition and uptake by the mononuclear phagocytic system (MPS)41. Some nanoparticle platforms have enjoyed a multifold prolongation of their circulation lifetimes as a result of this surface modification, liposomal doxorubicin (Doxil/Caelyx) in particular40,42–44.

A strongly emphasized concept in the cancer nanomedicine literature surrounding mechanisms guiding the passive localization of nanoparticles to solid tumours is the enhanced permeability and retention (EPR) effect, which leverages the distinctive pathophysiology observed in a variety of tumours and the engineered size range of nanomedicines. In this way, the paradigm for delivering cancer nanomedicines—leveraging unique physiologic characteristics as a basis for therapy—is similar to that of radioactive iodine therapy employed in thyroid cancer, which contributes to the high survivability of that disease (see Section 1, Cancer).

2.1 The enhanced permeability and retention effect

Beyond prolonging circulatory lifetime and solubilizing drug cargo, cancer nanomedicines are proposed to have an enhanced capacity to passively accumulate in tumours45. Accumulation of traditional chemotherapies at the tumour site is known to be hindered by the rapid clearance of

small molecules (<5.5nm) by the renal system46, representing a key barrier to effective therapy. In 1986, Maeda et al. found that a SMANCS*-conjugated albumin macromolecule demonstrated a prolonged half-life in bloodstream47, which was later attributed to the escape of these macromolecules from renal clearance on account of their increased size48. Instead of being cleared, the macromolecules tended to accumulate in tumour tissue over time and were retained there for longer periods than free drug47.

Tumours tend to grow an irregularly structured blood supply system during the course of their rapid angiogenesis49. These systems typically exhibit gaps—‘fenestrations’—in the endothelial lining of tumour blood vessels, which results in vascular leakiness at cancer sites. These fenestrations can range in size from 100 to 780nm, depending on the type of tumour50–52, which allows macromolecules in the blood to exit the circulatory system—to ‘extravasate’—and enter the tumour interstitium53,54.

Macromolecules were also found to have a long residence time within tumours due to the tissue’s impaired lymphatic drainage55. The combination of prolonged circulation due to escape from renal clearance, preferential accumulation in tumours due to leaky vasculature, and retention in tumours due to poor lymphatic drainage forms the basis for passive targeting of macromolecules via EPR effect48.

2.2 Nanomedicine technologies featured in this thesis

Nanomedicine platforms that have enjoyed extensive development over the past decades are nanoparticle-based drug delivery systems, which include liposomes, micelles, lipid nanoparticles, protein-based nanoparticles, and polymeric nanoparticles36. Liposomes and protein-based nanoparticles designed to deliver anticancer drugs represent the only two forms of cancer

* Styrene maleic acid neocarzinostatin: a polymer-conjugated anticancer agent271. 9

nanomedicine technology that had been approved by U.S. Food and Drug Administration (FDA) or European Medicines Agency (EMA) regulators at the time of writing and, thus, are heavily featured in this thesis.

2.2.1 Liposomes

Nearly 90% of nanomedicines approved for the treatment of cancer by the FDA or EMA are formulated as liposomes (see Chapter 2, Analysis). Lipid vehicles—the original name for liposomes—were first described in 196556. Their design is based on a phospholipid bilayer and liposomes can be used to carry both hydrophilic and hydrophobic drug molecules57. The first long-circulating liposomes were described in 1987, which introduced and leveraged the concept of pegylation58. This pegylation reduced the liposomes’ destruction by MPS and premature clearance, thereby prolonging blood circulation time and enhancing tumour accumulation40,58. The first cancer nanomedicine to receive marketing approval—Doxil/Caelyx—came in the form of pegylated liposomes loaded with doxorubicin hydrochloride indicated for the treatment of AIDs-related Kaposi’s sarcoma59 (Figure 4).

Encapsulated doxorubicin hydrochloride

Liposome (phospholipid bilayer) Grafted PEG layer Figure 4 | Structure of pegylated liposomal doxorubicin (Doxil/Caelyx) From “Pegylated Liposomal Doxorubicin for Advanced Ovarian Cancer in Women who are Refractory to Both Platinum- and Paclitaxel-Based Chemotherapy Regimens” by T. Sugiyama and S. Kumagai, 2009, Clinical Medicine Insights: Therapeutics, 1, p. 1227-36, CC BY 2.0.60

At present, Doxil/Caelyx is also approved for the treatment of multiple myeloma and ovarian cancer by the FDA61 and for these same conditions, with the addition of metastatic breast cancer, by the EMA62. The global market for liposomal doxorubicin—which includes the generic Lipodox and the non-pegylated Myocet (approved in Europe)—was valued at nearly 815 million USD and is projected to reach 1.39 billion USD by 202463, which can be taken as one indication of the success of these technologies. Section 4 of this chapter describes further the performance of liposomal doxorubicin in terms of cancer-killing efficacy and toxicity reduction.

Liposome technology also allows the important possibility of delivering combination chemotherapies in controlled molar ratios, as in the case of the acute myeloid leukaemia drug Vyxeos, which delivers a 5:1 molar ratio of cytarabine and daunorubicin, respectively64. Other liposome-based nanomedicines approved for the treatment of cancer include Daunoxome, Depocyt, Mepact, Marqibo, and Onivyde: their clinical benefits are described as part of the analysis in Chapter 2.

2.2.2 Protein-based nanoparticles

Apart from liposomal technologies, protein-based nanoparticles are the only other kind of nanomedicine that has been approved for the treatment of cancer by the FDA or EMA, of which there is just one example: Abraxane. Abraxane uses albumin—an endogenous protein—to reversibly bind the cytotoxic and hydrophobic drug paclitaxel in order to improve its solubility. The manufactured product is a consortium of approximately 130 nm diameter Abraxane particles, which then dissociate into smaller albumin-paclitaxel particles (4-14 nm) upon injection65 (Figure 5). By taking advantage of both the EPR effect and receptor-mediated transcytosis pathways—which albumin affords access to—Abraxane can reach the tumour microenvironment in therapeutic concentrations65–67.

Figure 5 | Structure of Abraxane and depiction of in vivo particle dissociation Image adapted from “Clinical impact of serum proteins on drug delivery,” by F. Kratz and B. Elsadek, 2012, Journal of Controlled Release, 161, p. 429-44568. Copyright 2011 by Elsevier B.V. Adapted with permission under license 4257710823696, via RightsLink®.

Prior to the introduction of Abraxane, the main formulation of paclitaxel was Taxol: a solution of drug, ethanol, and the non-ionic solvent Cremophor EL69. Though the formulation was successful in forming a drug-solubilizing emulsion in aqueous solution, the Cremophor EL excipient was associated with a range of adverse effects in patients, including hypersensitivity reactions70–72. The nanoparticle formulation of paclitaxel with albumin allows for the hydrophobic paclitaxel to be solubilized for systemic circulation in the absence of poorly tolerated surfactants. As a result, paclitaxel formulated as Abraxane can be administered at a 49% greater dose than Taxol without premedication; this increase in maximum tolerated dose (MTD) substantively improved paclitaxel’s therapeutic index72.

Abraxane earned its original FDA approval in 2005 for the treatment of metastatic breast cancer, and subsequently earned marketing approval for pancreatic and non-small cell lung cancer (NSCLC) indications73. The worldwide nano-formulated paclitaxel market is thriving, with Abraxane sales fetching 973 million USD in 201674 and projected to reach 1.9 billion USD by 202075, and with several new nano-formulated paclitaxel competitors being approved in international markets and approaching licensure in North America and Europe76.

3 The difficulty with delivery

In order for nanomedicines to maximize their therapeutic potential in the context of modern oncology, they must: 1. Arrive at the tumour site from systemic circulation in therapeutic concentrations; 2. Penetrate the tumour and distribute therein; 3. Release active drug cargo, making it bioavailable within the tumour.

These delivery vehicles must be able to localize at the tumour, access its structure, and, once inside, expose the tumour to their cell-killing cargo. Unlike nanomedicines, traditional formulations of small molecule chemotherapies are not engineered to discriminate between the malignant and normal cells upon which they act and patients are liable to experience significant toxic effects during treatment. A guiding principle in the design of nanomedicines is to reduce off-target toxicity by limiting exposure to normal tissues. Viewing nanomedicine performance as a combination of cancer-killing efficacy and a therapy’s tolerability among patients—with an increasing emphasis on the latter—may encourage a positive shift toward patient-centredness in the practice of oncology. In this light, the impetus for overcoming challenges—described in this section—encountered during the development of drug delivery technologies that elicit holistic clinical benefit to patients is clear. An understanding of who among a patient population will benefit from nanomedicine treatment, along with the mechanisms underlying this phenomenon, is key to delivering clinical benefit.

3.1 Beyond the EPR effect: Addressing multifactor heterogeneity

A heavily emphasized concept in nanomedicine literature is the EPR effect, which hypothesizes that a tumour’s leaky neovasculature and impaired lymphatic drainage allows a long-circulating nanomedicine to enter the tumour interstitium and remain there for a period long enough to release its drug payload47.

It is widely accepted that cancer is a highly heterogeneous disease77–79 and the extent to which the EPR effect facilitates drug delivery varies between patients and even between tumours within the

same patient. Harrington et al. demonstrated this heterogeneity in human tumour accumulation between patients having the same and different cancer types over 15 years ago80. The study elucidated the biodistribution and pharmacokinetics of pegylated liposomes labeled with 111In- * DTPA in 17 patients having a variety of locally advanced cancers by whole body gamma scintography: tumour accumulation of the liposomes ranged from 33.0 ± 15.8% ID/kg (percent of injected dose/kg) in head and neck cancers to 5.3 ± 2.6% ID/kg in breast cancers. This research demonstrated the capacity of pegylated liposomes to accumulate at high concentrations in human solid tumours and reside therein for long periods of time, but these concentrations and durations are highly heterogeneous across different tumour types and across patients having the same tumour type80. In 2017, Lee et al. also sought to assess the EPR effect by analyzing PET/CT imaging of 64Cu-labeled HER2-targeted pegylated liposomal doxorubicin (64Cu-MM- 302) administered to women with HER2-positive metastatic breast cancer81. Results of this work indicated a high degree of heterogeneity between lesions in the same patient, suggesting that accumulation of 64Cu-MM-302 was governed more by characteristics of the individual lesion, rather than characteristics of the diagnostic nanomedicine. These results are discussed further in Section 3.2.

As a result of studies like those described above, consensus in cancer nanomedicine has been reached on one important point: delivery of nanomedicines to cancer cells is more complex than can be explained solely by the factors originally posited to facilitate the EPR effect. Decades of research have found that a multiplicity of factors govern nanomedicine accumulation in a tumour82–86, many of which are associated with the complexity and heterogeneity inherent to the tumour microenvironment (features depicted in Figure 6). The magnitude of the EPR effect across biological systems has been shown to be context-dependent and susceptible to change by modulating factors like stromal volume, macrophage abundance, interstitial fluid pressure, microvessel density and leakiness, and blood flow87,88.

* Diethylenetriaminepentaacetic acid 14

Figure 6 | Example of tumour microenvironment composition and organization Image adapted from “Tumor microenvironment at a glance,” by F.R. Balkwill, M. Capasso, and T. Hagemann, 2012, Journal of Cell Science, 125, p. 5591-559689. Copyright 2012 by Company of Biologists Ltd. Adapted with permission under license 4257780586977, via RightsLink®. Acronyms: natural killer cells, NK cells; natural killer T cells, NKT cells; cancer-associated fibroblast, CAF. White lines are artifacts from copyright holder’s original publication.

Since the time of Harrington’s key demonstration of variability in nanomedicine delivery across patients, cancer types, and tumours of the same cancer type, advances have been made in understanding factors that affect nanomedicine delivery, but new products and clinical trial designs that take advantage of this knowledge are just beginning to be developed.

3.2 Indicators of nanomedicine delivery

A modern understanding of the complexity and variability of nanomedicine drug delivery has provided the impetus for developing companion diagnostic tests to screen for patients whose physiology might best facilitate tumour accumulation, perhaps leading to improved clinical benefit90,91. One example is ferumoxytol, a dextran-coated magnetic nanoparticle approved by the FDA to treat iron deficiency, which has been used pre-clinically as a surrogate indicator of nanomedicine uptake92. Also, monitoring levels of circulating blood markers MMP9 and TIMP1 has given researchers early insight into EPR effect magnitude and its influence on liposome delivery93,94. Several recent reviews discuss companion diagnostics for nanomedicines, factors affecting and tools for modulating EPR, and barriers to drug delivery88,95,96.

Predicting a patient’s pharmacokinetic (PK) disposition toward nanomedicines has the potential to inform improved trial designs. As proof-of-concept, MM-DX-929 (a 64Cu-liposomal PET agent) was administered prior to therapy with MM-302 (HER2-targeted pegylated liposomal doxorubicin) and could accurately predict inhibition of tumour growth in mice bearing mammary and subcutaneous BT474-M3 tumours97. Testing the concept in the clinic, 64Cu-MM-30298 was administered to 19 patients with HER2-positive metastatic breast cancer81 during the course of a * clinical trial of MM-302 (NCT0130479799) . From PET/CT image analysis, patients could be classified into ‘low uptake’ or ‘high uptake’ strata based on tumour deposition levels. Retrospective analysis indicated a correlation between high 64Cu-MM-302 deposition and better treatment outcomes: 43% of low uptake patients experienced stable disease (SD) with no partial

* Described in Section 3.1 16

response (PR) and a 1.7-month progression-free survival (PFS), while 75% of high uptake patients experienced SD and/or PR and a 2.0-month PFS.

Pretreatment administration of such imaging agents could allow for the non-invasive determination of a nanomedicine’s PK profile and could highlight patient groups wherein the delivery of nanomedicines to tumours is best facilitated. Patient stratification by characteristics predictive of efficient drug delivery acts to improve the likelihood of patients benefitting from treatment—and, importantly, to reduce the likelihood of unnecessarily treating those who will not. Indications of tumour penetration and drug release remain important in predicting how a nanomedicine might benefit patients, but using indications of tumour localization like PK and EPR effect magnitude as patient selection criteria in clinical trials represent an important first step.

Stratifying patients according to a biomarker is not a novel concept, especially in the context of targeted cancer therapies. For example, just 10-20% of newly diagnosed breast cancers are HER2 receptor positive100 and only these tumours will respond to the targeted monoclonal antibody drug trastuzumab (Herceptin)101. If tested against an unselected population of women with breast cancer, this paradigm-shifting medicine—the OS of HER2-positive breast cancer patients saw a 3.0-year improvement since Herceptin’s introduction102—would have failed in trials and never reached the clinic.

3.3 Performance measures

Pre-clinical studies frequently measure the efficacy of cancer nanomedicines by determining their bulk tumour accumulation. However, there are data to indicate that nanoparticle accumulation at the tumour site is not principal among performance metrics for determining efficacy: the quantity of local, bioavailable drug is what elicits a cancer-killing effect. For example, human trials of liposome formulations of cisplatin (Lipoplatin and SPI-77) have demonstrated that though liposome accumulation in tumour tissue reached levels up to 50 times

greater than in healthy tissue, treatment of patients with stage IIIB or IV NSCLC demonstrated limited therapeutic activity103–105. Post-treatment examination of tumour levels of platinum-DNA adducts—evidence of drug activity—suggests that cisplatin was released too slowly from its carrier liposome to have been effective104. Metrics like bulk tumour accumulation of % ID of nanoparticles at the tumour site speaks to a nanomedicine’s ability to localize, but not its therapeutic efficacy106: they are related, but separate concepts.

4 Toxicity reduction

While approved nanomedicines have provided improvements in therapeutic efficacy—typically measured by OS, or surrogate endpoints like progression-free survival (PFS), time to tumour progression (TTP), or objective/overall response rates (ORR)—one area in which the technology has shown appreciable success is in improving the toxicity profile of chemotherapeutic agents. One example is the use of pegylated liposomal doxorubicin (PLD, or Doxil/Caelyx).

PLD earned accelerated approval from the FDA to treat AIDS-related Kaposi’s sarcoma in 1995, and full approval in 1997, by demonstrating superior ORR relative to the era’s standard of care: a combination of doxorubicin (Adriamycin®), bleomycin, and vincristine (ABV)59. In 1998, PLD was approved to treat recurrent ovarian cancer on the basis of similar ORR in the intent-to-treat population, superior OS in a platinum-resistant sub-group, and an improved safety profile compared to topotecan107. PLD has since gained approval to treat metastatic breast cancer108 and multiple myeloma (in combination with vincristine and dexamethasone)109 on the basis of demonstrating similar efficacy (PFS and PFS/ORR/OS, respectively) to free doxorubicin comparators and demonstrating improved safety.

Free doxorubicin is known to cause cumulative dose-dependent cardiotoxicity110,111 in humans. A Phase III clinical trial studying women with metastatic breast cancer and normal baseline cardiac function found that those treated with PLD had a significantly lower risk of cardiomyopathy

compared to those treated with free doxorubicin, while the two groups were similar with respect to PFS and OS108. In addition, treatment with PLD is associated with lower rates of side-effects common among chemotherapeutic drugs like nausea and vomiting, myelotoxicity, neutropenia, and hair loss than free drug comparators (though PLD can introduce skin toxicities like palmar- plantar erythrodysesthesia [hand-foot syndrome])59,108,109.

Free doxorubicin has been associated with complete hair loss in over half of treated patients, whereas only 7% of patients reported this degree of hair loss as a result of treatment with PLD108. While hair loss is non-life-threatening, any factor that promotes the conservation of QOL can be considered important in determining the benefit a therapy is delivering to patients, especially in light of the fact that most chemotherapy is administered to patients with palliative, rather than curative, intent112.

5 Quality of life

Ensuring a patient’s overall well being by providing care that, as much as is possible, conserves the quality of living is a foundational goal in medicine. While this aim is well accepted and the idea of QOL is understood broadly within and without the medical community, defining the concept is nontrivial. Also, integrating patient QOL into the quantitatively rigorous paradigm of modern healthcare has proven a challenge, requiring careful contextualization and parameterization of the term.

While the evaluation of QOL is important in many contexts, including global development and government, its assessment there involves good health, but necessarily includes factors like wealth, crime, education and training, and factors bound up in the environment113. The term health-related QOL (HRQOL) refers to QOL applied to areas of life that are most sensitive to changes in health and illness, differentiating it from broader definitions114.

The World Health Organization defines HRQOL as follows:

An individual’s perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns. It is a broad concept affected in a complex way by the person’s physical health, psychological state, personal beliefs, social relationships, and their relationship to salient features of their environment115.

