Personalized Healthcare in : Past, Present and Future

Eric Walk, MD, FCAP Chief Medical Officer, Ventana Medical Systems Inc., a member of the Roche Group November 16th, 2016 EMPAA 2016 Annual Meeting, New Castle, New Hampshire Disclosures

I am an employee of Ventana Medical Systems, Inc., a member of the Roche Group.

I will not be discussing the off-label use of any pharmaceutical or diagnostic products. Personalized Healthcare in Oncology

PtPast

Present

Future Personalized Healthcare AfA fron t row seat

2001-2005: Novartis Oncology

2005-2008: Ventana Medical Systems, Inc.

2008-present: Roche Diagnostics Personalized Healthcare in Oncology

PtPast

Present

Future Traditional treatment paradigm in oncology One size fits all

Traditional oncology paradigm Trial and error /one drug fits all

Responder Non-responder One size does not fit all drugs effective in only 25% of patients

Percentage of population for whom class of Antidepressants Asthma Drugs Diabetes Drugs ddtdrugs do not work

Arthritis Drugs Cancer Drugs

Spear B et al. Trends in Molecular Medicine May 2001 Broken drug development model Increased spending , decreased output

R&D Spending by Pharmaceutical Companies (US$ in billions) $45 # of NDAs Pending at Close of the Calendar Year 400 $39 $40 350 $35 300 $30 250 $25 200 $20 150 $15 100 $10 107

$5 50

$0 0 2001 2002 2003 2004 2000 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999

PhRMA 2012 Pharmaceutical Industry Profile New era of personalized healthcare Herceptin (1998) and Gleevec (2001)

1998 2001 Personalized healthcare model in oncology Biomarker-based identification of responders

Targeted Traditional oncology paradigm Trial and error/one drug fits all

Responder

Non-responder Personalized healthcare “The right drug for the right patient” Personalized healthcare Definitions

Disease risk (E.g. BRCA)

Drug A form of medicine that Prognosis/risk uses information about Disease ooecuecef recurrence response monitor ing a person’ s genes, (E.g. (E.g. Ca125) , and Oncotype dx) prediction (E.g. Her2) environment to prevent, diagnose, and treat disease.

Pharmaco- genetics (E.g. Cyp450 genotyping) 2005: personalized healthcare paradigm questioned Short-term fad or long-term sustainable model in oncology?

Drug(s) Companion Diagnostic Drug Approval

1998 (metastatic breast TbTrastuzumab (Hercepti n®) HER2 cancer) 2001 (CML) (Glivec®) KIT 2002 (advanced GIST)

Erlotinib (Tarceva®) EGFR mutations 2004 (advanced NSCLC)

KRAS mutations (negative 2004 (advanced colorectal (Erbitux®) predictor) cancer)

Return to the “one size fits all” model ? Personalized healthcare was not a fad Steady increase in FDA approvals

Masters et al. JCO 2015 “Clinical Cancer Advances 2015 Annual Report on Progress Against Cancer from ASCO” Personalized healthcare widespread adoption Expplosion in druggg:diagnostic co-development

Biomarker #Drugs Drug(s) erbB 1 FGFR 4 AZD-4547 BGJ-398 dovitinib lactate FP-1039 FLT3 4 KW-2449 dihydrochloride tandutinib folate recp 2EC-145farletuzumab GPC3 1GC-33 GPNMB 1 HER2 8 ARRY-380 CP-724714 TD-M1 HLA-A2 1 ALT-801 IGFR 1 IL13R 1 hIL-13-PE38QQR 1IMGN-388 KIR121 1Karostimoncology drugs with stratification biomarkers in Lewis Y 2 CMD-193 hu3S193 LHRHR 2 AEZS-108 EP-100 development Mek 1Trametinib mesothelin 2 SS1(dsFV)-PE38 Met 3 EMD-1214063 SGX-523 N-cadherin 1Exherin NPC-1C 1 NY-ESO-1 1CDX-1401 PDGFR 2 PgR 1Lonaprisan Ph+ 8 DCC-2036 imatinib IY-5511 omacetaxine mepesuccinate PI3K 2 BEZ-235 BKM-120 RAAG12 1 RAV12 somatostatin 1177-Lu-DOTA-oct TA-MUC1 1GT-MAB2.5-GEX TdT 1 Cordycepin 3 Abiraterone acetate degarelix orteronel TS 1Thymectacin Hayashi K et al. Clin Pharm Ther. 2012 Oct 11 Second Wave of Personalized Healthcare Drug and Diagnostic Combinations Continue

2011 2011

ZELBORAF XALKORI () () Approved for patients with locally Approved in US for people with BRAF advanced or metastatic NSCLC that are VEV600E mutate d metastat ic me lanoma ALK-positive.

BRAF test ALK test • Roche cobas 4800 BRAF V600 Mutation • Vysis ALK Break-Apart FISH Probe Kit Test • Identifies patients with ALK positive • Identifies patients with BRAF V600E NSCLC mutations • Approx 3% to 5% of NSCLC patients • BRAF is m utated in app ro ximate ly ½ o f have an ALK-positive tumor late-stage Personalized Healthcare in Oncology

Past

Present

Future Personalized healthcare benefits Acceleration of drug development and approval timelines

BCR-ABL inhibition 2001 (imatinib) 41 yrs 1960 T argeted therapy

ERBB2 inhibition () 13 yrs 1998 FDA A

1985-1987 p with BM strateg with BM proved

BRAF inhibition (vemurafenib) 10 yrs 2011 y

2002

ALK inhibition 2011 (crizotinib) 4 yrs

2007 Adapted from Chin L et al. Nature Medicine March 2011 Reduced attrition rates in drug development Targeted therapy increases success from phase 1 to registration

0.5 0.47

0.45

0.4

0.35

0.3 All oncology drugs 0.25 0180.18 Kinase inhibitors 0.2

0.15

0.1

0.05

0 All KI n=974 n=137

Phase I‐Registration transition probability all oncology drugs vs. kinase inhibitors

Walker I, Newell H. Nature Rev Drug Discov.8:15-16 (2009) Molecular reclassification of disease Paradigm shift in how we understand and treat non- small cell (NSCLC)

Dr iver mu ta tions in NSCLC 2000 DiDriver mutat ions in NSCLCTdNSCLC Today

Unknown Unknown

. Treatment: platinum doublet • Treatment: Targeted matched to molecular defects ((ge.g. EGFRmut, ALK, RAS)

. Response rate: 10-20% • Response rate: 50-70%

Image adapted from Sharma et al., Nature Rev Ca. Vol 10, pg 241-253, 2010 Continued paradigm shift in disease classification From anatomic origin to molecular driver events

Breast Prostate Colon Lung Brain

PIK3CA BRAF HER2 EGFR KIT Companion Diagnostics Diagnostic tests required for drug selection and use

HER2 Dual ISH

Patient information shown is for illustrative purposes only Tissue Diagnostics Pre-PHC Primarily focused on diagnosis

H&E + IHC/ISH

Diagnosis . Malignant . Benign . Morphologic classification Tissue Diagnostics Post-PHC Delivering critical treatment guiding information

Molecular Profiling IdentificationClinical of Drug Info Targets, H&E + IHC/ISH + Resistance Mechanisms , Immune Checkpoints and Heterogeneity

Treatment guiding information

Diagnosis Prognosis Therapy prediction • Malignant • Risk of recurrence • Response • Benign • Need for adjuvant • Resistance • Molecular chemotherapy classification • Rational combo tx Personalized healthcare challenge #1 Inevitable drug resistance with all targeted therapies

Primary resistance “Acquired” resistance

TtdTargeted therapy

CidiiCompanion diagnostics Initial response Recurrence ( 1-2 yrs)

Resistance mechanism #1 Resistance mechanism #2 Resistance mechanism #3

Multiple molecular mechanisms of resistance “Acquired” resistance mechanisms in cancer Acquisition or selection?

Mechanism appears to be selection of rare pre-existing tumor clones Translational lung , Vol 4, No 6 December 2015 Resistance Through of Genomic Driver Mutations Molecular ‘Whac-A-Mole’

Targeted Therapy Personalized healthcare challenge #2 Tumor heterogeneity

Intra-tumoral spatial heterogeneity Renewed appreciation of tumor heterogeneity Swanton et al. 2012

Gerlinger, Swanton et al. NEJM 366;10 (2012) Intra-tumor heterogeneity in renal cell 65%%f of mutations not present in every bioppysy

Gerlinger, Swanton et al. NEJM 366;10 (2012) Branched evolution heterogeneity map Molecular history of a tumor

Branch length proportional to number of NS mutations from branch point

Gerlinger, Swanton et al. NEJM 366;10 (2012) Branched evolution heterogeneity map Differential mTOR expression

ON

Branch length proportional to number of NS mutations from branch point OFF

Gerlinger, Swanton et al. NEJM 366;10 (2012) Branched evolution in lung cancer Long vs. shkhort trunks

Charles Swanton Intra-tumoral heterogeneity and predicting outcome Myeloma subclone determining final outcome: <1%

Keats et al. Blood. 2012 August 2; 120(5): 1067–1076. Intra-tumoral heterogeneity Diversity enables darwinian evolution and selection

Charles Darwin - July 1837 – 1st sketch of evolutionary tree Tumor heterogeneity in the news Threatens PHC approach

http://www.genengnews.com/insight-and-intelligence Previous assumppgtions of tumor homogeneity incorrect Implications for tumor sampling procedures Previous assumppgtions of tumor homogeneity incorrect Implications for tumor sampling procedures PHC Challenge #3 Evolvinggg Diagnostics Reg ulatory Landscap e

2010 2011 2014 2016

38 US FDA Diagnostic Registration Process

• Diagnostic registration: – Regulated by FDA Center for Devices and Radiological Health (CDRH) – Driven by a risk-based classification of the product – Different levels of controls and length/expense of registration process

• Final designation of the product determines how a product is labeled and marketed (i.e. “claims”)

Must label “Not for Must label clinical use” “Investigational Use In-vitro diagnostics Cannot market for Only” clinical applications Cannot market Companion Diagnostics

Product Class ASR RUO IUO Class I Class II Class III

FDA VliitdVery limited Clini cal titria ls Lim ited 510K PMA premarketing requirements 39 Companion Diagnostic Development Parallel Development of Drug and Diagnostic