Owing to marked improvements in cancer care during and after the 1970s that enabled the realization of extended survival of patients with many cancers, concern for patients’ psychosocial well-being gained importance in the clinic and the literature116,117. With the development of new therapies that allowed physicians and patients to opt for alternate treatment pathways, assessments that weighed the multidimensional costs of treatment against their benefits became critical to oncology, acknowledging that many cancer treatments are associated with deleterious effects on health and overall well-being118. Chemotherapy may improve HRQOL by reducing symptoms, or it may reduce HRQOL by introducing treatment-related toxic effects119.

Through the measurement of HRQOL, researchers can assess the clinical benefits of treatment in terms separate from, but correlated with, traditional endpoints like survival and treatment toxicity120. HRQOL measurement seeks to assess patients’ subjective perceptions of their disease symptoms, treatment side effects, physical functioning, social functioning, life satisfaction, mental health—which includes emotional health and cognitive function121—and other key domains such as sexuality and spirituality122. An understanding of how patients experience changes on these dimensions can provide information to support and add value to traditional biochemical outcome measures used in oncology114. There is also evidence that HRQOL is an indicator of prognosis: pretreatment HRQOL scores have been found to be predictive of overall survival and a patient’s response to treatment123,124, underscoring its potential value-add in the context of cancer clinical trials.

Many dimensions considered in HRQOL assessment are intensely personal and inherently subjective, and, as such, these data must be yielded from patient self-reports. Even on dimensions that appear accessible for doctors to observe and evaluate—e.g. severity of disease symptoms, treatment side effects, physical functioning—research has uncovered great discord between the reports of patients and doctors125–130, indicating the latter group as unsuitable instruments for this type of measurement. Any data a patient reports directly—without outside interpretation, e.g., by a physician or family member—can be considered patient-reported outcomes (PROs), and the process of obtaining such data is a PRO measurement (PROM). Thus, HRQOL is a type of PRO and HRQOL assessment is a type of PROM131.

5.1 Measuring HRQOL

The earliest organized attempts at measuring HRQOL in patients were completed, largely, by physicians and came in the form of unidimensional scales like the Karnofsky Performance Scale (KPS)132 and the Eastern Cooperative Oncology Group Performance Scale (ECOG PS)133. On each of these performance scales, the patient is allocated a score that summarizes their ability to perform daily activities and the level of assistance they require: 0 (dead) to 100 (fully active, no sign of disease) for KPS; 0 (fully active) to 5 (dead) for ECOG PS134. Though helpful to physicians for quick assessments of well being or for determining patients’ eligibility in clinical trials, these scales are open to the physician’s bias and are frequently plagued with high interrater variability, all the while providing very little detail on patients’ HRQOL119.

Modern HRQOL instruments have their contents and administration centred firmly about the patient, emphasizing a shift toward PROs in recent decades8. A modern HRQOL instrument is designed to have a scope appropriate for its intended clinical context and to only assess aspects of HRQOL that are important to the specific patients under study122. HRQOL instruments are designed to be simple to understand and non-strenuous to complete by patients, acknowledging possible disease- or treatment-related hindrances122. Also, a modern HRQOL instrument is validated to ensure that: it measures the intended effect (construct validity); it yields similar results given similar inputs (test-retest reliability); related attributes yield correlated data

(convergent validity); items designed to measure different aspects yield distinguishable data (divergent validity); it is responsive to changes in a patient’s condition (responsiveness)119,135.

Examples of modern HRQOL instruments used in oncology include the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core Module (EORTC QLQ-C30)136 and the Functional Assessment of Cancer Therapy – General (FACT-G)122. These instruments comprise series of questions grouped by HRQOL domain that a patient responds to by filling out a Likert-style scale. For example, in the ‘physical well-being’ domain of the FACT-G, a patient is asked how well the statement “I have a lack of energy” applies to them by circling: 0 (not at all), 1 (a little bit), 2 (somewhat), 3 (quite a bit), or 4 (very much)122. HRQOL items are scored by summing responses in each domain. Assessments of changes in a specific domain or in overall HRQOL can be made by comparing post-treatment and pre-treatment scores, or by comparing scores interval-by-interval during a clinical trial.

Instruments like the EORTC QLQ-C30 and FACT-G form the basis of most HRQOL assessments of cancer patients, which allows for cross-study comparison of these general domains and items124. HRQOL instruments that are specific to the disease or treatment of interest have also been developed in an effort to improve sensitivity to effects peculiar to those contexts. Examples of these include a breast cancer specific module to complement the EORTC QLQ- C30—the QLQ-BR23137—and a taxane chemotherapy specific module to complement the FACT-G—the FACT-Taxane138. Specimens of the general EORTC QLQ-C30 and the breast cancer-specific EORTC QLQ-BR23 can be found in Appendix A.

6 Regulatory approval process for cancer medicines

For the approval of drugs in the U.S., regulators at the FDA require evidence of holistic clinical benefit from “adequate and well-controlled investigations”139. Clinical benefit describes the provision of a longer life or a better life140: in the context of oncology, drugs would ideally achieve both112.

The FDA has two main routes available for the marketing approval of cancer drugs: traditional (‘regular’) approval, or accelerated approval. Regular approval requires that a therapy is safe and that it demonstrates prolongation of life, improvement of life quality, or an established surrogate measure for either of these. Accelerated approval, which was introduced by the FDA in 1992 in response to the AIDS crisis140,141, allows for the expedited licensure of drugs treating serious or life-threatening diseases that appear to provide a benefit over therapies that are currently available142,143. Accelerated approval allows clinical benefit to be demonstrated with evidence yielded from endpoints that are “reasonably likely” to predict a prolongation of life or a better QOL142. Surrogate endpoints—less established and less direct indications of clinical benefit—are typically used as evidence for accelerated approval, such as response rates and time-to-event endpoints like ORR and TTP, respectively. The FDA has committed to making licensure decisions using this more tenuous evidence to allow expedited access to potentially life-saving drugs. As a safeguard against long-term marketing of new and typically expensive drugs that offer no clinical benefit144, the FDA requires post-approval (or postmarketing) clinical trials be performed in order to confirm that the candidate drug provides clinical benefit according to the surrogate endpoint’s original prediction140. If postmarketing studies successfully confirm clinical benefit, a drug application can be converted from accelerated approval to regular approval145. Conversely, if a drug sponsor does not undertake postmarketing studies or is unable to realize the predicted clinical benefit within a pre-negotiated period of time, regulations allow the FDA to remove this drug from market145.

6.1 Patient-centred drug development

Acknowledging that many approved cancer drugs yield small survival benefits measured in weeks, the oncology community is becoming increasingly interested in the efficacy-toxicity balance of treatments146: data describing how similar patients have experienced similar treatment are critical to informing modern treatment decisions. Though the inclusion of PROs in clinical trials has been increasing—from 14% of trials registered with ClinicalTrials.gov using at least one PROM in 2007 to 27% in 2013—more than two thirds (71%) of all oncology trials examined over 2007-2013 included no PROMs at all147. Additionally, when PROMs like HRQOL were 23

assessed, the analysis and reporting of that data was found to be highly variable, which presents challenges for interpretation among clinicians and interested patients alike148.

To address these issues, the U.S. Food and Drug Administration (FDA) has set processes in motion to encourage the inclusion of patient perspectives in drug development during recent years, including the publication of guidance documents outlining the rigorous design, administration, and analysis of PROs to support marketing applications and labeling claims8. In his 2013 New England Journal of Medicine perspective, Dr. Ethan Basch outlined six key steps (paraphrased here) drug developers and regulators could take to further their push toward patient- centred drug development in oncology146: 1. Identify patient-centred outcomes through direct patient feedback at the earliest stages of drug development 2. Discuss plans for measuring and analyzing patient-centred outcomes in formal developer-regulator meetings 3. Develop or select measures to evaluate outcomes using established qualitative and quantitative methods before pivotal clinical trials to ensure that key and exploratory patient-centred endpoints were appropriately selected and that anticipated effects are likely to be observed 4. Include PROMs in pivotal clinical trial with plans for analysis specified in the study protocol, which include strategies for minimizing and handling missing data 5. Engage patients representative of the target population to inform inclusion criteria, outcomes, endpoint design, comparators, and strategies for retaining participants 6. Include PROs on the drug label to help patients and providers with treatment decision making

Patient perspectives of their own treatment could provide key guiding information for future of cancer care and drug development, especially in an era when most chemotherapy is given with palliative intent6,112. The systematization of PRO integration in pivotal clinical trials and the subsequent reporting of this data will help to ensure the continued adoption of these endpoints by

clinicians and the accessible communication of salient, treatment decision-informing PRO data to patients146,147,149.

7 Rationale

This research seeks to collate evidence of clinical benefit—the provision of a longer life or a better life—engendered by cancer nanomedicines approved for the treatment of cancer. Major claims in the cancer nanomedicine literature include the technology’s capacity to improve cancer-killing efficacy and to reduce systemic toxicity. This research seeks to evaluate the validity of these claims from the perspective of the clinic, with a particular focus on nanomedicines’ capacity to conserve or improve patients’ HRQOL relative to comparator therapies.

In a time when many cancers have available a range of treatment options and durations of survival with the disease are improving—with great proportions of the Canadian9 and American150 populations living with cancer or a history of it—attending to the HRQOL of patients and the tolerability of treatment is gaining relevance in oncology practice146. As a technology developed with the intention of reducing off-target toxicity, cancer nanomedicine has the potential to deliver effective therapy while mitigating factors that can diminish patient safety and HRQOL.

This research asks the questions: • How are cancer nanomedicines delivering clinical benefit to patients? • What evidence is being presented to support claims of clinical benefit? • Can the application of strong HRQOL collection, analysis, and reporting practices advance patient-centred care in oncology? • Where do trials of cancer nanomedicines currently stand with respect to these practices?

7.1 Grounding in engineering design

This research is presented for consideration as a master’s of applied science thesis. Engineering projects characteristically begin with the development of a problem statement, which comprises

the evidence-based formulation of a problem facing humanity, the presentation of previous solutions, and the identification of a gap that exists between them: the unmet need151. This gap outlines the design space in which an engineer works to develop solutions that satisfy the unmet need, and identifying this gap requires a holistic examination of the problem. This research is presented as a work of gap-delineation in the area of clinical cancer nanomedicines, their applications for marketing approval, and their role in patient-centred oncology. Proposals for the development of early-stage solutions to satisfy the unmet needs discovered here are presented as part of this work also, mirroring the conceptual design stage of an engineering project.

Chapter 2 Analysis of anticancer efficacy, quality of life, and safety benefits associated with marketed nanomedicines 1 Introduction to analysis

This investigation consolidates information from American or European regulatory approvals of cancer nanomedicines, analyzes trends in evidence provided to support regulatory approval, and sheds light on whether these drugs have engendered clinical benefit in real-world populations with respect to anticancer efficacy, HRQOL, and safety. This investigation considers only those nanomedicines that have been granted marketing approval, and therefore focuses on the most clinically successful agents. From these, information around what regulators demand to support new drug applications (NDAs) can be gleaned. Depending on the approval type being pursued, different kinds of evidence are required, but, in the end, clinically meaningful benefit must be demonstrated to be a marketed cancer drug.

Applications for marketing approval by the FDA do not require direct comparison of candidate drugs with standard of care medications as proof of improved clinical benefit in terms of efficacy, HRQOL, and safety, frequently do not incorporate gold standard efficacy endpoint data like OS time, and rarely provide rigorous evaluation and discussion of a drug’s effect on HRQOL using validated HRQOL instruments152,153. To address this void in direct evidence of clinical benefit, this investigation also amalgamates information relating to the clinical risks and benefits engendered by approved cancer nanomedicines in the context of expanded study populations, more rigorous trial endpoints, and more mature data compared to that which was provided for licensing approval in the US and Europe. To do this, clinical evaluation, scientific discussion, and summary conclusion-type documents were collected and reviewed from English (The National Institute for Health and Care Excellence, NICE), French (Haute Authorité de Santé, HAS), Australian (Pharmaceutical Benefits Advisory Committee, PBAC), and Canadian (Canadian Association for Drugs and Technology in Health, CADTH) health technology assessment (HTA) agencies.

HTAs examine the short- and long-term consequences of incorporating a new technology into a healthcare system, with the purpose of informing national policy and funding decisions154. HTAs are undertaken when technologies emerge that have potential to give rise to significant impacts on a healthcare system, as when a new medicine is developed that is likely to replace the existing standard of care therapy. HTA of a given medicine typically involves a comparative assessment of its safety, efficacy, PROs, and cost against current alternative clinical strategies154,155. In the US, a range of publicly and privately funded organizations produce varied forms of HTA, but connections between assessment recommendations and national policy decisions are indirect on account of the country’s lack of a universal healthcare coverage apparatus*. For these reasons, HTAs from US agencies were not collected as part of this study.

Taken together, this evidence can give a sense of how marketed cancer nanomedicines are performing in the real world, where there are voids of evidence at different stages of the approval process, and, though each new nanomedicine has distinct physical, chemical, and clinical characteristics, may inform how future cancer nanomedicine developers conduct clinical trials to benefit from common strengths.

2 Methods 2.1 Inclusion and exclusion criteria

All therapies approved by the FDA and EMA that are considered nanomedicines—typically liposomal or solid nanoparticle drug delivery systems ranging from 1 to 1000 nm in diameter— and having a primary indication for cancer therapy were eligible for inclusion in this investigation*. A group of eligible cancer nanomedicines was determined by amalgamating and

* The FDA focuses their evaluations on pre-licensing studies of drug efficacy, safety, and HRQOL effects, but does not conduct formal technology assessment, as real-world effectiveness and cost-effectiveness lie outside their scope of work. * The full range of engineered nanomaterials intended for use in biomedical applications—which, for example, would include gold nanoparticles for potentiating radiotherapy272 and radiotracer-decorated nanoparticles for 28

filtering previously compiled lists of approved and in-trial nanomedicines95,156–161 and screening FDA13 and EMA163 drug registries for new approvals until November 15, 2017. Nano-formulated biological products were considered to be outside the scope of this work: FDA approvals of biological license applications (BLAs)—as opposed to NDAs—were excluded from analysis (e.g. Kadcyla, Ontak, Oncaspar).

As sources of information for this investigation included only published reports and no patient- level data, this study was determined exempt from institutional review board approval.

2.2 Regulatory approvals

The proprietary and scientific names of each eligible cancer nanomedicine were used to query the FDA drug registry in order to access original approval documents, including original drug labels, approval letters, and committee reviews (summary, medical, or statistical), if available. If a drug was not approved for marketing in the U.S. as of November 15, 2017, approval information was sought from the EMA in the form of European Public Assessment Reports (EPAR) documents, including ‘Summary for the Public’, ‘Product Information’, ‘Assessment Report’, and ‘Scientific Discussion’ documents, if available.

Regulatory documents were selected for review only if they pertained to each cancer nanomedicine’s clinical indication of original approval. Several nanomedicines have received

diagnostics88—is broader than the scope of this investigation. Here, “nanomedicine” refers to nano-sized drug delivery systems (NDDSs) whose therapeutic advantages owe mainly to their size, increased residence time in systemic circulation, and capacity to solubilize drug cargo that would otherwise be poorly soluble or insoluble in the bloodstream. 29

supplementary approval for new indications since their original marketing approvalς, but these were considered outside the scope of this investigation.

Key information recorded from regulatory approval documents included details of a cancer nanomedicine’s original indication, approval date, approval type, trial comparator(s) (if any), clinical endpoints employed, and evidence of clinical benefit supporting approval, as parameterized by anticancer efficacy, HRQOL, and safety. Main anticancer efficacy outcomes were reported according to their corresponding metrics (e.g. OS in months, response rates in %).

HRQOL and safety benefits were categorized as improvement, none established, reduction, NA, or, if a trial was non-comparative, a category reserved for overall judgments. ‘Improvement’ indicates that a regulatory approval document specifically referred to the drug’s positive effect on patient HRQOL† or safety*. ‘None established’ indicates a specific reference to treatment- associated HRQOL or safety effects that reported no statistically significant change. ‘Reduction’ indicates a specific reference to treatment-associated HRQOL or safety effects that reported a negative statistically significant change on account of the study drug. ‘NA’ indicates that treatment-associated HRQOL or safety was not specifically referenced in the regulatory approval documents and was likely not assessed as part of the pivotal trial in question. The overall judgment category is used in the case of non-comparative trials and contains a one-word

ς For example, Abraxane was granted its original marketing approval by the FDA in 2005 as a drug indicated for the treatment of metastatic breast cancer. In response to supplementary applications, the FDA granted Abraxane approval as a drug indicated for the treatment of advanced non-small cell lung cancer (2012) and metastatic pancreatic cancer (2013). Only Abraxane’s metastatic breast cancer indication was considered in this investigation162. † Strongest evidence for HRQOL came in the form of statistically significant improvements on some or all domains of validated HRQOL instruments. * Strongest evidence for safety came in the form of statistically significant improvements in the frequency of adverse event (AE) observation, treatment termination rates, or dose-limiting side effects. 30

judgment‡ gleaned from the regulatory approval documents on the drug’s general effect on HRQOL or safety.

2.3 Health technology assessments (HTAs)

Methods for collecting, reviewing, and synthesizing HTA information on approved cancer nanomedicines were adapted from Salas-Vega et al.164, who evaluated the comparative therapeutic value of all cancer medicines approved as new molecular entities (NMEs) by the FDA or EMA between 2003 and 2013 using a narrative synthesis approach165,166. The present study follows this same approach but instead evaluates all eligible cancer nanomedicines to have been approved by American or European regulators, without temporal restriction.

This author collected and reviewed clinical evaluation, scientific discussion, and summary conclusion documents from Canadian (CADTH), English (NICE), French (HAS), Australian (PBAC), and European (EPAR) HTA agencies. HTAs were selected for review if they assessed the same therapeutic target as the original FDA-approved indication. If multiple reports from a single agency evaluated the same target condition, the latest report that most closely matched the original FDA-approved indication was selected for review. EMA-approved indications were used if the FDA had not approved the drug before November 2017.

European Public Assessment Reports (EPARs), which are produced by the EMA alongside their licensing decisions, were included as part of this HTA analysis in order to fill voids in assessment information available on cancer nanomedicines. EPARs, unlike most modern FDA filings and reviews, generate overall conclusions on their opinion of a drug and formulate a benefit/risk statement with each report.

‡ “Reasonable” was a frequently assigned judgment among regulatory documents wherein non-comparative clinical trials provided the basis for approval, especially when describing safety profiles. Often, if the toxicity profile of a NDDS was not obviously different from comparable drugs, or its free-drug counterpart, the drug’s safety profile was described as “reasonable” by regulators. 31

2.4 Data extraction and synthesis

As inspired by Salas-Vega et al.164, a ‘patient, intervention, comparator, outcomes’ framework for systematic reviews167 was used to review HTAs of the clinical impact of approved cancer nanomedicines. Information on the drugs’ primary indication, alternate names, orphan drug status*, marketing status, and the HTA agency’s overall recommendation regarding drug reimbursement was extracted from each drug appraisal. Evaluations of each nanomedicine’s impact on OS, HRQOL, and safety were also extracted from HTAs, considering only key outcome measures that are typically used as part of formal drug reviews140,168.

Evidence typically reported by HTA agencies for OS include median OS, mean OS, and survival probability. Measures typically reported for HRQOL include scores from validated HRQOL instruments, symptom improvement, impacts on patient function and utility, expectations of HRQOL impact (e.g. convenience of treatment schedule versus comparators), patient advocacy group statements on HRQOL, and clinical expert statements on HRQOL. Measures typically reported for safety include total incidence of adverse events (AEs), incidences of mild, moderate, severe, and life-threatening AEs, treatment discontinuations, overall statements on tolerance and safety profile, patient advocacy group statements on safety, and clinical expert statements on safety.

To synthesize and evaluate evidence reported by HTA agencies, this author followed a rules- based process. HTA agency reports of OS, HRQOL, and safety were considered valid for this investigation in cases where overall judgments were available from HTA summary sections, if original data was presented as part of the HTA, or if statements were made about the significance of the clinical trial results. If none of these were available, the corresponding dimension of the drug’s ‘Health Technology Assessment Summary’ table was marked ‘NA’ (Appendix B). OS

* Verified by consulting Orphanet273. 32

benefits were categorized as 3 months or longer, less than 3 months*, increase but of unknown magnitude, and no increase established. HRQOL and safety benefits were categorized using a rationale similar to the one used in Section 2.2, sorted into categories of improvement, none established, reduction, mixed evidence, or NA.

This analysis used a hierarchical process to generate a composite measure of OS, HRQOL, and safety when more than one HTA was available to evaluate a given cancer nanomedicine. For OS, the most positive treatment-associated survival benefit was selected if many HTAs with disparate OS values were available, highlighting the upper bound of OS improvement available with the drug. For HRQOL and safety, if one HTA agency indicated an overall improvement in therapy while another found that no change was demonstrated, the drug was classified here as engendering a net positive change. If opposing evidence existed among HTAs, the drug was classified as being associated with mixed results. Overall HTA recommendations deciding drug reimbursement also followed this hierarchical process to yield its composite measure. Descriptive statistics were used to summarize the composite measures of OS, HRQOL, and safety impact generated here.

3 Results 3.1 Basis for approval of nanomedicines

The FDA and EMA have approved nanomedicines for the treatment of cancer from as early as November 1995 and to as recently as May 2017. In all, this review of approved nanomedicines yielded nine eligible drugs, which can be found in Table 1 organized by NDDS type and by date of marketing approval, from least to most recent.

* This binning scheme acknowledges the general definition of clinically meaningful prolongation of life set by NICE: ≥ 3 months175,176. 33

Table 1: Eligible Cancer Nanomedicines and their Original Bases for FDA or EMA Marketing Approval Drug Name FDA- or EMA- Approval Evidence Supporting Original Approval (NDDS API(s) Approved Comparator(s) Endpoints Date Type Efficacy Effect HRQOL Effect Safety Effect platform) Indication Abraxane Metastatic breast 2005- None None Paclitaxel R Taxol RR (recTLRR) 21.5% vs. 11.1% (albumin NP) cancer 01-07 established established Doxil/Caelyx AIDS-related 1995- RR: 27% TTP: 73 Doxorubicin AA None RR, TTP NA Reasonable* (liposome) Kaposi's sarcoma 11-17 days (median) Daunoxome AIDS-related 1996- None Daunorubicin R ABV RR, TTP None established† Improvement (liposome) Kaposi's sarcoma 04-08 established Depocyt Lymphomatous 1999- Cytarabine AA Cytarabine RR 41% vs.6% RR Improvement§ Reduction (liposome) meningitis 04-01 Doxorubicin + CPA; Myocet Metastatic breast 2000- Doxorubicin R doxorubicin; RR None established NA Improvement (liposome) cancer (EMA) 07-13 epirubicin + CPA Doxorubicin + Mepact Muramyl Osteosarcoma 2009- Cisplatin + R DFS 68% vs. 61%∥ NA Reduction (liposome) tripeptide (EMA) 03-06 Methotrexate (+/- ifosfamide) RR = 15% (ORR) TTP = 28 days Ph-negative acute Marqibo 2012- RR, TTP, (median) Vincristine lymphoblastic AA None NA Reasonableδ (liposome) 08-09 Bridge⊥ 8% subsequent stem leukaemia (ALL) cell transplant rate after CR or CRi Fluorouracil / OS: 6.2 vs. 4.1 mo. Onivyde Metastatic 2015- OS, PFS, ϕ Irinotecan R leucovorin PFS: 3.1 vs. 1.5 mo. NA Reasonable (liposome) pancreatic cancer 10-22 ORR (5-FU/LV) ORR: 7.7% vs. 0.8%

7+3 Cytarabine + Acute myeloid combination Vyxeos daunorubicin 2017- leukaemia (AML): R of cytarabine OS 9.6 vs. 5.9 mo. NA Reduction (liposome) (5:1 fixed 08-03 t-AML or AML-MRC and molar ratio) daunorubicin

Source: Author’s analysis of data from sources defined in Methods.

Acronyms:

Nano drug delivery system, NDDS; active pharmaceutical ingredient, API; U.S. Food and Drug Administration, FDA; European Medicines Agency, EMA; nanoparticle, NP; response rate, RR; reconciled target lesion response rate, recTLRR; acquired immunodeficiency syndrome, AIDS; regular approval, R; accelerated approval, AA; objective response rate, ORR; time to progression, TTP; not assessed, NA; adriamycin, bleomycin, vincristine combination chemotherapy, ABV; cyclophosphamide, CPA; Philadelphia chromosome, Ph; complete response, CR; complete response with incomplete haematological recovery, CRi; fluorouracil, 5-FU; leucovorin, LV; progression-free survival, PFS; month, mo; therapy-related acute myeloid leukaemia, t-AML; AML with myelodysplasia-related changes, AML-MRC; Karnofsky Performance Score, KPS; Mini-Mental State Examination, MMSE; Functional Assessment of Cancer Therapy questionnaire – Central Nervous System module, FACT-CNS; Oncologics Drugs Advisory Committee, ODAC.

Notes:

*PPE presentation in 3.4% of patients, with 0.9% discontinuing. Dose modification could ameliorate effects. Myelosuppression was dose limiting adverse event.

§Claimed improvement with respect to KPS, MMSE, and FACT-CNS scores, but too much missing data to make conclusion. In their AA recommendation, FDA’s ODAC committee indicated that “DepoCyt provides a meaningful advantage over existing treatments,” citing its “more convenient treatment schedule” as a factor providing this meaningful advantage, prompting the drug’s HRQOL effect being noted as an “improvement” in this analysis.

†Non-statistically significant trends toward improvement vs. comparator.

∥28% reduction in risk of death" (HR = 0.72). Patients followed for up to 10 years.

⊥ Marqibo is termed a ‘bridge’ treatment: this therapy enables patients to access stem cell transplants.

δ No change from vincristine: "No new or unexpected AEs were observed with VSLI. The overall frequency and severity of these AEs did not appear to be superior to vincristine.”

ϕ Safety data drawn from single-arm trial: no comparator.

Eight of the nine approved nanomedicines are liposomal formulations of active pharmaceutical ingredients (APIs), while one, Abraxane, comprises the API paclitaxel bound to albumin nanoparticles. Seven unique APIs are included in the nine approved nanomedicines: paclitaxel, doxorubicin, daunorubicin, cytarabine, mifamurtide, vincristine, and irinotecan. These APIs can be classified according to four broad anticancer drug categories: microtubule inhibitors (or antimitotic agents), nucleoside analogs (or DNA/RNA intercalators), topoisomerase inhibitors, and immunomodulators (or monocyte and macrophage activators)(Figure 7). The most recently approved nanomedicine, Vyxeos, comprises a combination of two APIs in a fixed 5:1 molar ratio; the combination may help to avoid the development of drug resistance and is suggested to be a synergistic ratio of daunorubicin and cytarabine, possibly causing the combined anticancer effect to be greater than the sum of the individual effects of these drugs64,169.

The originally approved indications for the nine drugs cover five cancer targets: breast, skin and mucosa (AIDS-related Kaposi’s sarcoma)170, blood (leukaemia and lymphoma), bone (osteosarcoma), and pancreas. Supplementary applications from pharmaceutical sponsors of these nanomedicines have resulted in these drugs being indicated for a broader range of cancers, including ovarian cancer, multiple myeloma, melanoma, lung cancer, and brain cancer88,95.

Regular approval was granted in the case of six of nine drugs’ original clinical indication, while three were granted accelerated approval. Regular approvals were all granted using evidence from randomized controlled trials (RCTs). Four of six regular approvals demonstrated anticancer efficacy using OS (or a long survival time surrogate of OS*) as a

* Mepact used disease-free survival (DFS) as a surrogate of OS on account of the long survival times afforded by treatments of paediatric osteosarcoma. In the studies that granted Mepact its original approval, subjects were followed for up to 10 years. Retrospective analyses reported a 6-year OS of 78% in the Mepact-including trial arm and 70% in the chemotherapy-only arm (P = 0.03)274.

API Delivered API Anticancer Action Category Action Anticancer API

NDDS Type

General Cancer Indication Cancer General

Figure 7 | Breakdown of approved cancer NDDS types, APIs delivered, API anticancer action categories, and general cancer indications covered. Anthracycline drugs (e.g. daunorubicin and doxorubicin) engage in cancer-killing action both as DNA/RNA intercalators and as topoisomerase inhibitors171. Acronyms: Nano drug delivery system, NDDS; active pharmaceutical ingredient, API. This Sankey diagram was generated using open tools at sankeymatic.com

primary trial endpoint, while two provided alternative evidence of clinical benefit that was compelling enough to convince regulators of their suitability for regular approval†. Accelerated approvals were granted for Doxil/Caelyx and Marqibo based on single-arm clinical trials, but each with compelling evidence of clinical efficacy in disease areas that are—or were at the time of approval—considered life threatening and have available few alternative treatment options. Depocyt was granted accelerated approval using evidence from a RCT and demonstrated advantage over an existing treatment (cytarabine) on the basis of RR.

Each drug granted accelerated approval was assigned postmarketing study responsibilities in order to verify the clinical benefit predicted by its surrogate endpoint. After originally being granted accelerated approval, Depocyt and Doxil were converted from regular approval in 2007 and 2008, respectively145, upon meeting due diligence requirements, which came in the form of confirmatory RCTs. Marqibo has not yet met its postmarketing requirements for conversion to regular approval, but proposed a confirmatory trialδ in a 2012 FDA submission172; the trial has not yet reported results.

In order to be granted marketing approval by the FDA or EMA, each of the nine cancer nanomedicines investigated here demonstrated some effect on clinical benefit, as parameterized by anticancer efficacy, HRQOL, and safety. Five of nine drugs demonstrated a positive comparative anticancer efficacy effect (using OS, DFS, and RR

† Abraxane demonstrated substantial improvements in target lesion RR vs. solvent-based paclitaxel. Myocet in combination with cyclophosphamide (CPA) demonstrated substantial improvements in cardiac safety versus traditionally formulated doxorubicin with CPA, but achieved similar efficacy in terms of RR.

δ “A Phase 3, Multicenter, Randomized Study to Evaluate the Substitution of Marqibo (Vincristine Sulfate Liposomes Injection, VSLI) Standard Vincristine Sulfate Injection (VSI) in the Induction, Intensification, and Maintenance Phases of Combination Chemotherapy in the Treatment of Subjects > 60 Years Old with Newly Diagnosed Acute Lymphoblastic Leukemia (ALL)”.

endpoints) and two drugs demonstrated positive efficacy effects in the absence of a comparator (both accelerated approvals; RR and TTP endpoints). Two drugs, Daunoxome and Myocet, were evaluated against comparators on the basis of anticancer efficacy but failed to demonstrate statistically significant differences with respect to RR and TTP for the former drug, and RR for the latter. Both of these drugs, however, did demonstrate a positive effect on safety versus their comparators, which seems to have been heavily weighted in judging the outcome of these drug applications. In just three of nine drug applications was HRQOL evaluated using a validated HRQOL instrument and none of these evaluations rendered statistically significant differences against its comparator in the global HRQOL effect of the drug. One drug, Depocyt, was allocated a positive HRQOL effect classification as part of this investigation on account of its more convenient treatment schedule, which was frequently referred to by FDA reviewers as a substantial factor affecting HRQOL. For the six drugs making up the balance of approved cancer nanomedicines, HRQOL was either not specifically assessed or not referred to in documents made available to the public by the approving regulatory agencies.

3.2 HTA of nanomedicines

Insight on regional opinions on the clinical value of approved cancer nanomedicines was gleaned by accessing HTAs from five national and regional jurisdictions: Canada (CADTH), England (NICE), France (HAS), Australia (PBAC), and the European Union (EPAR). Each of these jurisdictions has granted marketing approval to cancer nanomedicines, but their numbers vary widely, from Australia with two marketed drugs to England, France, and the US with seven each. Abraxane and Doxil/Caelyx are the only two cancer nanomedicines that are approved in all five jurisdictions, while Marqibo and Vyxeos—two of the three most recently approved drugs—are only approved in the US at present, and Mepact is the only agent not approved in North America (see Table 2).

Table 2: Nanomedicine Approvals By Region and Health Technology Assessment Coverage By Agency Regional Approvals Health Technology Assessment Coverage Drug US Canada England France Australia Europe CADTH NICE HAS PBAC EPAR

Abraxane Pancreatic Pancreatic Breast NSCLC Breast

Doxil/Caelyx Ovarian KS Myeloma KS

Daunoxome § KS

Depocyt LM LM

Myocet Breast Breast

Mepact Osteosarcoma Osteosarcoma Osteosarcoma

Marqibo

Onivyde Pancreatic Pancreatic Pancreatic Pancreatic

† Vyxeos

Acronyms: Canadian Association for Drugs and Technology in Health, CADTH; National Institute for Health and Clinical Excellence, NICE; Haute Authorité de Santé, HAS; Pharmaceutical Benefits Advisory Committee, PBAC; European Public Assessment Report, EPAR; non-small cell lung cancer, NSCLC; Kaposi’s sarcoma, KS; lymphomatous meningitis, LM; acute myeloid leukaemia, AML.

Notes:

• Black cells indicate that the given nanomedicine has not received marketing approval in the given region or has no HTA available from a given agency.

• Unfilled cells indicate that the nanomedicine has received marketing approval in the given region or has an HTA available from the given agency, but not addressing the drug’s original approval.

• Red cells indicate that the nanomedicine has been approved in the given region or has an HTA available from the given agency, but not addressing the drug’s original approval.

§Daunoxome approval information from the EMA’s website could not be located, but the drug’s HAS HTA indicates that it is reimbursed by national health systems across Europe, indicating that this drug likely received EMA approval at some point in the past. † NICE indicates that an HTA covering the treatment of AML with Vyxeos is in progress. No data had been published as of November 15, 2017.

Among the HTA agencies consulted, less than half generated assessments of the nine nanomedicines of concern in this investigation: 21 reports of a possible 45 (47%). Fewer reports were found that assess the drugs’ original approval indication: 16 reports of 45 (36%), covering seven of nine nanomedicines. If EMA EPARs were not consulted, 10 reports on seven drugs would have provided the entire basis of data used in this analysis.

A changing combination of the five agencies generated HTAs for all approved cancer nanomedicines except Marqibo and Vyxeos, for which no HTAs had been generated at the time of writing*. All HTAs collated information on the drugs’ efficacy, in terms of anticancer activity or life prolongation, as well as their effects on patient safety. Often, HTAs referred to evidence of drugs’ effects on patients’ QOL, which came in the form of PRO data yielded from validated HRQOL measurement instruments like the EORTC QLQ-C30136, opinion from medical experts yielded from their experience treating patients with the drug of focus, or summaries of patient experiences collected by patient advocacy groups.

* Marqibo is approved for marketing only in the US, which is a jurisdiction covered by no HTA agency consulted for this investigation. Vyxeos—also approved for marketing only in the US—was granted approval in August of 2017: two months prior to the writing of this report. A void of HTAs covering Vyxeos is therefore not unusual. A Marketing Authorization Application (MAA) for Vyxeos was submitted to the EMA on November 3, 2017 and NICE awarded it ‘Promising Innovative Medicine’ (PIM) designation, an early indication of the UK’s intention to grant eligible leukaemia patients early access to the drug275. NICE also indicated that a HTA of Vyxeos was in progress at the time of this writing276.

In some cases, data were presented with little commentary, leaving readers to interpret trial outcomes, while in others the HTA committee synthesized efficacy, safety, and HRQOL dimensions into a cohesive statement on a drug’s holistic clinical benefit, often referring to the agent’s ‘benefit/risk’ balance, as below from the EMA’s EPAR for Myocet173: Overall it has been demonstrated that Myocet lowers the risk of cardiotoxicity compared with conventional Dox in dosages clinically equipotent with respect to antitumour activity. The absolute benefit from this, however, appears modest in patients with MBC. With respect to other aspects of toxicity, the safety profiles of Myocet and Dox are clinically similar.

Based on the [committee’s] review of data on quality∗, safety and efficacy, the

[committee] considered by majority decision that the benefit/risk profile of Myocet, in combination with cyclophosphamide, in the first line treatment of metastatic breast cancer in women was favourable.

A summary of all HTAs generated for FDA- and EMA- approved cancer nanomedicines—covering only originally approved therapeutic indications—can be found in Table 3. The table includes the date range over which the drug was appraised by different agencies, the number of HTAs available per drug, the therapies used to benchmark the performance of nanomedicines, the HTA agencies’ findings on the clinical benefit of each nanomedicine in terms of improved OS, improved HRQOL, and improved safety. This clinical information, analyzed in concert with economic considerations, was used by each HTA agency to formulate a conclusion about whether the drug should be reimbursed for patients as part of that jurisdiction’s universal healthcare system, summarized in the ‘Recommendation’ column of Table 3.