Pre-Clinical Phase I Phase II Phase III Commercialization Drug

Biomarker Evaluation Companion Diagnostic Development

Biomarker Prototype Clinical Assay Trial Regulatory Global && nostic Discovery Assay/RPAs Validation Development Support Submission Launch

Design and develop robust Assay, with In-house clinical Develop Assay , scoring algorithm, Traditional and Accelerated Launch Diag testing of Pharma’s patient tissue samples control slides, and training materials. Models available

Assay Development and CAP/CLIA clinical IVD development and support studies

40 A Tale of Two Diagnostics In V itro Diagnostics (IVD s) & L ab D eveloped T ests (LDT s)

IVD

LDT

http://labsoftnews.typepad.com/file_uploads/Harper_LDT.pdf A Tale of Two Diagnostics In Vitro Diagnostics (IVDs) & Lab Developed Tests (LDTs)

In Vitro Diagnostic Laboratory-Developed (()IVD) Test (()LDT) Centrally developed for Designed, manufactured Development, wide (e.g. global) and used in a single lab distribution and usage distribution and use (()initial intent) FDA, but provisions were historically not enforced. Regulatory Authority FDA Lab quality regulated under CLIA; Draft FDA guidance issued 2014 Analytical validation Premarket clearance or Review process reviewed biennially; often approval required after test already in use

Apppplicant validation Analyyytic Validity Analyyytic Validity requirements Clinical Validity Clinical Validity

Draft Guidance for Industry, FDA Staff, and Clinical Laboratories: Framework for Regulatory Oversight of Laboratory Developed Tests (LDTs). October 3, 2014.. Accessed 3/17/15 at www.fda.gov 43 http://www.fda.gov/MedicalDevices/ProductsandMedicalProcedures/InVitroDiagnostics/ucm407296.htm 44 http://www.fda.gov/MedicalDevices/ProductsandMedicalProcedures/InVitroDiagnostics/ucm407296.htm FDA Levels the Diagnostics Playing Field Warning Letter to 23 & Me, November 2013

45 FDA Draft Guidance Framework for Regulatory Oversight of LDTs • October, 2014: draft Guidance: “Framework for Regulatory Oversight of Laboratory Developed Tests (LDTs).” –A risk-based approach: Class I,,, II, III – start with high risk tests and phase in enforcement over time (9 years).

6 months 12 months 24 months 4 years 5 years 9 years

Notification Priority list FDA releases FDA completes Pre-market for remaining priority list phased-in Moderate completed risk LDTs and/or review for high risk for moderate enforcement of registration, initial high (class III) risk (class II) premarket phased-in listing and risk (class III) devices with devices review for class adverse devices submission III & begins event starting 12 class II phase-in reporting months later

Exceptions • Low-risk LDTs • Traditional LDTs: manufactured and used by a sing le hea lth care f acility ilit • Rare diseases (<4,000 patients/year) • LDTs for unmet needs: no FDA cleared/approved IVD available Public Health Evidence for FDA Oversight of LDTs 20 Case Stu dies

• November, 2015 – FDA presented 20 case studies of LDTs that it believes may have caused or could cause harm to patients.

http://www.fda.gov/downloads/AboutFDA/ReportsManualsForms/Reports/UCM472777.pdf Future Of LDT Oversight Still Uncertain CAP and AMP Counter-ppproposals

AACC recently released a position statement on CLIA calling for CMS, not FDA, to be responsible for LDT oversight .

Association for Molecular Pathology (AMP) and the College of American Pathologists (CAP) , are advocating an alternate approach to oversight of LDTs that would build on the existing CLIA framework.

FDA is moving ahead with plans to issue a final guidance in 2016, said Eric Pahon, an FDA spokesperson. Socioeconomic Impact of Inaccurate HER2 IHC Testing of FDA-approved IVDs compared with Lab-developed IVDs for HER2

• Study analyzed HER2 testing accuracy (False -/+ rates) using data from the Nordic Immunohistochemistry Quality Control (NordiQC) HER2 IHC program

• Results were used in an economic breast cancer treatment model to estimate direct costs, loss of survival, productivity benefit and quality-adjusted life-years (QALYs).

Vyberg M et al. Immunohistochemical expression of HER2 in breast cancer: socioeconomic impact of inaccurate tests. BMC Health Services Research (2015) 15:352 Socioeconomic Impact of Inaccurate HER2 IHC Testing of Breast Cancer Study methodology

• Cost calculator/modeling tool – Consequences of false-positive/negative HER2 results – Patient outcomes based on 232,340 patients with invasive breast cancer in USA 2013 – Direct medical costs • Societal perspective adopted using US costs – Life expectancy • Survival calculations: NSABP study B31, North Central Cancer Treatment Grouppg trial N9831 studies (EBC), H0648g phase3 study (MBC) – Quality of life: Quality- adjusted Life Years (QALYs) – Loss of productivity - based on QALYs

Vyberg M et al. Immunohistochemical expression of HER2 in breast cancer: socioeconomic impact of inaccurate tests. BMC Health Services Research (2015) 15:352 Socioeconomic Impact of Inaccurate HER2 IHC Testing of Breast Cancer Examples of Optimal Staining and False Negatives/Positives