∗ ‘Quality’ refers here to the quality of data and statistical analyses presented by the sponsor, not HRQOL. No statistically significant differences in HRQOL domains were observed in comparative studies of Myocet. It is possible that committee’s perspective on Myocet’s impact on patient HRQOL was incorporated into their benefit/risk statement.

Table 3: Therapeutic Profile of FDA- or EMA-Approved Cancer Nanomedicines According to Health Technology Assessment Agencies

OS Effect Recomm- No. Nanomedicine Indication Appraisal Dates Comparator(s) HRQOL Effect Safety Effect (months) endation HTAs < 3 None Abraxane Metastatic breast cancer Oct 07 – Jan 10 Paclitaxel Reduction Positive 2 (2.3) established AIDS-related Kaposi’s None Doxil/Caelyx Nov 04 – May 16 Paclitaxel; ABV Improvement Improvement Positive 2 sarcoma established§ AIDS-related Kaposi’s None None Daunoxome Jul 14 ABV Improvement Positive 1 sarcoma established established None None Depocyt Lymphomatous meningitis Jun 04 – Jan 05 Cytarabine Improvement Positive 2 established§ established Doxorubicin + None None Myocet Metastatic breast cancer Sep 01 – Jan 05 Improvement Positive 2 CPA established established Doxorubicin + Exact cisplatin + Mepact Osteosarcoma (paediatric) Dec 08 – Oct 11 magnitude Improvement Reduction Positive 3 methotrexate + uncertain ifosfamide Acute lymphoblastic Marqibo NA NA NA NA NA NA 0 leukaemia Metastatic pancreatic < 3 Onivyde Jul 16 – Nov 17 5-FU/LV Improvement Reduction Mixed 4 cancer (1.9) Vyxeos Acute myeloid leukaemia In progress (NICE) NA NA NA NA NA 0 Source: Author’s analysis of data from sources defined in Methods. Appendix B includes unmerged data from all HTAs available for the drug in question.

Acronyms: Overall survival, OS; Quality of life, HRQOL; Health technology assessment, HTA; acquired immunodeficiency syndrome, AIDS; adriamycin, bleomycin, and vincristine combination chemotherapy, ABV; cyclophosphamide, CPA; fluorouracil/leucovorin combination chemotherapy, 5-FU/LV. Notes: ‘NA’ indicates that no appraisal was available through November 2017 ‘None established’ indicates that no HTA agency concluded that a validated change occurred on account of the study drug versus the comparator drug for the domain in question. • Validated change in OS: OS is required to have been appointed as an a priori endpoint in a comparative clinical trial that found a statistically significant difference between study drug and comparator drug. • Validated change in HRQOL: requires results from a validated HRQOL measurement instrument that indicate a statistically significant change in individual HRQOL domains or global HRQOL status. If a validated HRQOL instrument was used in studies and a direct and conclusive statement on HRQOL is given as part of the HTA, this constitutes a validated change. • Validated change in safety: requires a direct and conclusive statement as part of the HTA that indicates the overall effect on safety from drug treatment. Usually, these statements were drawn from HTA summary conclusions on: incidence of adverse events, adverse drug reactions, treatment discontinuations, or dose reductions due to adverse events. ‘Exact magnitude unknown’ indicates the occurrence of a validated OS change in favour of the study drug, but its magnitude cannot be expressed in units of time, usually on account of very long survival times and study subjects surviving beyond the conclusion of the trial. § Response rate used as primary evidence of treatment efficacy and a statistically significant difference in favour of the study drug (nanomedicine) was shown.

3.2.1 Overall survival

Statistically significant increases in OS were demonstrated in patients treated with Abraxane (+2.3 months), Onivyde (+1.9 months), and Mepact (exact magnitude uncertain*). In the remaining four of seven assessed cancer nanomedicines, no difference in OS could be established between the study drug and its comparators. In the cases of Doxil/Caelyx and Depocyt, OS data was either not included as part of the HTA or was not a primary endpoint in the studies considered by the HTA agencies. Instead, HTAs for these drugs included RR data as primary anticancer efficacy endpoints, which each demonstrated statistically significant improvements against their comparators. In the cases of Daunoxome and Myocet, OS was evaluated and was found to be equivalent to their respective comparator drugs.

3.2.2 HRQOL

Among 16 total HTAs of approved cancer nanomedicines, 15 offer information on how treatment affected patients’ HRQOL, but only eight (50%) report HRQOL information yielded from validated HRQOL measurement instruments. Five of the seven cancer nanomedicines covered by HTA agencies have HRQOL information included in their assessment that was gleaned from a named and validated HRQOL instrument, while HTAs of two drugs (Daunoxome and Mepact) included no reference to a specific instrument for evaluating HRQOL.

3.2.2.1 HRQOL improvement established

Improvements in HRQOL were recorded in the HTAs of four of seven approved cancer nanomedicines based on statistically significant differences found in global HRQOL or HRQOL subdomains of validated HRQOL measurement instruments, or based on overall judgments made by HTA committees. Among these four drugs, several different approaches to measuring HRQOL were used. For Doxil/Caelyx, the main HRQOL instrument used was the Functional

* DFS and predictive models of OS were used as measures of Mepact’s anticancer efficacy on account of long survival times observed in paediatric osteosarcoma, as outlined in Section 3.1.

Life Assessment of HIV Quality of Life (FAHI QOL), which was developed specifically for patients with AIDS-related Kaposi’s sarcoma (KS). According to EMA EPAR documents, Doxil/Caelyx demonstrated significant improvements on “five of nine general HRQOL domains—general health, pain, social functioning, energy level, and health distress”—and “four of nine Kaposi’s sarcoma-specific domains—pulmonary dysfunction or pain, restricted head or limb movement, exercise limitation, and sleep disturbance”—within the FAHI QOL questionnaire62.

For Depocyt, though no significant differences were found in Karnofsky Performance Status (a clinician-evaluated score of functional impairment; KPS), validated HRQOL instrument score (Functional Assessment of Cancer Treatment with Central Nervous System module; FACT- CNS), or in psychological health status (Mini Mental State), HTA committees made plain statements indicating that this drug engenders HRQOL benefits over current treatments owing to the fewer intrathecal injections it requires. The clinical context and route of administration are clearly important factors in making a holistic determination of HRQOL.

For Mepact, HRQOL was sparsely reported and no specific HRQOL instruments were named, but the HTA from NICE reported greater QALY amounts in all Mepact-including trial arms. Calculation of QALY infers that HRQOL and safety evaluations were performed, but neither was outlined specifically in the English agency’s assessment.

For Onivyde, HTAs cited a study comparing Onivyde + 5-FU/LV with 5-FU/LV alone as candidates for second-line therapy, which employed the EORTC QLQ-C30 instrument and revealed no significant differences among the treatment groups in terms of global health status, functional scales, and symptom scales. Neither drug regimen was found to reduce patient HRQOL according to the instrument, but the study suffered from large amounts of missing data and no statistically rigorous conclusions could be made. This investigation reports Onivyde’s HRQOL effect as an overall ‘Improvement’ on account of a rich collection of statements given by Onivyde-treated pancreatic cancer patients via patient advocacy groups as part of the CADTH

HTA. Several of the passages indicated patients’ favourable perspectives on the tolerability of Onivyde-incorporating treatment, especially among those who had previously undergone treatment with intensive drug regimens like FOLFIRINOX (combination fluorouracil[5-FU] + leucovorin[LV] + irinotecan, + oxaliplatin) or combination gemcitabine + Abraxane, which are common first-line therapies for pancreatic cancer. According to one patient whose disease had relapsed after gemcitabine + Abraxane therapy (excerpt from CADTH Clinical Guidance document174):

“I couldn’t stop the pain. And with the pain, I had no appetite, no more hope.” In her words, after the second treatment with [Onivyde], she stated: “the pain was gone; I had hope again. There are some side effects (lacerations in mouth, nausea, diarrhea, and swollen ankles) but I can cope with them and they have gotten less over time.”

Another patient reported being well enough to attend a family reunion on account of treatment:

Without Onivyde, I would not have had the energy or the presence of mind to enjoy the time together.

The main clinical trial referenced by HTA agencies found that patients in the Onivyde arm demonstrated no differences from comparator in terms of HRQOL effect but experienced increased incidence of AEs. Perspectives offered by CADTH-consulted patients mainly leveraged their experiences of previous treatment—first-line treatment—to benchmark their experiences of Onivyde with respect to tolerability and overall HRQOL. Though these remarks do not reflect a direct comparison of Onivyde and the comparator regimen, they do offer information on the contrasts that are important to these pancreatic cancer patients. Also, the perspectives indicate domains of HRQOL that were important to these patients and that were benefitted by Onivyde treatment relative to first-line treatment, which include but are not limited to physical (symptom-related), functional, and social domains.

3.2.2.2 No HRQOL improvement established

Three of seven HTAs of cancer nanomedicines reported no improvement in HRQOL with respect to comparator drugs. Abraxane was evaluated using the EORTC QLQ-C30 instrument and was found to demonstrate no statistically significant differences between treatment groups on the basis of global health status or individual HRQOL dimensions.

Information from HTA agencies covering Daunoxome across all domains of patient benefit was limited. The HTA does indicate that weight change, KPS, and an unspecified HRQOL measure were assessed during Daunoxome’s original trials, but none of these data were available for analysis. That no significant differences in HRQOL were found was the sole insight yielded here.

Myocet was evaluated using the EORTC QLQ-C30 questionnaire with breast cancer module (QLQ-BR23). The HRQOL profiles of the Myocet and trial comparator arms were similar among most HRQOL parameters.

In no study of approved cancer nanomedicines was patient HRQOL found to deteriorate versus its comparator drug.

3.2.3 Safety

Evaluations of safety were performed in all 16 HTAs of cancer nanomedicines collected as part of this investigation. Fourteen of 16 HTAs reported comparative data from key clinical trials rather than general safety profiles of given drugs; the latter can be found on marketed drug labels. Of the seven evaluated cancer nanomedicines, three (43%) demonstrated an improved safety profile relative to comparators, one (14%) did not elicit a positive safety effect, and three (43%) demonstrated a reduction in patient safety relative to comparators.

3.2.3.1 Safety improvement established

Reduced incidence of treatment related AEs of varying grades of severity and improved patient retention in trials were central factors in determining improved safety profiles of cancer nanomedicines. Compared to paclitaxel in patients with AIDS-related KS, Doxil/Caelyx was found to significantly reduce severe to life-threatening AEs (grades 3 to 4) like neutropenia and leukopenia, as well as mild to moderate AEs (grades 1 to 2) like alopecia and peripheral neuropathy. When Doxil/Caelyx was compared with ABV therapy, significantly more patients were retained through the course of treatment (68% versus 34%, respectively) as a result of improved drug tolerability. Daunoxome and Myocet demonstrated improved safety profiles relative to comparator drugs on the basis of similar evidence (Appendix B).

Importantly, Doxil/Caelyx, Daunoxome, and Myocet are all NDDSs of anthracycline drugs, which share the major dose-limiting side effect of cardiotoxicity111. HTAs for each of these cancer nanomedicines emphasized that the drugs were associated with lesser risks of cardiotoxicity—with changes in left ventricular ejection fraction (LVEF) as an indicator— compared to similar doses of conventional doxorubicin or daunorubicin.

3.2.3.2 No safety improvement established

Depocyt, a cytarabine NDDS, was the only nanomedicine wherein no changes in safety profile were observed against its comparator: conventional cytarabine. AEs typically associated with intrathecal injection*, like meningeal irritation, were common in both treatment groups. Arachnoiditis was the most frequent adverse event that occurred with Depocyt, but was considered mild, did not result in any treatment discontinuations, and its rate of occurrence was not significantly different from conventional cytarabine.

* Depocyt is indicated for lymphomatous meningitis: a blood-borne cancer of immune cells that infiltrates the central nervous system (the meninges, specifically). A key strategy for chemotherapeutic treatment of this disease is to inject drugs directly into the spinal cord such that they reach the cerebrospinal fluid. This way, chemotherapeutic drugs can bypass the blood-brain barrier: a major challenge in systemic drug delivery277,278.

3.2.3.3 Safety reduction established

Reductions in drug safety profiles were observed with Abraxane, Mepact, and Onivyde. Treatment of metastatic breast cancer with Abraxane, a paclitaxel NDDS, resulted in higher rates of treatment discontinuation and sensory neuropathy compared with solvent-based paclitaxel. Treatment of paediatric osteosarcoma with a Mepact-including multi-agent chemotherapy regimen was associated with similar rates of AEs and treatment withdrawals compared to multi- agent chemotherapy alone, but in one pivotal trial significantly greater rates of hearing loss were observed in the Mepact arm. A clinical HTA committee member with NICE posited that cisplatin, which was administered in all trial arms, is likely responsible for the hearing loss observed rather than Mepact, but no other HTA agency offered opinions directly supporting this notion. Treatment of metastatic pancreatic cancer with Onivyde-including combination chemotherapy was found—unanimously among four HTA agencies—to increase the burden of AEs patients experienced compared to combination chemotherapy alone. The PBAC HTA committee reported, however, that the benefit-risk balance of Onivyde, given the poor prognosis of the indicated treatment group, is favourable.

3.2.4 Recommendations for reimbursement

HTA agencies recommended the reimbursement of evaluated cancer nanomedicines within socialized healthcare systems in the case of every drug except one: Onivyde. This drug was given a negative recommendation by both English (NICE) and Australian (PBAC) HTA agencies. Positively, Onivyde was found to elicit significant improvements in the OS of metastatic pancreatic cancer patients versus comparator drug regimens and was found to improve or, at least, not negatively impact HRQOL according to measures of global HRQOL and direct patient statements. Negatively, Onivyde was associated with greater rates of treatment associated AEs compared to treatment with 5-FU/LV alone. What appeared to inspire negative

recommendations for reimbursement, though, was the drug’s price. According to CADTH*, Onivyde costs 1,000 CAD per 43mg/10 mL vial and nearly 7,000 CAD per 28-day course. NICE and PBAC each determined, by way of pharmacoeconomic determinations of ICER, that Onivyde was not sufficiently cost effective to justify recommendation for reimbursement by the National Health Service (NHS) and the Pharmaceutical Benefit Scheme (PBS), respectively. The PBAC, for example, determined an ICER of 100,000 AUD per QALY gained compared to 5- FU/LV treatment; the PBAC recommends an ICER not in excess of 50,000 AUD per QALY gained in the case of resubmission.

* CADTH maintained its positive recommendation of Onivyde conditional on “the cost effectiveness being improved to an acceptable level.”

Chapter 3 Discussion 1 Basis for regulatory approval of nanomedicines

Nine cancer nanomedicines had NDAs granted accelerated or regular approval by American or European regulators between 1995 and 2017, with two of three accelerated approvals converted to regular approval in the same timeframe (Error! Reference source not found.). At the time of original approval, all (100%) eligible cancer nanomedicines indicated for the treatment of cancer demonstrated some positive clinical effect in terms of anticancer efficacy, HRQOL, or safety.

At the time of registration, all nine cancer nanomedicines demonstrated some positive general effect on anticancer efficacy: most (55%) demonstrated this effect by showing advantage over a comparator drug and, from that group, most (60%) demonstrated a positive comparative effect on OS. In trials where OS time was measured as a primary endpoint, cancer nanomedicines extended OS by a mean (SE) of 2.9 (0.8) months (0.24 [0.07] years) over comparator treatments, which were often the standard of care for the given disease. Though these changes in OS fall on the lower bound of what some regulators consider clinically meaningful (≥3 months)175,176, the OS improvements engendered by these cancer nanomedicines (Onivyde and Vyxeos) represent 51% and 63% OS improvements in metastatic pancreatic cancer and t-AML/AML-MRC patients, respectively.

Figure 8 | Timeline of cancer nanomedicine approvals, accelerated approvals, and approval conversions granted by the FDA and EMA.

Of nanomedicines that demonstrated comparative benefit in anticancer efficacy at the time of drug registration, 60% did so at the expense of patient safety. Conversely, of the drugs that demonstrated no comparative benefit in anticancer efficacy, 100% demonstrated a comparative improvement in patient safety. These findings can serve as evidence that regulators take into consideration all factors that comprise the definition of ‘clinical benefit’ while engaged in marketing approval decisions. Interestingly, Depocyt, a drug that demonstrated superior efficacy and inferior safety relative to its comparator, was reported to elicit a positive effect on patient HRQOL, emphasizing that safety and HRQOL must be considered separate clinical concepts even though they are often challenging to resolve.

Comments on any sort of HRQOL assessment were reported in the approval documents of just 33% of (three of nine) cancer nanomedicines. These documents all indicated the use of a HRQOL instrument that demonstrated no statistically significant differences in HRQOL, but each report suffered from a deficiency in data or reporting quality. In one case the instrument was not specifically named, in another the entirety of data yielded from a validated HRQOL instrument assessment were described in a single sentence, and in another the assessment contained too much missing data to make a compelling claim of significance*. These findings make clear the dearth of HRQOL data reported by sponsors of cancer nanomedicines at the time of marketing approval, and even when HRQOL data was addressed in application documents, the collection and reporting of this data consistently lacked rigour177. Understanding that regulators seek any valid evidence of cancer medicines providing a longer or better life for patients, it is surprising that makers of cancer nanomedicines have generally neglected to include high quality patient-reported HRQOL evidence in their marketing applications. There is much opportunity for improvement in the collection, assessment, and communication of HRQOL data among cancer medicine clinical trials in general178, but among cancer nanomedicines, a drug class that regularly claims improved patient tolerability and HRQOL, avoiding HRQOL assessment seems to represent an opportunity missed.

* Data from Daunoxome, Abraxane, and Depocyt approval documents, respectively.

It is notable that liposome-based cancer nanomedicines account for eight of the nine total nanomedicines approved for the treatment of cancer, given that several more nanomedicine technologies exist, e.g. drug-carrying polymer micelles. This could be on account of liposomes’ near 60-year history of development, during which key formulation optimizations were made and significant expertise was grown, eventually leading to the approval of nanomedicine’s first marketed drug: pegylated liposomal doxorubicin (Doxil/Caelyx). By providing protection from cardiotoxicity and improved cancer-killing efficacy versus the conventional formulation of doxorubicin in clinical trials179,180, this liposome technology—made up of materials similar to those found in the human body and known to be biocompatible—enjoyed a relatively straightforward path to market, gaining FDA approval a short five years after its development was reported59. This 1995 approval may have provided liposome drugs with market-bound momentum by instilling a positive outlook on the technology among regulators, with the approvals of other liposome-based medicines such as Daunoxome (FDA 1996), Abelcet (FDA 1997)—liposomal amphotericin B for the treatment of infectious diseases—Depocyt (FDA 1999), and Myocet (EMA 2000) following shortly thereafter. Abraxane, made up of albumin- bound paclitaxel, represents the only non-liposomal cancer nanomedicine approved in the U.S. or Europe (FDA 2005), likely owing to the technology leveraging the inherent safety and biocompatibility of an endogenous protein and improving patient tolerability by avoiding the need for excipients like Cremophor EL. Though outside the scope of this work, it would be interesting to investigate whether nanomedicine technologies that leverage components that are completely exogenous—e.g. polymers, metals—face greater resistance from regulators as they approach the clinic.

It is also notable that many approved liposomal cancer nanomedicines were developed in close geographic proximity, with an epicenter in western Canada. Myocet, Abelcet, Visudyne—a liposomal verteporphin to address wet macular degeneration—Marqibo, and Vyxeos were all developed by groups in British Columbia or Alberta. By 2012, Dr. Pieter Cullis’ NanoMedicines Research Group at the University of British Columbia (UBC)181 had translated three lab-borne technologies to the clinic through sponsor organizations: Abelcet through Enzon Pharmaceuticals, Myocet through Cephalon Inc.182, and Marqibo through Inex Pharmaceuticals183. Dr. Marcel Bally, a former PhD student in Cullis’ UBC laboratory, is

another key player in the commercialization of Canadian liposomes. Bally was intimately involved in the development of Myocet, Marqibo, and Vyxeos, and played co-founding roles in companies including Lipex Biomembranes Inc. (with Cullis), Inex Pharmaceuticals (with Cullis; now Arbutus), Northern Lipids Inc. (with Cullis; now Transferra), Celator Pharmaceuticals, and Cuprous Pharmaceuticals184. Celator Pharmaceuticals’ other co-founder was Dr. Lawrence Mayer, another important former member of Cullis’ research group185 who has played lead roles in companies like QLT Inc.186, the Vancouver-based company spun out of UBC that was responsible for the development and commercialization of Visudyne187. Dr. Theresa Allen of the University of Alberta contributed to fundamental research behind long-circulating liposomes58, which led to the development and clinical success of pegylated liposomal doxorubicin in the form of Doxil/Caelyx, the first approved cancer nanomedicine. This region being so rich in clinical innovation and commercial success speaks to the value of long-standing embedded expertise and strong academy-industry collaboration.

2 HTA of nanomedicines

HTAs were consulted in order to investigate approved cancer nanomedicines with added information in the form of regional assessment committee opinions and more robust clinical data afforded by the passage of time between drug approval and HTA generation. All cancer nanomedicines (100%) examined by HTA agencies were evaluated against a comparator drug, which was typically the standard of care treatment. This represents a 22% improvement from data available at the time of marketing approval. OS, or a close approximation of it (as with DFS with Mepact), was evaluated during the original FDA or EMA approval of 33% of drugs. At the time of HTA generation, OS was evaluated in 71% of the drugs investigated here, demonstrating that HTA recommendations are, indeed, developed with the benefit of more available data than regulatory approval decisions.

Combining results from regulatory approval data, a total of four cancer nanomedicines reported significant extensions in OS and three reported this in terms of comparative improvement in OS

time. These three cancer nanomedicines extended OS by a mean (SE) of 2.7 (0.5) months (0.23 [0.04] years) over comparator treatments.

Findings yielded from consulting regional HTAs indicate that 100% of approved cancer nanomedicines increased OS by some known or unknown magnitude, or demonstrated some form of evidence of improved HRQOL or safety over alternative treatments. In general, it seems that approved cancer nanomedicines are delivering clinical value to patients and their families.

Of HTA agency-evaluated cancer nanomedicines, 100% of those that demonstrated a statistically significant improvement in OS did so at the expense of patient safety. If considering all endpoints that infer improvements in anticancer efficacy (e.g. RR), drops to 60%, mirroring findings from FDA and EMA approval data. Also mirroring data available at the time of approval, 100% of cancer nanomedicines that demonstrated no extension in OS demonstrated improvements in HRQOL or safety.

Information referring to the drugs’ effect on HRQOL was included in 94% of HTA documents, but only 50% used validated HRQOL measurement instruments to support their claims. Overall, 57% of cancer nanomedicines were determined to improve HRQOL compared to its comparator, but, if using evidence only from validated HRQOL instruments, just 14% of drugs signaled statistically significant improvements.

In no cancer nanomedicine evaluated by HTA agencies was HRQOL found to engender reductions in global HRQOL or HRQOL subdomains with respect to a comparator. Taken together, these findings indicate that cancer nanomedicines work to conserve patients’ HRQOL during cancer treatment as well or better than comparative therapies, as measured by a validated HRQOL instrument or not.

The median year of assessment for HTAs that reported validated HRQOL instruments was not significantly different from those that did not (2012 ± 6 and 2010 ± 5, respectively). From this, it appears that the gulf of validated HRQOL data is not influenced by any lack of availability in HRQOL assessment technologies or strong precedent for reporting HRQOL outcomes, but instead is governed by inconsistent reporting practices.

Direct patient perspectives on their experiences with treatment, like those included as part of CADTH’s HTA for Onivyde, shed light on important contextual details that might otherwise be overlooked when reviewing the HRQOL- and safety-related effects of a drug. The contrasts between Onivyde + 5-FU/LV and 5-FU/LV according to the HRQOL instrument EORTC QLQ- C30, were not so great as to be significant even in the presence of significant increases in treatment-emergent AEs attributed to the Onivyde arm*. This finding, when considered in concert with direct patient perspectives, reveals key contextual information about what this particular patient group might be willing to tolerate during treatment to achieve gains in OS. Two months of OS benefit relative to 5-FU/LV could be extremely meaningful to patients whose prognoses would otherwise have dictated a four-month life expectancy, especially when that treatment has the capacity to palliate symptoms of disease and has a much-favoured toxicity profile compared to these patients’ first-line treatment.

CADTH’s direct reports of patient perspectives also remind the reader that critical nuances of human experiences with illness and treatment are liable to be confounded when fed into the indifferent mechanisms of a standardized HRQOL instrument. Understanding the context of a patient’s disease and previous treatment experience, along with their goals and outlook, are critical accompaniments to aggregated OS, HRQOL, and safety data when assessing the clinical benefit of a cancer medicine.

* The Onivyde + 5-FU/LV versus 5-FU/LV study suffered from a high early attrition rate on account of pancreatic cancer’s poor prognosis and recruited patients’ advanced disease, which led to high levels of missing HRQOL data.

3 Emphasizing the intentional collection, analysis, and communication of HRQOL data in cancer nanomedicine

Although many approved cancer nanomedicines have demonstrated substantial anticancer efficacy in the clinic—Vyxeos (+3.5 mo. OS [AML]), Abraxane (+2.3 mo. OS [metastatic breast cancer]), Onivyde (+1.9 mo. OS [metastatic pancreatic cancer]), Mepact (+ OS effect, magnitude undetermined [osteosarcoma])—clinical trials of these treatments must also be designed to determine whether these technologies meaningfully reduce deleterious effects on HRQOL associated with other systemic treatments*. This evidence would be borne from trials185 wherein PROs, like HRQOL, are established as co-primary or secondary endpoints186,187 and rationally selected HRQOL assessment instruments116,118,134,136,188 are deployed alongside typical efficacy evaluating schemes (see Future Work). Pursuing these measures would make clear a sponsoring organization’s commitment to the development of both efficacious and well-tolerated therapies, while bolstering corresponding claims of patient benefit if discovered. Future nanomedicines must be designed with the patient in mind, not just the tumour. This is the essence of patient- centred drug development146,189.

To patients and patient families who wish to be actively engaged in healthcare decision-making, clear messages from physicians about prognosis and goals of treatment are critical to achieve care that is concordant with their values and preferences130. When advising on the treatment options available for patients diagnosed with a cancer that nanomedicines are prescribed for— many of them incurable—it is important for physicians to be forthright about the reality of the disease and the likely effects of treatment to avoid inaccurate expectations of therapy190. Reports of patients’ experiences with specific chemotherapies are commonly anecdotal, poorly analyzed, sparsely reported, or made inaccessible by discipline-specific language148,149,177,191,192.

* This notion applies to clinical trials of all medicines, but especially those studying the application of toxic or side effect inducing drugs in patients with life-limiting conditions.

The director of the FDA’s Oncology Center of Excellence, Richard Pazdur, and colleagues indicated in a 2003 paper that HRQOL is a key endpoint in the approval of oncology drugs, but acknowledged that no approvals in the preceding 13 years had been based on instruments measuring HRQOL140. The paper attributes this to poor standards of practice being employed during the measurement of HRQOL*, which is frequently plagued by missing data and weakly defined plans for analysis. To improve credibility, Pazdur et al. call for instruments that are validated for the specific purpose of measuring HRQOL differences in RCTs of patients with a specific cancer type and to aim for duplication of results in trials using the same instrument140.

Adding to this conversation, the Consolidated Standards of Reporting Trials (CONSORT) Group asserted in 2011 that clinical trial reporting of patient-reported outcomes (PROs) should bear the following hallmarks in order to improve quality and transparency177,192,193: • PROs are identified as a primary or secondary outcome in the abstract; • A description of the hypothesis of the PROs and relevant domains are provided (i.e. if a multidimensional PRO instrument has been used); • Evidence of the PRO instrument’s validity and reliability is provided or cited; • Statistical approaches for dealing with missing data is explicitly stated; • PRO–specific limitations of study findings and generalizability of results to other populations and clinical practice are discussed.

The CONSORT PRO extension guidelines apply to all RCTs and are in no way specific to trials in cancer or of cancer nanomedicines. They are reported here to underscore the importance of high-quality reporting of patient experiences in developing medicines that deliver patient benefit. Owing to intentionally designed HRQOL-conserving characteristics, cancer nanomedicines stand to be key players in patient-centred oncology; placing a special emphasis on accessible, first-rate PRO reporting could help secure this position to the benefit of patients, researchers, and industry stakeholders alike. So, effort must be put forth on two fronts: building a base of rigorous

* “[T]his aspect of the clinical trials has generally not been well conducted.”140

evidence supporting the HRQOL impacts engendered by different cancer treatments, including nanomedicines; and developing ways of facilitating the simple and accurate communication of that evidence in the literature and to patients7,194–196.

In a recent trial, OS improvements in patients with metastatic solid tumours were associated with a very simple intervention: integrating a system for patient-reported symptom monitoring during routine cancer treatment197. Truly, no reasons remain for avoiding high-quality HRQOL assessment, especially for a field that stands to benefit so much from the evidence collected.

Configuring the scope of cancer nanomedicine design to look beyond technological sophistication and to have a keen eye for toxicity reduction and a view to holistic patient benefit will be key in ensuring the technology’s continued relevance in clinical practice. The incorporation of innovative agents and drug combinations in nanomedicines, along with recognizing synergies between nanomedicines and other powerful technologies in cancer medicine, like modern immunotherapy159,160,198–202, will also be critical in paving paths forward. Retooling nanomedicine clinical trials with companion diagnostics for patient stratification and the careful incorporation of PROMs of symptom prevalence and HRQOL outcomes will set a strong foundation from which nanomedicines can build evidence of their efficacy and their unique position as QOL conserving chemotherapies.

Chapter 4 Limitations, future work, and conclusions 1 Limitations

This investigation focused only on the eligible cancer nanomedicines’ indication of original regulatory approval, which limited the data available for analysis in terms of both regulatory approvals and HTAs, since many nanomedicines have an abundance of approvals for supplemental indications. Focusing on original indications for the oldest nanomedicines required the review of regulatory documents drafted in the mid-1990s, which were sometimes difficult to source (if they were available at all) and were frequently associated with inconsistencies in the clinical trial information reported and redacted text. HTAs for the original indications of older nanomedicines were also difficult to locate, since several newer documents had superseded the original. This frequently caused the original assessment to be buried within the newer documents related to different indications or comparisons against modern replacements, often with incomplete information around the rationale for the original judgements made.

This investigation assessed comparisons between approved cancer nanomedicines and standard of care treatments for their respective clinical indications. This data is useful from the perspective of universal healthcare administrators, as it sheds light on the relative clinical value of therapies available for specific stages of specific diseases, which helps inform reimbursement decisions. From the perspective of those looking to directly assess the clinical value of one drug delivery technology against another, though, this approach is not ideal. The La-Beck research group at Texas Tech University performed a meta-analysis of clinical studies comparing the anticancer efficacy of liposomal chemotherapies versus their conventional counterparts—14 clinical trials comprising 2589 patients—and found no differences in cancer-killing efficacy in terms of RR, OS, or PFS between the two technologies206. The analyses included in this thesis solely assessed nanomedicines’ clinical benefit in their indications of original approval, whereas the studies assessed by La-Beck et al. included clinical data collected in indications other than each nanomedicine’s indication of original approval (e.g. pegylated liposomal doxorubicin for soft tissue sarcoma) or they included data from nanomedicines that have not yet been approved for the treatment of cancer (e.g. liposomal cisplatin or liposomal paclitaxel). As a result, there

was no overlapping data between the studies assessed in the present work and those assessed by La-Beck et al. The present investigation yields useful insights on cancer nanomedicines’ holistic value in the clinical benefit versus standard of care treatments, but it can make no broad claims about the relative clinical benefit of conventional chemotherapies versus nanomedicine chemotherapies.

No US HTA agencies were consulted for this investigation, which further limited the approved cancer nanomedicine data available for analysis*. Though HTA systems that exist in the US appear less formalized than those operating in Europe, Canada, and Australia, they may offer high quality assessments of cancer nanomedicines. The value of consulting US HTA agencies is underscored in the context of cancer nanomedicines that are approved in that country and no place else (i.e. Onivyde and Vyxeos). Although the lack of a universal healthcare apparatus in the US complicates the aims of its HTA agencies, the absence of an American voice represents a significant limitation to the comprehensiveness of this study.

This research did not investigate the economic impact of cancer nanomedicines, but this played a critical role in decisions for reimbursement made by HTA agencies. Regional committees scrutinize the economic impact of introducing a new drug to a government-funded healthcare system by developing cost- and clinical benefit-incorporating models that allow comparison of new and standard-of-care medications. For example, calculating the number of additional quality-adjusted life years (QALYs) or quality-adjusted time without symptoms of disease and toxicity (Q-TWiST) in order to estimate an incremental cost effectiveness ratio (ICER)164,207. On the basis of pharmacoeconomic metrics like these, HTA agencies—notably, NICE, PBAC, and CADTH—formed conclusions on whether to recommend the nanomedicine in question for reimbursement under a national healthcare plan. The economic evaluation of Onivyde for the treatment of pancreatic cancer led to the drug’s negative recommendation for reimbursement in England and Australia, and its conditional recommendation in Canada. From the present sample

* Rationale for the exclusion of US HTA agencies was provided in the Methods section of Chapter 2.

of HTAs, those drafted during the past five to 10 years most frequently incorporated such economic analyses, perhaps reflecting mounting concerns over the cost of oncology drugs208,209.

The robustness of the current investigation certainly could have been improved by considering the impact of drug cost on the overall value delivered by cancer nanomedicines. This is especially true in the U.S. in light of the fact that one of nation’s few major national healthcare programs, Medicare, is required by law to reimburse all drugs approved by the FDA without option of price negotiation208, and is therefore prevented from acting on available HTA recommendations. England’s HTA agency, NICE, advises their National Health Service (NHS) on reimbursement decisions and may exclude drugs from coverage if they are found to elicit marginal or uncertain benefits, especially in the case of medications coming at high financial cost210,211.

This study was executed by a single reviewer of regulatory approval and HTA documents, with no second reviewer on hand to ensure consensus with and no medical expert on hand to verify the clinical minutiae of cancer treatments, as was done by Salas-Vega et al.164 and as is suggested for methodological rigour in narrative syntheses165,212. Also out of step with narrative synthesis methodology was this investigation’s lack of inter-rater reliability and agreement measures (e.g. the kappa statistic213 or Krippendorff’s alpha coefficient214) among HTA agencies, which can be attributed to insufficient availability of data.

2 Future work 2.1 Updated survey of cancer nanomedicine HRQOL effects

To shed light on the proportion of approved cancer nanomedicines that have been formally evaluated and documented to engender influence on patients’ HRQOL, this author proposes a systematic search of the literature following—but expanding upon—the method of Rupp and Zuckerman, 2017215. The authors developed a simple literature search protocol to locate peer-

reviewed summaries of the HRQOL benefits associated with cancer drugs that had been newly registered on the basis of surrogate endpoints144. The method uses PubMed MeSH terms to seek out comparative clinical trials of cancer drugs’ original approval indication wherein a validated HRQOL instrument was employed.

In order to update and broaden the cancer nanomedicine-related HRQOL information available through HTAs, the adaptation of Rupp and Zuckerman’s method for approved cancer nanomedicines is proposed. The adapted search protocol and preliminary results are included as Appendix C. The scope of eligible results returned by the original search protocol was quite limited—five of nine cancer nanomedicines returning no HRQOL data—so this author proposes widening the search scope to all approved indications and compiling results on a drug-by-drug, indication-by-indication basis. This search exercise will form an updated catalogue of the evidence available to substantiate cancer nanomedicines’ claims of reduced off-target toxicity and improved HRQOL.

2.2 Cancer nanomedicine-specific clinical trial design

Companion diagnostics for cancer nanomedicines are likely to be key to predicting clinical benefit, given heterogeneity in tumour microenvironment and the multiplicity of other factors governing nanomedicine delivery to tumours. So, the inclusion of companion diagnostics will be crucial for guiding patient selection in clinical trials.

This author proposes future work in the development of a cancer nanomedicine-tailored clinical trial, wherein drug-specific companion diagnostics are employed as a method of patient stratification and responder population enrichment, and anticancer efficacy endpoints (e.g. OS, RR, PFS) are deployed alongside PRO measures of HRQOL as primary study endpoints. Feedback on delivery efficiency and treatment response would be provided by the diagnostic agent-appropriate imaging modality (e.g. PET, CT, MR) and feedback on the treatment’s effect on patient HRQOL would be provided by regular assessment of treatment- or disease-specific

HRQOL measures. Progression of treatment would be informed by these modes of data, with physicians and nurses being attentive to changes in symptom reports and HRQOL scales (Figure 9). In this way, trial-enrolled patients stand the greatest chance of responding to treatment, receive the most proactive symptom-palliating care possible, and thus, are least likely to drop out of the study on account of persistent unaddressed treatment side-effects.