Case 1 Case 2 Case 3 Case 4

NordiQC Assessment: Optimal Staining Lab HER2 3+ HER2 2+ HER2 1+ HER2 0 1 Positive Equivocal Negative Negative

NordiQC Assessment: Poor Staining – Too Weak Lab 2 False Negative

NordiQC Assessment: Poor Staining – Overstained Lab False 3 Positive

Vyberg M et al. Immunohistochemical expression of HER2 in breast cancer: socioeconomic impact of inaccurate tests. BMC Health Services Research (2015) 15:352 Socioeconomic Impact of Inaccurate HER2 IHC Testing LDTs Associated with Higher False Negative and False Positive Ra tes w ith Impac t to Recurrence, Surv iva l an d QALYs Missed gain in life expectancy 500 False Negative and False Positive Rates for IHC testing ( NoodQCrdiQC) 400 273 yrs LDT HER2 IHC FDA-Approved HER2 300 226 yrs Test IHC Test 200 False Negative 25% 11% 100

False Positive 5% 0% 0 EBC MBC

R/idtRecurrence/progressions due to FDA-Approved IVD Lab developed IVD incorrect test results QALYs lost 500 500 400 400 300 300 217 193 yrs 200 200 109 100 100 0 0 EBC MBC EBC MBC FDA-Approved IVD Lab developed IVD FDA-Approved IVD Lab developed IVD

Vyberg M et al. Immunohistochemical expression of HER2 in breast cancer: socioeconomic impact of inaccurate tests. BMC Health Services Research (2015) 15:352 Economic Costs of Inaccurate HER2 IHC Testing $46M in additional costs associated with LDT

Additional Cost Cost US$ FDA-approved IVD Lab-developed IVD Associated with LDT ancer CC Direct cost/patient 364 1394 1030 Total direct costs 14,447,666 55,377,720 40,930,054 Cost of lost ge Breast ge Breast

aa 83 190 107 prodii/iductivity/patient Total cost of lost 3,301,263 7,546,231 4,244,968 Early St productivity

Additional Cost Cost US$ FDA-approved IVD Lab-developed IVD Associated with LDT

t Cancer Direct cost/patient 176 1228 1052 ss Total direct costs 859,446 5,992,471 5,133,025 Cost of lost 52 120 68 productivity/patient static Brea aa Total cost of lost 255,594 586,221 330,627 Met productivity

Vyberg M et al. Immunohistochemical expression of HER2 in breast cancer: socioeconomic impact of inaccurate tests. BMC Health Services Research (2015) 15:352 Economic Costs of Inaccurate HER2 IHC Testing IVDs more expensive initially but usage results in net savings to healthcare system

• More expensive initial outlay for approved vs . laboratory -developed IVD tests (LDTs) – $45 vs $10 assumed in current study

• Additional direct costs resulting from false-positive and false- negative test results are significantly higher for LDTs

• “Use of approved rather than laboratory-developed IVD tests could result in a savings of approximately $46 million.” – “Every $1 save d by la bs by us ing c heaper reagents could potentially result in approximately $6 additional costs to the healthcare system” – Overall cost of using a LDT is 2.5x greater than using an approved IVD

Vyberg M et al. Immunohistochemical expression of HER2 in breast cancer: socioeconomic impact of inaccurate tests. BMC Health Services Research (2015) 15:352 FDA Regulation of Next-Generation Sequencing (NGS) February 25th, 2016 Public Workshop

http://www.fda.gov/downloads/MedicalDevices/NewsEvents/WorkshopsConferen ces/UCM488271.pdf FDA Regulation of Next-Generation Sequencing (NGS) February 25th, 2016 Public Workshop

http://www.fda.gov/downloads/MedicalDevices/NewsEvents/WorkshopsConferences/UCM488271.pdf FDA Regulation of Next-Generation Sequencing (NGS) February 25th, 2016 Public Workshop

http://www.fda.gov/downloads/MedicalDevices/NewsEvents/WorkshopsConferences/UCM488271.pdf FDA Regulation of Next-Generation Sequencing (NGS) February 25th, 2016 Public Workshop

• Potential intended use statement with table listing variants with established use as companion diagnostics.

http://www.fda.gov/downloads/MedicalDevices/NewsEvents/WorkshopsConferences/UCM488271.pdf FDA Regulation of Next-Generation Sequencing (NGS) February 25th, 2016 Public Workshop

• Potential analytical results table for variants where safe and effective use has not been established for selecting therapy

http://www.fda.gov/downloads/MedicalDevices/NewsEvents/WorkshopsConferences/UCM488271.pdf FDA Regulation of Next-Generation Sequencing (NGS) JyJuly 8, 2016 Dra ft Guidance Documents

• Adaptive approach to regulating NGS-based tests is part of the FDA’s engagement in the Precision Medicine Initiative (PMI )

• For rare hereditary diseases (not somatic tumor testing), and addresses the potential for using FDA-recognized standards to demonstrate analytical validity

• Approach where test developers may rely on clinical evidence from FDA- recogpggnized public genome databases to support clinical claims

http://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/UCM509838.pdf PHC Challenge #4: Diagnostics are Undervalued Diaggffnostic tests inform 60% of clinical decisions, but make up < 2% of healthcare spend