Figure 9 | Proposed patient-centred clinical trial for cancer nanomedicines. Patients stratified according to indicators of tumour deposition, tumour distribution, and drug release: companion diagnostics. Efficacy endpoints and patient-reported outcome endpoints are used in tandem to determine the success or failure of drug candidates. Dr. James Evans (Prof. Christine Allen Laboratory, Leslie Dan Faculty of Pharmacy, University of Toronto) made substantial contributions to the arrangement of this diagram. Images contained herein are reprinted with permission from Servier Medical Art, licensed under CC BY 3.0.

While developing valid diagnostic agents is nontrivial and executing diagnostic tests through clinical trials is logistically complex and expensive, they are essential. By avoiding these, sponsors are readying their drugs for failure in clinical trials, while patients who could benefit most from these treatments remain unidentified in study populations.

2.3 Study of patient experiences with cancer nanomedicines with view toward development of HRQOL assessment tool

To lay groundwork for the development of a clinically rigorous HRQOL assessment tool specific to clinical trials of cancer nanomedicines, this author proposes future work in the qualitative co- construction of patient experiences of treatment with these agents. Standardized HRQOL instruments are often useful only in the reporting of large effects in obvious treatment domains, but treatment- and disease-specific HRQOL instruments improve the likelihood that changes in nuanced treatment domains—that, perhaps, are peculiar to a treatment technology or a disease— can be resolved upon analysis. Qualitative research methods will be adopted here, as this arm of scientific research is particularly well suited to the complexity of society and human experience. Specifically, the initiation of research following the methodological traditions of interactional narrative analysis as described by Riessman216 is proposed. Working with patients to understand their narratives of treatment will form the basis of evidence used to define domains important to patients undergoing treatment with cancer nanomedicines, which are integral to the effect- resolving power of the result HRQOL instrument. This narrative analysis process—in-depth semi-structured interviews conducted over months—will also provide an important platform for patients to share their experiences with cancer therapy: an avenue for healing in itself217

This author, in collaboration with Professor Elise Paradis (Leslie Dan Faculty of Pharmacy, University of Toronto), have drafted a qualitative research proposal of this kind for a small study alongside women with advanced ovarian cancer receiving treatment with Doxil/Caelyx at the Princess Margaret Cancer Centre. This proposal may be adapted for narrative analysis research in different disease populations and for different cancer treatments. See Appendix D for complete proposal*.

* This research was proposed to clinical partners midway through this master’s work and was planned to yield the central, original data around which this thesis would be written. Effort expended by the author to develop this study, proposal, and the methodological grounding necessary to write it included engaging in one semester-long course on qualitative research methods (beyond master’s course requirements for the Department of Chemical Engineering and Applied Chemistry), several ethics trainings for studies including human subjects, consultation with the University Health Network’s Research Ethics Board, and five months of discussion and meetings with clinical partners. Ultimately, the proposal was denied and the research aborted.

3 Conclusions

Cancer nanomedicines represent an innovative mode for chemotherapeutic drug delivery with several examples of their capacity to engender clinical benefits, including reductions in off-target toxicity, capacity for fixed-ratio dual drug delivery, and improved drug delivery efficiency to tumour sites. As researchers understand more about the physiological milieu through which nanomedicines must transit to exert their targeted therapeutic effects, the rational design of cancer nanomedicines will only improve: movement toward a disease-driven, rather than formulation-driven, approach should accelerate this effort39. Advances in strategies to stratify clinical trial-enrolled patients according to their likelihood of benefitting from treatment with cancer nanomedicines—e.g. leveraging key biomarkers or deploying companion diagnostics and imaging protocols—will allow a fuller understanding of these drugs’ effects in optimal patient populations, perhaps informing more specific indications for which the drug is approved by regulators.

Reduction in treatment toxicity and improvements in HRQOL remain important aims in medicine, generally, and a key claim among cancer nanomedicines. According to HTAs— sources of mature, post-approval clinical data and judgments from regional health administrators on the value of new therapies—available for seven of the nine approved cancer nanomedicines considered in this work, all seven performed as well or better than their comparators with respect to HRQOL. These claims, though, were generally made on the basis of data that would be considered weak or unacceptable by authors of the CONSORT PRO extension, with only 50% of HTAs including HRQOL data yielded from a validated HRQOL instrument. A maximum of 14%

Failure of this research effort ultimately owed to the perceived risks of recruiting members of a vulnerable patient population, low confidence in the small size of the proposed subject cohort, and poor stakeholder buy-in for engaging in qualitative research of this kind. The latter aspect may reflect a broader ‘paradigmatic clash’282,283 between the heavily quantitative positivist or post-positivist research paradigms employed in medicine and the spectrum of alternate research paradigms employed in qualitative research, like the constructivist one proposed in Appendix D. Though there has been plenty of forward progress toward integrating quantitative and qualitative research in medicine—as evidenced by the important work of patient advocacy groups, HRQOL methodologists, and medical education researchers—it seems there is still much ground to be made.

of these approved cancer nanomedicines would be considered to engender an improvement in HRQOL against its comparator according to best practices, instead of the 57% reported by HTA agencies. Given the emphasis regulatory agencies place on patient-centred care in oncology, evidenced by the provision of guidances around the use of PROs to support drug applications, a gap in deploying and reporting PROs like HRQOL among cancer nanomedicines is clear. The intentional and structured collection, analysis, and reporting of PROs like HRQOL in clinical trials will help lay a foundation from which cancer nanomedicines can build evidence of their role in mitigating toxic effects of chemotherapy and conserving patients’ quality of living.

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Appendix A Quality of life measurement instrument specimens

Examples of quality of life measurement instruments developed by the European Organization for Research and Treatment of Cancer

(EORTC) are included in the present appendixφ. The general EORTC Quality of Life Questionnaire (QLQ) C30 acts as a basis for evaluations of quality of life in clinical trials across many cancer types. Disease-specific quality of life measurement modules, like the QLQ- BR23 for breast cancer, can be employed in cancer clinical trials where investigators aim to yield data about the effect of a treatment on patients’ quality of life that might be peculiar to that specific type of treatment or disease.

Specimens: I) EORTC QLQ-C30 Version 3.0 (General Questionnaire) II) EORTC QLQ-BR23 (Breast Cancer Module)

All specimens were retrieved from and reprinted with permission by the EORTC Quality of Life Department218, for academic use only. Scoring manuals for the included quality of life questionnaires are available from the EORTC* but cannot be reprinted here.

φ The EORTC QLQ-C30 and disease-specific modules are examples from just one system for evaluating quality of life. Another important example is the Functional Assessment of Cancer Therapy (FACT) questionnaire and its disease-specific modules, developed by David Cella and the FACIT group (http://www.facit.org/)122. * Full collection of EORTC quality of life questionnaires available at: http://groups.eortc.be/qol/eortc-qlq-c30

ENGLISH ENGLISH

During the past week: Not at A Quite Very EORTC QLQ-C30 (version 3) All Little a Bit Much

We are interested in some things about you and your health. Please answer all of the questions yourself by circling the 17. Have you had diarrhea? 1 2 3 4 number that best applies to you. There are no "right" or "wrong" answers. The information that you provide will remain strictly confidential. 18. Were you tired? 1 2 3 4

Please fill in your initials: 19. Did pain interfere with your daily activities? 1 2 3 4 Your birthdate (Day, Month, Year): 20. Have you had difficulty in concentrating on things, Today's date (Day, Month, Year): 31 like reading a newspaper or watching television? 1 2 3 4 ______

Not at A Quite Very 21. Did you feel tense? 1 2 3 4 All Little a Bit Much 1. Do you have any trouble doing strenuous activities, 22. Did you worry? 1 2 3 4 like carrying a heavy shopping bag or a suitcase? 1 2 3 4 23. Did you feel irritable? 1 2 3 4 2. Do you have any trouble taking a long walk? 1 2 3 4 24. Did you feel depressed? 1 2 3 4 3. Do you have any trouble taking a short walk outside of the house? 1 2 3 4 25. Have you had difficulty remembering things? 1 2 3 4 4. Do you need to stay in bed or a chair during the day? 1 2 3 4 26. Has your physical condition or medical treatment 5. Do you need help with eating, dressing, washing interfered with your family life? 1 2 3 4 yourself or using the toilet? 1 2 3 4 27. Has your physical condition or medical treatment interfered with your social activities? 1 2 3 4 During the past week: Not at A Quite Very All Little a Bit Much 28. Has your physical condition or medical treatment caused you financial difficulties? 1 2 3 4 6. Were you limited in doing either your work or other daily activities? 1 2 3 4

7. Were you limited in pursuing your hobbies or other For the following questions please circle the number between 1 and 7 that leisure time activities? 1 2 3 4 best applies to you

8. Were you short of breath? 1 2 3 4 29. How would you rate your overall health during the past week?

9. Have you had pain? 1 2 3 4 1 2 3 4 5 6 7

10. Did you need to rest? 1 2 3 4 Very poor Excellent

11. Have you had trouble sleeping? 1 2 3 4 30. How would you rate your overall quality of life during the past week? 12. Have you felt weak? 1 2 3 4 1 2 3 4 5 6 7 13. Have you lacked appetite? 1 2 3 4 Very poor Excellent 14. Have you felt nauseated? 1 2 3 4

15. Have you vomited? 1 2 3 4

16. Have you been constipated? 1 2 3 4

Please go on to the next page

ENGLISH ENGLISH

During the past week: Not at A Quite Very EORTC QLQ - BR23 All Little a Bit Much 47. Did you have any pain in your arm or shoulder? 1 2 3 4

Patients sometimes report that they have the following symptoms or problems. Please indicate the extent 48. Did you have a swollen arm or hand? 1 2 3 4 to which you have experienced these symptoms or problems during the past week. 49. Was it difficult to raise your arm or to move it sideways? 1 2 3 4 During the past week: Not at A Quite Very All Little a Bit Much 50. Have you had any pain in the area of your 31. Did you have a dry mouth? 1 2 3 4 affected breast? 1 2 3 4

32. Did food and drink taste different than usual? 1 2 3 4 51. Was the area of your affected breast swollen? 1 2 3 4

33. Were your eyes painful, irritated or watery? 1 2 3 4 52. Was the area of your affected breast oversensitive? 1 2 3 4

34. Have you lost any hair? 1 2 3 4 53. Have you had skin problems on or in the area of your affected breast (e.g., itchy, dry, flaky)? 1 2 3 4 35. Answer this question only if you had any hair loss: Were you upset by the loss of your hair? 1 2 3 4

36. Did you feel ill or unwell? 1 2 3 4

37. Did you have hot flushes? 1 2 3 4

38. Did you have headaches? 1 2 3 4

39. Have you felt physically less attractive as a result of your disease or treatment? 1 2 3 4

40. Have you been feeling less feminine as a result of your disease or treatment? 1 2 3 4

41. Did you find it difficult to look at yourself naked? 1 2 3 4

42. Have you been dissatisfied with your body? 1 2 3 4

43. Were you worried about your health in the future? 1 2 3 4

During the past four weeks: Not at A Quite Very All Little a Bit Much

44. To what extent were you interested in sex? 1 2 3 4 45. To what extent were you sexually active? (with or without intercourse) 1 2 3 4 46. Answer this question only if you have been sexually active: To what extent was sex enjoyable for you? 1 2 3 4

Please go on to the next page

Appendix B Health technology assessment of approved cancer nanomedicines

Table 4: Abraxane Health Technology Assessment Summary

Abraxane (nab-Paclitaxel; ABI007; nanoparticle albumin- FDA Primary Indication bound paclitaxel; protein-bound paclitaxel)

ATC Code: L01CD01 Abraxane contains nanoparticles of paclitaxel bound to human serum albumin. Albumin is known to mediate endothelial transcytosis of Orphan status: plasma constituents and in vitro studies have demonstrated that the presence of albumin enhances paclitaxel transport across endothelial Licensure: FDA (2005), EMA (2008) cells. Abraxane monotherapy is indicated for the treatment of metastatic breast cancer in patients who have failed first-line treatment for metastatic disease and for whom standard, anthracycline containing therapy is not indicated [Source: HAS HTA, 2010] Marketing status: Active, Prescription

Agency CADTH NICE HAS PBAC EPAR Appraisal date Jan, 2010 Oct, 2007 Comparator Taxol (paclitaxel) Taxol (paclitaxel) Modelled/indirect comparison No No OS: OS: OS: 2.3 month increase in median OS OS: OS: 2.3 month increase in median OS compared to Basis for classification compared to paclitaxel in second-line (or paclitaxel in second-line (or greater) treatment greater) treatment population. population.

HRQOL: HRQOL: HRQOL: "No improvement in quality of life HRQOL: HRQOL: "Global Health Status/QOL did not show was demonstrated in the pivotal study." notable trends or statistically significant differences between the treatment groups." Drawn from EORTC QLQ-C30 questionnaire, version 3.0.

Safety: Safety: Safety: Higher incidence of discontinuations of Safety: Safety: "The safety profile was similar between treatment in Abraxane group than paclitaxel ABI007 and solvent-based paclitaxel except for a group (7% vs. 4%), mainly on account of higher incidence of sensory neuropathy associated neurotoxicity. Sensory manifestations with ABI007." generally regress or disappear after a few months of treatment.

Effects Merged Data OS increase 2.3 months < 3 months < 3 months

HRQOL change No difference No difference No difference

Safety change - - -

Recommendation + + +

Notes Metastatic breast cancer has median survival time of ~2 years, so additional 2.3 months represents ~10% improvement.

Table 5: Doxil/Caelyx Health Technology Assessment Summary Doxil/Caelyx (pegylated liposomal doxorubicin; FDA Primary Indication PLD) ATC Code: L01DB01 Orphan status: Orphan Doxil (pegylated liposomal doxorubicin) is indicated for the treatment of AIDS-related Kaposi’s sarcoma in patients in combination with ARV therapy after failure of prior systemic chemotherapy or intolerance to such therapy (therapy comprising at least two of the following agents: a vinca alkaloid, Licensure: FDA (1995), EMA (1996) bleomycin and doxorubicin [or another anthracycline]). [Source: FDA Regular Approval Letter, 2008] Marketing status: Active, Prescription Agency CADTH NICE HAS PBAC EPAR Appraisal date May, 2016 Nov, 2004

Comparator Paclitaxel ABV (adriamycin, bleomycin, vincristine)

Modelled/indirect comparison No

OS: OS: OS: No OS discussed. PFS durations showed no OS: OS: OS was not a study endpoint, but median survival was statistically significant difference between Doxil and 160 days with Caelyx and 153 days with ABV (not statistically Basis for classification paclitaxel groups: 12.2 weeks vs. 17.5 weeks, significant). Partial response rate was primary efficacy respectively (p=0.66). endpoint statistically significant difference in favour of Caelyx (46% and 26% for Caelyx and ABV, respectively). HRQOL HRQOL: HRQOL: No statistically significant difference HRQOL: HRQOL: Statistically significant differences in favour of Caelyx : between paclitaxel and Doxil groups when in 5 of 9 domains of general HRQOL domains: general health, evaluated by KS Functional Assessment of HIV pain, social functioning, energy level, and health distress. Quality of Life (FAHI QOL). Statistically significant differences in favour of Caelyx in 4 of 9 domains of Kaposi’s sarcoma-specific HRQOL domains: pulmonary dysfunction/pain, restricted head/limb movement, exercise limitation, and sleep disturbance.

Safety: Safety: Safety: Fewer grade 3-4 AEs in Doxil group than Safety: Safety: “The overall treatment-related safety profile of Caelyx paclitaxel group: 66% vs. 84%, respectively. Less seemed to be favourable compared with the alternative grade 1-2 AEs: 11% vs. 58% incidence of alopecia combination therapy, since there are less risks associated and 9% vs. 26% peripheral neuropathy, respectively. with Caelyx and a better tolerability.” No incidence of cardiac toxicity (not a common AE in current comparator, but important in other anthracyclines). Effects Merged Data None OS increase None established None established established HRQOL change + No difference +

Safety change + + +

Recommendation + + +

Notes Evaluation of OS is complicated in this indication, since patients have inherent AIDS comorbidity.

Table 6: Daunoxome Health Technology Assessment Summary

Daunoxome (liposomal daunorubicin; daunorubicin citrate FDA Primary Indication liposome injection)

ATC Code: L01DB02

Orphan status: Orphan Daunoxome is liposome-encapsulated daunorubicin, an antineoplastic drug from the anthracycline family. Daunoxome is indicated for the treatment of AIDS-related Kaposi's sarcoma with extensive skin and mucous membrane or visceral involvement in patients at an Licensure: FDA, EMA advanced stage of the infection (CD4 < 200/mm3). [Source: HAS, 2014]

Marketing status: Inactive

Agency CADTH NICE HAS PBAC EPAR

Appraisal date Jul, 2014

Comparator ABV (adriamycin, bleomycin, and vincristine)

Modelled/indirect comparison No

OS: OS: OS: "Efficacy of Daunoxome seems equivalent to multidrug chemotherapy." OS: OS: Basis for classification

HRQOL: HRQOL: HRQOL: "No significant difference in terms of Karnofsky score, weight change, or HRQOL: HRQOL: QOL." Safety: Safety: Safety: Fewer alopecia and neuropathy related AEs. No significant difference in Safety: Safety: terms of haematological safety. Cardiac safety is "good" in both groups.

Effects Merged Data

None established None established OS increase No difference No difference HRQOL change + + Safety change + + Recommendation

Table 7: Depocyt Health Technology Assessment Summary

Depocyt (Depocyte; liposomal encapsulated FDA Primary Indication ara-C; sustained release cytarabine; cytarabine liposome injection)

ATC Code: L01BC01

Orphan status: Depocyt(e) is an encapsulated (liposomal) form of cytarabine that is characterised by a long period of activity after intrathecal injection. Depocyt(e) is indicated for the intrathecal treatment of lymphomatous meningitis, usually as part of a palliation strategy for the disease. [HAS, 2004] Licensure: FDA (1999), EMA (2001)

Marketing status: Active, Prescription

Agency CADTH NICE HAS PBAC EPAR

Appraisal date Jun, 2004 Jan, 2005

Comparator Cytarabine Cytarabine

Modelled/indirect comparison No No

OS: OS: OS: No OS data included. OS: OS: No statistically significant change in OS.

72% RR in Depocyt vs. 18% RR in cytarabine 72% response rate in Depocyte group vs. 18% in cytarabine Basis for classification group (statistically significant). group (statistically significant).

77 days PFS in Depocyt vs. 48 days PFS in cytarabine group (not statistically significant.

HRQOL: HRQOL: HRQOL: Karnofsky performance score and HRQOL: HRQOL: "[Depocyte] could improve patients' quality of life global HRQOL described as secondary because fewer intrathecal injections are needed." endpoint in pivotal trial, but no results described in HTA. No statistically significant differences in Karnofsky performance status or quality of life according to FACT-CNS instrument, Mini Mental State examination, and Q-TWiST analysis methodology.

Safety: Safety: Safety: No comparative data. Safety: Safety: "Treatment-related arachnoiditis was the most common adverse event […] the incidence of arachnoiditis was similar in patients treated with Depocyte versus conventional ara-C [cytarabine]."

Effects Merged Data None None established None established OS increase established HRQOL change + NA +

Safety change No difference NA No difference

+ + + Recommendation 94

Table 8: Myocet Health Technology Assessment Summary

Myocet (Non-pegylated liposome encapsulated FDA Primary Indication doxorubicin citrate; TLC-D99; D-99)

ATC Code: L01DB01

Orphan status: — Myocet contains doxorubicin citrate that is encapsulated in non-pegylated liposomes. Myocet in combination with cyclophosphamide (CPA) is indicated for the first line treatment of metastatic breast cancer in adult women. Licensure: EMA (2000)

Marketing status: Active, Prescription

Agency CADTH NICE HAS PBAC EPAR

Appraisal date Sep, 2001 Jan, 2005

Comparator Doxorubicin + CPA Doxorubicin + CPA

Modelled/indirect comparison No No

OS: OS: OS: No OS differences reported. Similar PFS OS: OS: No statistically significant differences and RR between Myocet and doxorubicin. established, but 2 combination studies showed 2- Basis for classification month OS differences favouring Myocet and 1 single-agent study showed a 5.5-month difference favouring doxorubicin.

HRQOL: HRQOL: HRQOL: No data reported. HRQOL: HRQOL: Mean changes for most parameters on the EORTC QLQ-C30 (BR23) questionnaire were similar between treatment groups. Minor differences in a few parameters to the advantage of either arm were observed. Safety: Safety: Safety: Cardiotoxicity rates significantly Safety: Safety: Myocet reduced the risk of cardiotoxicity, as greater in doxorubicin group than in Myocet measured by changes in left ventricular ejection group. fraction (LVEF) compared to doxorubicin. Apart from cardiotoxicity, Myocet and doxorubicin showed similar safety profiles.

Effects Merged Data

OS increase None established None established None established

HRQOL change No difference NA No difference

Safety change + + +

Recommendation + + +

Table 9: Mepact Health Technology Assessment Summary Mepact (mifamurtide; liposomal muramyl tripeptide FDA Primary Indication phosphatidyl ethanolamine; MTP-PE; liposomal MTP) ATC Code: L03AX15 Mepact contains the immunomodulator, mifamurtide. Mifamurtide activates monocytes and macrophages and this may be the Designation: Orphan mechanism responsible for its antitumour activity. Mepact is indicated in children, adolescents, and young adults for the treatment of high- grade resectable non-metastatic osteosarcoma after surgery. It is used in combination with post-operative multi-agent chemotherapy Licensure: EMA (2009) (doxorubicin, cisplatin, methotrexate, and ifosfamide). Marketing status: Active, Prescription

Agency CADTH NICE HAS PBAC EPAR

Appraisal date Oct, 2011 Nov, 2010 Dec, 2008

Comparator Multi-agent chemotherapy Multi-agent chemotherapy Multi-agent chemotherapy

Modelled/indirect comparison Yes Yes Yes

OS: OS: "Adding mifamurtide to OS: Improvement in OS at 7.9 year follow- OS: OS: "MEPACT significantly chemotherapy regimens statistically up point in Mepact + chemotherapy increased the overall survival of significantly improved overall group versus chemotherapy group alone, patients with newly-diagnosed survival compared with but expressed in terms of risk reduction resectable high-grade chemotherapy alone, with an overall (7.8%, HR = 0.72, 95% CI [0.53-0.97]) and osteosarcoma when used in survival of 71% in the control arm with statistical treatments of conjunction with combination (chemotherapy alone) and 78% in questionable validity. chemotherapy when compared the mifamurtide arm (chemotherapy to chemotherapy alone.” Basis for classification plus mifamurtide)." “The addition of adjuvant MEPACT [...] resulted in a relative reduction in the risk of death by 28% (p = 0.0313, hazard ratio (HR) = 0.72 [95% confidence interval (CI): 0.53, 0.97])." HRQOL: HRQOL: All Mepact-incorporating HRQOL: "According to clinical data HRQOL: HRQOL: NA arms of the study resulted in greater available, this product is not expected to QALY amounts than chemotherapy- have any impact on morbidity and only arms (+1.34, +0.59, +2.05 in mortality and quality of life compared three arms). with existing treatments."

"Very important issues affecting health-related quality of life […] had not been adequately captured in the economic analysis."

Mepact (mifamurtide; liposomal muramyl tripeptide FDA Primary Indication phosphatidyl ethanolamine; MTP-PE; liposomal MTP) Safety: Safety: Similar adverse event profile Safety: Similar rates of withdrawal Safety: Safety: "The observed toxicity between treatment arms, but between groups as a result of adverse profile raised no particular statistically significant increase in events. concern." subjective and objective hearing loss. But, "cisplatin was used in all arms of More hearing loss was found in Mepact Majority of adverse events the study and there is a known risk group than in chemotherapy-only group. thought to be related to the of hearing loss associated with its mechanism of mifamurtide use (usually in the range 5–15%). were reported as either mild or Accordingly, the rate of hearing loss moderate. seen […] was not unusual and could be an effect of cisplatin rather than mifamurtide."

Effects Merged Data OS increase Exact magnitude uncertain Uncertain Uncertain Uncertain

HRQOL change + + No difference NA

Safety Change - No difference - No difference

Recommendation + + + +

Table 10: Marqibo Health Technology Assessment Summary

Marqibo (vincristine sulfate liposome injection; FDA Primary Indication VSLI; vincristine sulfate liposome; marquibo; Onco TCS)

ATC Code: L01CA02

Orphan status: Orphan (FDA) Marqibo kit (vincristine sulfate, liposomes, and sodium phosphate injection) is indicated for the treatment of adults with Philadelphia Chromosome negative (Ph-) acute lymphoblastic leukaemia (ALL) in second or greater relapse or whose disease has progressed following two or more treatment Licensure: FDA (2012) lines of anti-leukaemia therapy.

Marketing status: Active, Prescription

Agency CADTH NICE HAS PBAC EPAR

Appraisal date

Comparator

Modelled/indirect comparison

OS: OS: OS: OS: OS: Basis for classification HRQOL: HRQOL: HRQOL: HRQOL: HRQOL:

Safety: Safety: Safety: Safety: Safety:

Effects Merged Data

OS increase NA

HRQOL change NA

Safety Change NA

Recommendation NA

Table 11: Onivyde Health Technology Assessment Summary Onivyde (irinotecan liposome injection; FDA Primary Indication nanoliposomal irinotecan; MM-398; PEP02) ATC Code: L01XX19 Orphan status: Orphan (FDA, EMA) Onivyde is liposome-encapsulated irinotecan that is indicated (in combination with fluorouracil and leucovorin [5-FU/LV]) for the treatment of Licensure: FDA (2015), EMA (2016) patients with metastatic adenocarcinoma of the pancreas after disease progression following gemcitabine-based therapy.

Marketing status: Active, Prescription

Agency CADTH NICE HAS PBAC EPAR

Appraisal date Nov, 2017 Apr, 2017 Nov, 2016 July, 2016

Fluorouracil / leucovorin (5- Fluorouracil / leucovorin (5- Fluorouracil / leucovorin (5- Comparator Fluorouracil / leucovorin (5-FU/LV) FU/LV) FU/LV) FU/LV)

Modelled/indirect comparison No No No No

OS: Significantly longer OS in OS: Significantly longer OS in OS: OS: "Onivyde appeared to OS: “An improved survival of Onivyde group than 5-FU/LV Onivyde group than 5-FU/LV provide a survival advantage, median 2 months, or a 50% group: 6.1 months vs. 4.2 months, group: 6.1 months (95% CI: 4.8 with an impressive hazard prolongation of median respectively. to 8.4 months) vs. 4.2 months ratio (0.67) although the survival, is considered Basis for classification (95% CI: 3.3 to 5.3 months), absolute gain in survival as clinically and regulatory respectively. measured by comparison of meaningful in patients with median survival was only ~2 relapsed/ refractory months." pancreatic cancer.”

HRQOL: "There were no HRQOL: "There was no HRQOL: HRQOL: "Quality of life was HRQOL: "Baseline median appreciable changes in the negative effect of pegylated assessed and there was no Global Health Status, proportion of patients who liposomal irinotecan on evidence that addition of Functional Scale and demonstrated QOL [EORTC QLQ- health-related quality of life." Onivyde lowered quality of Symptoms Scale scores were C30] improvements or life for patients." similar among treatment deterioration between Onivyde or Incomplete HRQOL data were arms.” (EORTC QLQ-C30 5-FU/LV arm. This is most likely collected in pivotal trial and HRQOL measured using instrument) due to large amounts of missing were not used in the sponsor's EORTC QLQ-C30: global data." economic modeling. health status, functional “Due to a too high early scale, and symptoms scale attrition rate, informative Q-TWiST analysis indicated that scores were similar among HRQOL data are not Onivyde arm was associated with treatment arms. available." 1.3 month greater Q-TWiST.

Patient Advocacy Group Findings: ‘Because nanoliposomal liposome is a four-drug combination instead of the more challenging five-drug

Onivyde (irinotecan liposome injection; FDA Primary Indication nanoliposomal irinotecan; MM-398; PEP02) combination (FOLFIRINOX), those who have experience with irinotecan liposome felt it was absorbed slower, had longer effectiveness, and had less toxic side effects.’

“Without Onivyde, I would not have had the energy or the presence of mind to enjoy the time.” Safety: More grade 3 or higher AEs Safety: Onivyde combination Safety: Safety: Onivyde appeared to Safety: More AEs in Onivyde in the Onivyde group than in the 5- arms were associated with "increase the burden of drug- arm, but closely followed by FU/LV arm: 92% in combination more treatment-emergent related adverse events." combination arm. arm vs. 87% in non-therapy arm serious adverse events. vs. 69% in control group. "The benefit-risk balance of "In NAPOLI-1, most TEAEs of Onivyde, given the proposed Onivyde in combination with usage, is favourable. This 5FU/LV were manageable assessment takes into with supportive therapy, consideration the very poor dose delays or both. No prognosis of the proposed unexpected safety findings patient group and the lack of have so far emerged from established alternative the liposomal irinotecan therapies." development program to challenge what is previously known from standard irinotecan."

Effects Merged Data 1.9 months OS increase < 3 months < 3 months < 3 months < 3 months (< 3 months)

HRQOL change + + No difference No difference No difference

Safety Change - - - - -

- - Recommendation +/- + + (pricing) (pricing)

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Table 12: Vyxeos Health Technology Assessment Summary Vyxeos (CPX-351; cytarabine:daunorubicin; cytarabine/daunorubicin; (cytarabine FDA Primary Indication and daunorubicin) liposome for injection) Vyxeos, a liposome-encapsulated combination of cytarabine and daunorubicin, is indicated for the treatment of adults with newly diagnosed ATC Code: — therapy-related acute myeloid leukemia (t-AML) or AML with myelodysplasia-related changes (AML-MRC). Orphan status: Orphan

Licensure: FDA (2017)

Marketing status: Active, Prescription

Agency CADTH NICE HAS PBAC EPAR

Appraisal date HTA commissioned

Comparator

Modelled/indirect comparison

OS: OS: OS: OS: OS: Basis for classification

HRQOL: HRQOL: HRQOL: HRQOL: HRQOL:

Safety: Safety: Safety: Safety: Safety:

Effects Merged Data

OS increase NA

HRQOL change NA

Safety Change NA

Recommendation NA

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Appendix C Search protocol for nanomedicine quality of life literature survey

Inclusion criteria: 1. Result must be a clinical trial summary. 2. Clinical trial must be investigating drug’s original indication (disease and drug regimen). 3. Clinical trial must use validated HRQOL measurement instrument and must report results therefrom. 4. Clinical trial must have a comparison group (placebo and observation groups included).

Search strategy:

First, check if PubMed will query related terms if marketed drug name is input, e.g. for Doxil, Abraxane: • In: doxil o Out: "liposomal doxorubicin"[Supplementary Concept] OR "liposomal doxorubicin"[All Fields] OR "doxil"[All Fields] • In: abraxane o Out: "albumin-bound paclitaxel"[MeSH Terms] OR ("albumin-bound"[All Fields] AND "paclitaxel"[All Fields]) OR "albumin-bound paclitaxel"[All Fields] OR "abraxane"[All Fields]

But for Daunoxome, Vyxeos:

• In: daunoxome o Out: daunoxome[All Fields] • In: vyxeos o Out: vyxeos[All Fields]

If PubMed does not expand search of drug name, I provided alternate common names for the drug, e.g.:

• Daunoxome OR "Daunorubicin Liposomal Injection" OR "daunorubicin citrate liposome injection" OR "liposomal daunorubicin”

Follow Rupp and Zuckerman for PubMed, and then modify to include broader results, while determining eligibility of results using inclusion criteria (original approval cancer type, comparator, validated HRQOL instrument used): 1. Drug name, cancer type, clinical trial filter, and MeSH terms quality of life and treatment outcome 2. Drug name, cancer type, and MeSH terms quality of life and treatment outcome 3. Drug name, cancer type, clinical trial filter, and MeSH term quality of life 4. Drug name, clinical trial filter, and MeSH terms quality of life and treatment outcome

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Figure 10 | Quality of life PubMed search protocol (author's screen capture)

Example of unexpanded PubMed full search protocol for Onivyde: 1. ((((onivyde OR Irinotecan liposome injection OR irinotecan liposome for injection OR MM-398 OR PEP02 OR Nanoliposomal irinotecan OR nal-IRI)) AND pancreatic cancer) AND quality of life[MeSH Terms]) AND treatment outcome[MeSH Terms] Filters: Clinical Trial 2. ((((onivyde OR Irinotecan liposome injection OR irinotecan liposome for injection OR MM-398 OR PEP02 OR Nanoliposomal irinotecan OR nal-IRI)) AND pancreatic cancer) AND quality of life[MeSH Terms]) AND treatment outcome[MeSH Terms] 3. ((((onivyde OR Irinotecan liposome injection OR irinotecan liposome for injection OR MM-398 OR PEP02 OR Nanoliposomal irinotecan OR nal-IRI)) AND pancreatic cancer) AND quality of life[MeSH Terms]) 4. (((onivyde OR Irinotecan liposome injection OR irinotecan liposome for injection OR MM-398 OR PEP02 OR Nanoliposomal irinotecan OR nal-IRI)) AND quality of life[MeSH Terms]) AND treatment outcome [MeSH Terms] Filters: Clinical

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Preliminary results from modified Rupp and Zuckerman search protocol for approved cancer nanomedicines comprise Table 13.

Table 13: Survey of Investigations in Nanomedicines’ Effects on Quality of Life

Effect on Quality of Quality of Life Quality of Life Drug Name Cancer Type Life Measures Comparison Groups

KS-FAHI, AIDS-related QOL Doxil/Caelyx Kaposi’s sarcoma ABV chemotherapy questionnaire (unspecified) Better

FACT-CNS Lymphomatous Cytarabine; Depocyt KPS meningitis methotrexate Q-TWiST

No statistical Metastatic pancreatic Onivyde EORTC QLQ-C30 5-FU/LV difference cancer

Daunoxome Kaposi’s sarcoma N/A N/A

Ph-negative acute Marqibo N/A N/A lymphoblastic leukaemia

Myocet Metastatic breast cancer N/A N/A No data reported Mepact Osteosarcoma N/A N/A

Abraxane Metastatic breast cancer N/A N/A

Vyxeos Acute myeloid leukaemia N/A N/A

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Appendix D Proposal for study of patient experiences with cancer nanomedicines

Narratives in nanomedicine: How women with advanced ovarian cancer experience treatment with Caelyx

1. Introduction

Modern cancer therapies embody two central—but usually disparate—aims: to prolong patients’ foreshortened lives and to enhance patients’ disease-hindered quality of life (QOL)118 relative to a situation wherein these patients remain untreated219. In the best cases and with the best therapies, both aims can be realized220,221, but in typical cases, the former is achieved at the expense of the latter, if at all222–224. Acknowledging that many chemotherapies are given for the sole purpose of palliating symptoms112 and that survival advantages offered by new drugs are frequently modest225, there has been a push for greater consideration of the patient’s treatment experience in the cancer drug development and approval process8,146,192.

Chemotherapeutic nanomedicines were designed with the aim of enhancing therapeutic efficacy by delivering large drug payloads directly to solid tumours95,226–230, but, despite decades of work, the technology has not yet proven to be cancer’s “magic bullet”231,232. Nanomedicines have, however, been found to beneficially alter a drug’s toxicity profile233, which can positively impact a patient’s health-related QOL (HRQOL). Caelyx (pegylated liposomal doxorubicin), for example, has been shown to significantly reduce the incidence of cardiomyopathy in patients234, which previously represented a dose-limiting side effect of conventional doxorubicin110. Frustration and negativity are mounting as a result of cancer nanomedicine’s low rates of clinical translation38 and poor drug delivery performance235, but some argue that the therapies that have been translated156,236,237 are providing great clinical benefit to patients. By “shifting the balance between off- and on-target localization”, nanomedicines can be better tolerated and are better suited for prolonged dose regimens238. Given these marked differences in opinion, it seems that a gulf exists between the therapeutic priorities of those who research and develop nanomedicines, 105

those who regulate them, those who prescribe them, and those patients whose cancers are treated with them: in the evaluation chemotherapeutic drugs, should a formulaic delineation of therapeutic efficacy be of primary importance, or should a holistic determination of patient benefit be chief?