Source: DxInsights White Paper January 2012 Personalized Healthcare – Payer Perspective P’CPayer’s Concerns

• Cost of testinggy many individuals to identify the few who could benefit

• Uncertainty regarding clinical- and cost-effectiveness – particularly linkage of diagnostic tests to health outcomes

• Coding issues: Code stacking versus test-specific codes reflective of value

© 2015, Genentech / Proprietary information — Please do not copy, distribute or use without prior written consent 62 62 PHC Coding Challenges and Opportunities Code stacking vs . test -specific codes g odes nn cc ode stacki vidual CPT CPT vidual CC ii Ind

cc Codes Specifi

63 63 Coverage of Companion Diagnostics Reimbursement landscapppe must evolve to keep pace with the increasingly complex PHC/CDx environment

Reimbursement Coding

• Medicare reimbursement of • Most complex molecular tests companion diagnostics is have no specific CPT codes2 reported to be limited and highly variable1 • Traditional “stacked coding” – Drugs may be reimbursed while does not describe actual assay their CDx is not – Documentation of CDx prior to • MolDx system: Instituted in prescribing is rarely required 2011 by Palmetto, a Medicare Part B contractor, to identify and • Value-based reimbursement establish coverage and has been proposed to reimbursement for molecular incentivize development and use diagnostic tests3 of tests that improve patient outcomes

1. Cohen JP, et al. J Pers Med. 2014 Apr 4;4(2):163-75. 2. Quinn B., Hoag F. Current Issues and Options: Coverage and Reimbursement for Molecular Diagnostics. July 2008. Available at: http://aspe.hhs.gov/health/reports/2010/CovReimCMD/index.shtml. Accessed April 13, 2015 3. Palmetto GBA – MolDx. Available at: http://www.palmettogba.com/palmetto/MolDX.nsf/DocsCat/MolDx%20Website~MolDx~Browse%20By%20Topic~Frequently%2 0Asked%20Questions~8N3ELL4072?open&navmenu=Browse^By^Topic||||. Accessed April 27, 2015. Palmetto GBA Molecular Diagnostic Program (MolDX) Test-specific Z-Code identifiers

• Clinical Laboratory Fee Schedule pricing methodology does not account for the unique characteristics of molecular diagnostic tests (MDTs) and LDTs

• Palmetto GBA’ s MolDX Program strives to create a consistent approach to coverage and pricing decisions for MDTs and LDTs.

• MolDX Program requires laboratories to obtain a test-specific identifier – i.e., a Z- Code Identifier – that is unique to the laboratory’s specific test.

• When repor te d in con junc tion w ith th e appropriate CPT/HCPCS code, the Z- Code Identifier allows payers to determine the exact test that has been perfdformed, facilit ati ng th e process of making pricing and/or coverage determinations http://palmettogba.com/Palmetto/moldx.Nsf/files/MolDX_Manual.pdf/$Fi le/MolDX_Manual.pdf Patient Selection Strategy is Key in PHC Era CDx Cut-Offs Impact Payor and Regulatory Acceptance omers atients CC pp All- # of 0% 50% 100%

Companion Diagnostic Cut-Off

IiiIncreasing patient popu lilation Increasing probability of regulatory approval and payor coverage

Even if health auth oriti es approve an all-comer lbllabel payors may restitrict tt to Dx-seltdlected population

66 Patient Selection Strategy is Key in PHC Era CDx CtCut-Offs Impac t Payor andRd Regu lat ory Accep tance Reimbursement and Regulatory Policy Imperatives Re-balancing the value equation & bringing certainty

Challenges Proposed Actions Reimbursement currently based on Create new reimbursement system that activity, not value rewards value

Lack of harmonization of standards for Create clear, unified clinical utility proof demonstrating clinical utility standards to capture enhanced value

UiUncertainty regardi dilng regulatory CihhilCreate certainty through timely oversight for lab developed tests regulatory framework and transparent implementation Lack of published outcomes and health Cross industry research groups econ data regarding impact of Dx

Not enougggh resources or new regulatory Create a new FDA Center for Advanced expertise relating to diagnostics Diagnostics Evaluation and Review (CADER) The future of personalized healthcare Match driver mutations to targeted therapy drugs

Cancer Driver A Cancer Driver C

Drug A Drug C

Cancer Driver D Cance r Drive r B

Drug B Drug D in the headlines 2013 Immunotherapy in the mass media NYkTiNew York Times

http://www.nytimes.com/2016/07/31/health/harnessing-the-immune-system-to-fight-cancer.html Metastatic Response to Before Ipilimumab After Ipilimumab 04/22/11 08/05/11

http://www.slideshare.net/roblyngold/community-oncology-clinical-debates-advanced-melanoma Case by Antoni Ribas, MD, PhD. Unique Kinetics of Response in Patients Treated With Ipilimumab Week 12: Swelling Screening and Progression Week 12: Improved

Week 16: Continued Week 72: Complete Week 108: Complete Improvement Remission Remission

Images courtesy of Jedd D. Wolchok, MD. http://www.slideshare.net/roblyngold/community-oncology-clinical-debates-advanced-melanoma Immunotherapy in the mass media NYkTiNew York Times

http://www.nytimes.com/2016/08/01/health/immunotherapy-offers-hope-to-a-cancer-patient-but-no-certainty.html?_r=0 Immunotherapy Clinical Effect JGtilphptitJason Greenstein, patient

http://www.nytimes.com/2016/08/01/health/immunotherapy-offers-hope-to-a-cancer-patient-but-no-certainty.html?_r=0 Theoretical immunotherapy advantages Adaptability, Broad Activity, Combinations

Immune adappytability and memory offers potential for long-term survival

Targeting the , not the tumor, Unique MOA offers Potential to Improve offers potential for opportunity for Clinical Outcome activity across multiple combination tumor types The cancer-immunity cycle How the immune system fights cancer

Trafficking of activated T cells 4 (cytotoxic T [CTLs]) to the 3 Priming and activation of the response 5 Infiltration of CTLs into tumors Active T cell Active T cell

2 Presentation of tumor to Activation/recruitment TUMOR MICROENVIRONMENT T cells of immune cells 6 Recognition and Cancer-cell recognition binding of CTLs and initiation of cell killing to cancer cells

Dendritic cell Antigens Apoptotic tumor cell

7 Killing of cancer cells 1 Release of tumor antigens

Tumor cell

Chen DS, Mellman I. Immunity. 2013 Regulation of T cell activation Balancing activating and inhibitory signals

Activating interactions Inhibitory interactions

APC/tumor APC/tumor

B7.1 CD28 CTLA-4 B7.2

B7.2 B7. 1 OX40 PD-1 OX40L PD-L2 GITR TcellT cell GITRL PD-L1 CD137 B7.1 CD137L CD27 HVEM BTLA CD70 LAG-3 TCR MHC MHC

Pardoll. Nat Rev Cancer 2012 Net balance of immune activity and regulation determines tumor fate Anticancer immune response vs. immunosuppressive cells

Anti-tumor immunity Intratumoral immunosuppression CTLs IFN TGF- Treg Th1 TNF- IL-10 Th2 cells pTh17 IL-2 IDO MDSCs NK cells GM-CSF PGE2 TAMs (M2) Net effect: DCs IL-12 CTLA-4 Some B cells tumor control Type I IFN PD-1/PD-L1 Chemokines IL-4/IL-13 Net effect: tumor growth

Tumor Tumor Tumor immunity

Pitt et al. Annals of Oncology 2016 Immune checkpoints Central and peripheral regulatory mechanisms Blood vessel Effector Phase T cell activation

Tumor cells

APC T cell T cell

Peripheral tissue Lymph node

APC T cell Tumor MHC TCR T cell TCR MHC 1st Signal1st signal Activation B7 CD28 +

2nd signal PD-1 PD-L1 2nd B7 Signal

CTLA-4

Adapted from Kyi C and Postow M. FEBS Letters 2014; 588:368-376 Targeting immune checkpoints Inhibit the inhibitory regulatory mechanisms Blood vessel Effector Phase T cell activation

Tumor cells

APC T cell T cell

Peripheral tissue Lymph node

APC T cell Tumor MHC TCR T cell TCR MHC 1st Signal1st signal Activation B7 CD28 +

2nd signal Inhibition 2nd PD-1 PD-L1 B7 Inhibition Signal

CTLA-4

Ipilimumab (BMS) (BMS) (Roche) (Merck) Durvolumab (AZ) Adapted from Kyi C and Postow M. FEBS Letters 2014; 588:368-376 Immunotherapy FDA Approvals Checkpoint Inhibitors in Multiple Indications Drug Target Tumor(s) Approval History Diagnostic

Yervoy March 25, 2011: unresectable or metastatic melanoma. CTLA-4 Melanoma None (ipilimumab) Oct 28 2015: adjuvant therapy for stage III melanoma

Dec 22, 2014: Advanced melanoma nd March 4, 2015: Advanced squamous NSCLC 2 line Complementary Melanoma nd Oct 9, 2015: Advanced (metastatic) NSCLC 2 line (PD- Diagnostic Opdivo Lung L1 comp. Dx) Dako PD-L1 IHC 28-8 PD-1 Nov 23, 2015: Me tas ta tic rena l ce ll carc inoma (nilivoluma b) RlRenal pharmDx Lymphoma May 31, 2016: Classical that has relapsed after autologous hematopoietic (NSCLC, melanoma) transplantation/.

Opdivo (nilivoluma b) + Oct 1, 2015: BRAF V600E wt unresectable or metastatic PD-1 + CTLA-4 Melanoma None Yervoy melanoma (ipilimumab)

Sep 4, 2014: Advanced Melanoma nd Oct 2, 2015: Advanced (metastatic) NSCLC 2 line (PD- Companion Diagnostic Melanoma L1 CDx) Dako PD-L1 IHC 22C3 Keytruda Aug 5, 2016: Recurrent/metastatic head and neck PD-1 Lung (1st line) pharmDx (pembrolizumab) squamous cell ca Head & Neck Oct 24, 2016: Metastatic non-small-cell lung cancer 1st (NSCLC) line, PD-L1 > 50% TPS with no EGFR or ALK genomic tumor aberrations.