Allying with advocates for “patient-centred” drug development in oncology146, I, through this proposed research, intend to illuminate patients’ experiences and priorities surrounding treatment with one of the oldest and most widely studied cancer nanomedicines, Caelyx. In order to provide the medical community with vivid understandings of what potential HRQOL improvements mean from a patient’s perspective, I ask the research question, “How do women with platinum-resistant epithelial ovarian cancer (PREOC) experience treatment with Caelyx at the Princess Margaret Cancer Centre in Toronto, Ontario?” Conversations with key gynaecologic medical oncologists at the Princess Margaret guided my selection of participants being treated for PREOC—one of a handful of diseases Caelyx is approved to treat239. (Full research question deconstruction in Appendix D-I.)

In 2012, nearly 14 million Americans were living with cancer or with a history of it7, and in 2013 there were an estimated 195,767 women living with ovarian cancer240 in the same country. At a time when many cancers can be considered chronic conditions112,118, and at a time when the treatment of advanced epithelial ovarian cancer cannot be considered curative241, I argue that the research and development of efficacious and well tolerated medicines—serving as maintenance or palliative therapies—should be prioritized alongside the search for cures. Analyzing and conveying these women’s narratives to the medical community should act to humanize their efforts and to add nuance to classic patient-reported outcome measures (PROMs) of ovarian cancer HRQOL136,242–244.

As a researcher embracing an interpretivist-constructionist paradigm245,246, I acknowledge my personal values and lived experiences as critical to and irremovable from the research process: I am a cancer nanomedicine researcher and the son of a father recently deceased from cancer. This 106

amalgam of positionality and experience has given rise to my conviction that HRQOL is principal in a patient’s illness experience, yet it is underrepresented in cancer drug development and evaluation (especially of chemotherapeutic nanomedicines). I aim to contribute to a conversation about HRQOL within the cancer research community with this exploratory study, in which I will compassionately co-construct with participants their stories of illness, treatment, and the meanings manifest in HRQOL changes through these processes.

2. Methodology

To understand and portray the experiences of women being treated with Caelyx for PREOC, I will follow the methodological traditions of interactional narrative analysis as described by Riessman247. This methodology seeks to have “storyteller and questioner jointly participate in a conversation…as a process of co-construction, where teller and listener create meaning collaboratively.” Interactional narrative analysis attends to “speech in all its complexity, not simply as a vehicle for content.”247 In this way, I will explore with my participants the circumstances of their treatment experiences as well as the emotional, relational, and social milieu in which these experiences occurred. The strengths of this methodology are embedded in the strengths of storytelling: stories are sense-making devices; are evocative and memorable; are perspectival; capture tacit knowledge; are persuasive; and are open to interpretation248. Importantly, narratives are helpful in that they shed light on other sources of evidence like HRQOL scales248, which serves well the interdisciplinary and interparadigmatic nature of this research.

In tandem with advocacy for emphasizing PROMs in oncologic drug labeling192 are calls for narrative research in the health sector248, generally, and of cancer experiences249, specifically. Bury250 writes that interest in illness narratives may stem from a “desire to limit the sometimes dehumanising effects of a medicalised society…that deliver[s] increasingly technical sophistication, but fail[s] to offer ‘comfort and care’ for patients as whole human beings.”

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Interactional narrative analysis is thus ideally suited to add nuance and humanity to our crude and formulaic understandings of patients’ experiences of illness and treatment.

3. Theory

I approach this work of understanding patient experiences from an interpretivist-constructionist research paradigm245,246, which embodies the ontological, epistemological, axiological, and rhetorical characteristics outlined in Table 14.

Table 14: Interpretivist-Constructionist Research Paradigm

Rhetorical Ontology Epistemology Axiology Structure

{Nature of Reality} {Nature of Knowledge} {Role of researcher values} {Language}

1st person Interpretivism: “knowledge is language, strong subjective; there are multiple, Relativism: “reality is narrative voice diverse interpretations of reality; Reflexivity: the researcher subjective and changing; used to describe there is no one ultimate or acknowledges and describes there is no one ultimate interaction with ‘correct’ way of knowing”245; their values, positionality246 truth”245 the research and knowledge is co-constructed with with research research participants participants246

This theory of knowledge is appropriate for an interactional narrative analysis methodology using semi-structured interviews as a method since my aim is not to collect facts, but to understand perspectives and to co-construct narratives, engaging my own values in the process. As participants tell me their stories, they too have interpreted reality before synthesizing it into narrative; indeed, “[n]arratives do not mirror, they refract the past.”247

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I intend to apply established theory at two stages of this research251: while considering sampling strategy and in developing data generation tools.

3.1 Considering methodology and sampling strategy

The transition theory of nursing252–254—a middle-range theory—and Frank’s illness narratives255 were used as sensitizing concepts for proposing sampling women with PREOC at the particular time of Caelyx treatment. At the Princess Margaret Cancer Centre, women are prescribed Caelyx for epithelial ovarian cancer only if they are found to have PREOC, which is indicated by a time to relapse of less than six months256. This means that the total time elapsed between diagnosis, first-line treatment, relapse, and second-line treatment is likely less than one year for the women who participate in this study. With this information from our clinical partners, I recognized that these women might hold rich information regarding transitions between clinical states, and, perhaps, between the types of stories told about illness and treatment. The transition theory of nursing deals with the importance of transition points in a patient’s illness experience and how incongruous expectations about “changes and differences” influence the way patients experience them254,257. For instance, the rapid succession of treatment transitions women with PREOC are likely to have experienced, along with their contingent expectations, may influence the stories they tell about their illness. The recency of these experiences might afford us rare insight on how these patients’ narratives can change and why.

Frank255,258 describes three common narratives an ill person uses to describe their experience: • The restitution narrative: the story of being restored to health by modern medicine; “a response to an interruption, but the narrative itself is above interruption.”255 • The chaos narrative: the story of a randomly progressing illness by a storyteller without hope of improvement; common to diseases without cure or reliable treatments258. • The quest narrative: the story of those who “accept illness and seek to use it.” Illness becomes “the occasion of a journey”255 wherein the narrator explores the meaning of suffering, the possibility of death, and the claiming of a “newer, wiser state.”258

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Sampling women being treated with Caelyx for PREOC will yield rich information about the experience of this disease, of being treated with this drug, and may uncover unique information about the effects of transitions on participants’ views of treatment and on the type of narrative constructed while telling stories of illness. Bringing this theory to a study about HRQOL will allow me to draw from and compare findings to established bodies of knowledge, thus enriching and contextualizing my research insights.

3.2 Developing data generation tools

To use semi-structured interviews for eliciting rich, storied data from study participants, I will consider Bourdieu’s principle of non-violent communication259 as inspiration. He emphasizes “social proximity and familiarity” as important factors for facilitating freer sharing of information than in situations of obvious cultural asymmetry. Recognizing that I am neither a woman nor am I likely to be close in age with my study participants—median age for diagnosis of epithelial ovarian cancer is 60 to 65 years260—I intend to cultivate social proximity and familiarity by sharing with participants my experiences of supporting an ill family member, my understanding of some issues these women face, and the value these women’s stories hold in my life and work. This principle is particularly important in the context of this project because only with the establishment of closeness and trust will study participants be willing to share intimate, emotional, and meaning-rich stories.

4. Information power

To guide the determination of sample size in qualitative interview studies, Malterud et al.261 proposed ‘information power‘—a conceptual analogy to the quantitative calculation of a study’s statistical power. The authors suggest that information power depends on: the aim of the study; sample specificity; use of established theory; dialogue quality; and analysis strategy. I describe each of these factors as they relate to this proposed study in Table 15, along with their impacts on information power, and thus, sample size.

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Table 15: Information Power Determination

Effect Information Power Study Design Details Required Sample Dimension Information Power Size

Study Aim: Narrow: study explores a relatively rare experience (low Grows Falls Narrow, Medium or direct transferability) Broad

Dense: purposeful, Sample Specificity: homogeneous sampling used to Grows Falls recruit women experiencing the Dense or Sparse exact phenomenon under study

Theory Applied: Stage-wise: sampling strategy Grows slightly Falls slightly Systematically, Stage- and data generation wise, or Not at All

Dialogue Quality: Medium: Trained but novice interviewer with familiarity Unchanged Unchanged Strong, Medium, or with participant situation, but Weak some social distance exists

Analysis Strategy: Case-concrete interview- Grows Falls 262 Case or Cross-Case based analyses performed

Considering this study’s information power and following the traditions of narrative analysis, wherein small sample sizes are commonplace (because of the approach’s aim for richness rather than statistical representativeness)248, I plan to sample a ‘small’ number of women. Given the limited time and resources available to complete this study—exploratory, master’s project, small research team—coupled with the story-embedded nature of the information required to answer our research question and the assessment outlined in Table 15, interviewing three to five women should satisfy our aim.

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5. Sampling strategy

In interpretivist qualitative research studies, rather than striving for representativeness through random sampling, participants are purposefully selected for their ability to uncover rich information about the focus of inquiry263. The aim of this research is to understand and illuminate the experiences of women living with a specific disease who are being treated with a specific drug at a specific hospital. The narrowness of this study aim requires a narrow sample population, who are all, most basically, experiencing the same pre-defined phenomenon: treatment with Caelyx in the clinical scenario of PREOC. Rich information about this phenomenon and the meanings associated with it can be gleaned using homogeneous sampling263 of participants from this narrow clinical population. Each woman interviewed for this study will be embedded in a unique social context, which, I expect, will engender diversity in the experience of treatment and in the kinds of stories told.

Participants will be consulted by our clinical partners during regular appointments and evaluated to ensure they meet the following eligibility criteria for this study: • Women with a clinical diagnosis of epithelial ovarian cancer; • Less than six months after first-line platinum and taxane-based chemotherapy264 the cancer relapsed—women with PREOC 256; † • Women being treated for PREOC with Caelyx in their fourth cycle of chemotherapy; • Women who are physically, psychologically, and cognitively265 able to participate in hour-long interviews, as determined by clinical facilitators.

† In order for participants to have a holistic understanding of the side effects of Caelyx treatment and to have reflected on the meanings manifest in these side effects’ impacts on their lives, patients’ fourth treatment cycle was suggested by our clinical partners as an opportune time to conduct interviews.

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6. Data collection method

Patient stories will be co-constructed using in-depth, semi-structured interviews266,267. Though homogeneous sampling strategies are often amenable to focus group-based data collection263, the method would be inappropriate here given the sensitivity of this participant group and the impracticality of bringing six to eight268 of these women together. Ethnographic observation would be impractical given that women in this patient group are often outpatients and this research team has neither the time nor resources to pursue this approach. Questionnaires are well suited for the codified assessment of HRQOL in clinical trial settings, but would be inappropriate for co-constructing nuanced patient narratives.

Narrative research traditions encourage in-depth interviews to be conducted as a conversation guided by the researcher’s curiousity248, but to ensure richness of the data collected by prompting patients’ reflection on specific aspects of the treatment experience, an interview guide was prepared (Appendix D-II). Prompts provided in the interview guide touch on topics covered in widely-used HRQOL inventories136,242–244 in order for this research to illuminate themes common to those examined in clinical trials, and thus serve as a grounding point for researchers more familiar with those traditional clinical tools.

7. Data analysis strategy

The result of interactional narrative analysis is the synthesis of disconnected event descriptions into a whole, coherent story that lends explanatory meaning to the data. Polkinghorne writes, “The analytic task requires the researcher to develop or discover a plot that displays the linkage among the data elements as parts of an unfolding temporal development.”269 I will transcribe interview data, engage in several close readings of the transcripts, and revisit field notes taken during interviews that shed light on mood, tone, and non-verbal communication observed at that time. Using the most salient, meaning-rich stories and unearthed plotlines (loosely considered

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“codes” and “themes”270), I will compose cohesive patient vignettes for publication in a medical, nanotechnology, or healthcare-leaning sociology academic journal.

The interactional narrative analysis approach is inherently flexible to surprise and discovery; it seeks to co-construct stories that are perspectival and unique to storytellers’ lifeworlds248, which aligns well with a constructionist worldview and our research question.

8. Ethics

We have partnered with medical, research, and nursing professionals from at the Princess Margaret Cancer Centre to pursue access to patients through the University Health Network’s Research Ethics Board. We continue to seek guidance from these stakeholders in the development of this research project in order to meaningfully and ethically interact with this participant group. According to the Risk-Vulnerability Matrix and Explanations (Table 16), this work earns a ‘Level 2 Review’ classification.

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Table 16: Risk-Vulnerability Matrix and Explanation

______Research Risk______

Group Vulnerability Low Medium High

Low 1 1 2

Medium 1 2 3

High 2 3 3

Research Risk Group Vulnerability

• No physical intervention; no deception; interview • Participants are adult women receiving treatment for guide engineered for patients to volunteer their own ovarian cancer after their first relapse of the disease. experiences and to describe relatively recent events; • According to this study’s eligibility criteria, patients to be briefed many days before interview. participants should have full cognitive autonomy and • Medium rating assigned: we anticipate that should be capable of actively deciding their describing the detailed circumstances of diagnosis participation. and relapse may elicit strong emotional responses • Medium group vulnerability assigned: prognoses for during interviews. women with PREOC are dismal271; recognizing and • To protect participants, we will only explore respecting the value of participants’ time and narrative areas that they are willing to explore and HRQOL is critical to interacting ethically with these have consented to. participants and honouring the aims of this study. • To ensure confidentiality of participants, audio recordings will be destroyed following transcription and any identifying elements of the transcript will be removed or coded, such that only the interviewer could link narratives to individual subjects. Participants’ access to treatment will not be related to this study, and the information collected will not be divulged to their care providers.

9. Quality and rigour

Rigour in qualitative research is a “product of the soundness of the theory, the transparency of the research assumptions, and the integrity of the research processes for data gathering and analysis.”245 Through reading and consultation with qualitative research professionals, I have worked to ensure the paradigmatic alignment of all aspects of this research. I have made clear my axiology and will continue to be transparent about assumptions made whilst conducting this research. I intend to perform member checks at the conclusion of each interview—reflecting on

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my interpretation of events and asking participants if my understandings were true to their experience—and I will leave an audit trail of memos detailing how I made decisions and came to analytic conclusions. Importantly, I will also identify the limitations of this research, which include low generalizability due to the narrowness of my research question and my inability to engage in a long-term, multi-interview study to shed light on temporal changes in illness narratives. Another perceived limitation of this study might include its small sample size, but the exploratory nature of this research and the proposed study design support the decision to engage with three to five participants.

Criteria for rigour specific to narrative research I intend to pursue include trustworthiness, plausibility, and criticality248. Trustworthiness deals in seeking a “thick description” of events that has been member-checked by research participants in order to ensure that what I write echoes what my participants truly wanted to tell me and how they truly felt. Plausibility deals in reader engagement, such that the account rings true to experience. Criticality deals in researcher reflexivity, where findings are openly questioned and alternate interpretations explored.

Continued collaboration with clinical partners who have significant experiences treating PREOC with both conventional treatment and with Caelyx is also a key to the quality of this research.

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Appendix D-I: Deconstruction of research question

Verb choice: “experience” • This research seeks to understand the lived experiences of those undergoing cancer treatment with nanomedicines from an interpretivist-constructionist worldview using an interactional narrative analysis methodology. Lived experiences and the meanings ascribed to them will be the central foci of this work.

Participants: “Women with platinum-resistant epithelial ovarian cancer (PREOC)” • PREOC is one of the few clinical indications that Caelyx is prescribed for. This participant population has just experienced first relapse and may be in the process of adjusting their expectations of treatment and their values surrounding HRQOL.

Key concept: “treatment with Caelyx”: • Caelyx is one of the oldest and most widely studied chemotherapeutic nanomedicines. Describing patient experiences with this drug, in particular, stands the greatest chance of resonating with researchers, regulators, funding bodies, clinicians, and patients, hopefully reinforcing the value of ‘patient-centred’ oncologic drug development.

Key concept: “at the Princess Margaret Cancer Centre in Toronto, Ontario”: • This defines our narrowness of scope and makes clear the location of research, which can shed light on the economic, political, and social contexts in which these patients experience treatment—critical data in interactional narrative analysis traditions. For instance, because of Canada’s public health insurance system, the drugs and clinical resources used to provide cancer treatments typically do not cause patients to fall into financial debt, as these might for uninsured or underinsured patients in the United States. For readers interested in applying the findings of this research to settings outside of Canada, it would be important to understand that this national policy may give rise to differences in women’s treatment narratives relative to those treated in other countries by limiting the financial burden associated with cancer treatment.

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Appendix D-II: Interview guide

This interview guide was designed to capture a broad view of the experiences and meanings manifest in PREOC treatment: 1. Tell me the story of your first diagnosis. a. When were you diagnosed? Where? b. How did this affect you? Your family? Your friends? Your work? 2. Tell me a story about your life as a woman being treated for ovarian cancer. a. To whom have you disseminated the information of your illness, your progress? b. How do you tell this story to your friends/family/colleagues? c. Do you have young children or grandchildren? How have you told them this story? How have they responded? 3. Describe what you were thinking/feeling/expecting as you approached your first-line chemotherapy treatment? 4. How would you describe a day in your life during first-line chemotherapy treatments? a. What was the most significant challenge to your quality of life? i. What side effects of treatment did you experience? b. What activities did you have to cut back on or stop? c. What were you able to continue doing? 5. What was it like to learn that you had relapsed and needed to return to treatment? a. How did this affect your expectations of treatment outcomes? b. How did this affect the goals and plans you made for life? c. How did this affect your relationships with family, friends? 6. What expectations did you have about the drug being prescribed as second-line treatment (Caelyx)? What were you told about it? 7. What goals and expectations do you have for the outcome of second-line treatment? a. Would you say these expectations have changed compared to those you had for first-line treatment? 8. How would you describe a day in your life during second-line chemotherapy treatments? a. What was the most significant challenge to your quality of life? i. What side effects of treatment did you experience?

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b. What activities did you have to cut back on or stop? c. What were you able to continue doing? 9. What would less pain/fatigue/nausea allow you to do, pursue, achieve? 10. What are aspects of your life that you have lost and hope to reclaim? a. What are aspects of your life that you have lost and accept that you can never reclaim? 11. What have you learned about yourself through this illness? a. How have you changed physically/emotionally/socially/spiritually/your values? 12. Has anything positive come out of your experience with illness? 13. What would you like doctors to ask about your well being/quality of life? 14. What would be helpful to you as you continue with treatment? 15. What does it mean to have someone to listen to your stories of illness? What does it mean to tell them? 16. What does ‘quality of life’ mean to you? 17. What else would you like to tell me?

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