May 18, 2016: Locally advanced/metastatic urothelial Complementary nd Diagnostic Tecentriq Bladder carcinoma 2 line PD-L1 Oct 18, 2016: Metastatic NSCLC w/progression after VENTANA PD-L1 (atezolizumab) Lung platinum-based chemotherapy and EGFR/ALK targeted (SP142) Assay therapy (for tumors with EGFR/ALK gene abnormalities). (Bladder, NSCLC) Companion vs. Complementary Diagnostics Essential vs. Guidinggf information

Companion Diagnostic Complementary Diagnostic

• FDA definition: • The term "complementary diagnostic" was introduced in June – "in vitro diagnostic device or an imaging tool that 2015 by Elizabeth Mansfield, Deputy Director for Personalized provides information that is essential for the safe and Medicine at FDA, but has yet to be officially defined. effective use of a corresponding therapeutic product." – A complementary test isn't required for the safe and effective use of a drug; it can be used to guide • PD-L1 drug and diagnostic example: treatment strategies and identify patients likely to derive the most benefit from a drug.

Drug Label: KEYTRUDA® (pembrolizumab) • PD-L1 drug and diagnostic example: “KEYTRUDA is a programmed death receptor-1 (PD-1)-blocking Drug Label: TECENTRIQ (atezolizumab) indicated for the treatment of…” “…patients with metastatic NSCLC whose tumors have high PD-L1 “TECENTRIQ is indicated for the treatment of patients with expression [(Tumor Proportion Score (TPS) ≥50%)] as metastatic non-small cell lung cancer (NSCLC) who have disease determined by an FDA-approved test…” progression during or following platinum-containing chemotherapy.” No reference to diagnostic

Dx Label: Dako PD-L1 IHC 22C3 pharmDx Dx Label: VENTANA PD-L1 (SP142) Assay “PD-L1 IHC 22C3 pharmDx is indicated as an aid in identifying “PD-L1 express ion in ≥ 50% TC or ≥ 10% IC determ ine d by NSCLC patients for treatment with KEYTRUDA® VENTANA PD-L1 (SP142) Assay in NSCLC tissue may be (pembrolizumab)” associated with enhanced overall survival from TECENTRIQ (atezolizumab).” “PD-L1 expression in ≥ 5% IC determined by VENTANA PD-L1 (SP142) Assay in urothelial carcinoma tissue is associated with increased objective response rate (ORR) in a non-randomized study of TECENTRIQ® (atezolizumab).” Kaplan-Meier Survival Curves Interpretation

100% Survival • Graphical way to compare survival of two patient groups

• Overall survival vs. progression- filfree survival

• All subjects within the group begin the analysis at the same point

• All are surviving until one of two things happen: – 1) patient dies or progresses – 2) patient is censored (e.g. subject drops out, is lost to follow-up, or required data is not available.)

A PRACTICAL GUIDE TO UNDERSTANDING KAPLAN-MEIER CURVES Otolaryngol Head Neck Surg. 2010 September ; 143(3): 331–336. Immunotherapy clinical efficacy Ipilimumab FDA phase III registration study data

Ipilimumab

alone Ipi + Gp100 ( vaccine)

Durable responses (4+yrs) Gp100 alone in 20% of patients

Hodi et al. NEJM 2010 Non-small-cell Lung Cancer Survival on Chemotherapy Median survival 8 months

/ plus cisplatin/carboplatin plus a

Does Type of Tumor Histology Impact Survival among Patients with Stage IIIB/IV Non-Small Cell Lung CancerTreated with First-Line Doublet Chemotherapy? Chemotherapy Research and Practice vol. 2010 20% 10-year survival in advanced melanoma Pooled analyyfsis of 1,861 patients treated with ipilimumab

87 Schadendorf et al. JCO 2015 PD-L1 Dampens Immune Response by Deactivating T cells

• PD-L1 is normally exppyressed by a subset of PD-1 PD-L1 T cellcellT • PD-L1 can be induced as part of a physiological process to down-modulate B7.1 Tumor ongoing host immune responses in cell B7.1 PD-1 peripheral tissue

• PD-L1 can be induced on activated PD-L1 PD-L2 lymphocytes (T, B and NK), endothelial cells and other non-malignant cell types

Macrophage • Tumor cells and associated stromal cells can also express PD-L1, turning off T effector cells

Chen et al. Clin Cancer Res 2012 Brown et al. J Immunol 2003 Park et al. Blood. 2010 Nivolumab 2nd Line Squamous NSCLC Chec kma te 017 t ri al Nivolumab 2nd Line Squamous NSCLC Chec kma te 017 t ri al Immunotherapy in metastatic Atezolizumab PD-L1 inhibition Immunotherapy in lung cancer Pembrolizumab PD-1 Inhibition – KEYNOTE-024 1st Line NSCLC Trial Atezolizumab 2nd Line Non-small-cell Cancer POPLAR phase 2 trial

Fehrenbacher et al. Lancet Vol387 April 30, 2016 PD-L1 Immunohistochemistry Staining can be observed in tumor cells , immune cells or both

Tumor cells (TCs)

Immune cells Tumor and immune cells (ICs) (TCs and ICs) Response rate by PD-L1 status Higgpher response rate in PD-L1-ppppositive population

Nivolumab PembrolizumabAtezolizumab 80 ITT PD-L1+ PD-L1- 60

(%) 40 RR OR

20

0

Non-sq.=non-squamous; sq.=squamous 1. Weber et al . Lancet 2015; 2. Robert et al. Lancet 2015; 3. Larkin et al. N Engl J Med 2015; 4. Borghaei et al. N Engl J Med2d 2015 5. Brahmer et al. N Engl J Med 2015; 6. Antonia et al. ASCO 2015; 7. Motzer et al. J Clin Oncol 2015; 8. Le et al. ASCO GI 2016 9. Kefford et al. ASCO 2014; 10. Garon et al. N Engl J Med 2015; 11. Plimack et al. ASCO 2015; 12. Vansteenkiste et al. ECC 2015 13. Rosenberg et al. Lancet 2016; 14. McDermott et al. J Clin Oncol 2015; 15. Rizvi et al. ASCO 2015; 16. Segal et al. ASCO 2015 17. Gulley et al. ASCO 2015; 18. Apolo et al. ASCO GU 2016; 19. Dirix et al. SABCS 2015; 20. Chung et al. ASCO GI 2016 Intra-tumoral PD-L1 expression and response to PD-1/PD-L1 blockade Higher response rate in PD-L1-positive population

N= 42 44 34 94 30 53 113 129 64 55 411 Response rates Unselected 21% 32% 29% 22% 23% 23% 40% 19% 26% 18% 40%

PD-L1 + 36% 67% 44% 39% 27% 46% 49% 37% 43% 46% 49% PD-L1 - 0% 19% 17% 13% 20% 15% 13% 11% 11% 11% 13%

Adapted from Margaret Callahan, ASCO 2014 can evade immune destruction Presence, type and activity of immune cells are key

CD8 CD8

Immunologic ignorance Excluded infiltrate

CD8 PD-L1

T cells present but.. …unable to act The tumor immunity continuum Immune oasis vs. immune desert

Inflamed Non-inflamed

Pre-existing immunity Excluded infiltrate Immunologically ignorant

Mutational Load

Proliferating TILs Angiogenesis CD8 T cells/IFN Tumors/ PD-L1 Reactive stroma Low Class I MDSCs

Respond favorably to Convert to inflamed phenotype with checkpoint inhibition combinations Hegde, et al. Clin Cancer Res 2016 Mutational burden hypothesis Higgpher mutational load increases probability of immunogenic neo-antigens

The prevalence of somatic mutations across human cancer types .

 Altered proteins contain new for immune recognition, providing a common denominator for immunotherapy

LB Alexandrov et al. Nature 000, 1-7 (2013) doi:10.1038/nature12477 Role of targeted therapy in the era of immunotherapy Additive, synergistic, or independent?

Clinical trials combining inhibitors and immunotherapy

Transl Lung Cancer Res. 2015 Dec;4(6):752-5

Seminars in Immunology 28 (2016) 73–80 Combining immunotherapy with other therapies Which combinations for which patients?

GITR TCE BiSpe mAbs CD137 IDOi

OX40 Herpes oncolytic KIR virus

CTLA4 PD-1/PD-L1 oncoltilytic virus Chemotherapy

Radiotherapy TLR ago

TKI STING ago RIG ago Combination immuno-therapies in NSCLC Enhanced efficacy with increasing levels of PD -L1 expression

100 92 Opdivo 3 Q2W + Yervoy 1 Q6/12W (pooled) Opdivo 3 Q2W 80 78

64 57 60 54 50 43 44 40

ORR (%) 40 31 28 23 18 20 14

0 n 77All 52 17 <1% 14 44≥1% 32 35≥5% 26 28≥10% 20 18≥25% 18 13≥50% 12 PD-L1 expression All <1% ≥1% ≥5% ≥10% ≥25% ≥50%

Hellmann et al. Presented at ASCO 2016 Immunotherapy in oncology Challenges

• Increase proportion of durable responders

• Predict response to specific drugs

• Understand role of immune agents in context of targeted therapies and traditional chemotherapy

• Manage toxicity

Mellman et al. Nature 2011 Immunotherapy side effects Autoimmune toxicity c/w mechanism of action

Mellman et al. Nature 2011 Personalized Healthcare in Oncology

Past

Present

Future How can we continue to improve survival rates?

Illustrative KM curve for overall survival cent Survival rr Pe

Targeted Therapy Chemotherapy

Time Pre-1990s 1990s+

Chemotherapy Targeted Agents Immunotherapy represents one of the most significant advances in the

Illustrative KM curve for overall survival cent Survival rr

Pe Immunotherapy

Targeted Therapy Chemotherapy

Time Pre-1990s 1990s+ 2010+

Chemotherapy Targeted First “Next Gen” Agents Immunotherapy Immunotherapy represents one of the most significant advances in the treatment of cancer

Illustrative KM curve for overall survival

Combination Immunotherapy Personalized Immunotherapy cent Survival rr Next Generation Pe Immunotherapy Targeted Therapy Chemotherapy

Time Pre-1990s 1990s+ 2010+ 2015+ 2015+

Chemotherapy Targeted First “Next Gen” Personalized Combination Agents Immunotherapy Immunotherapy Immunotherapy Additional ppfillar of cancer care

AACR Cancer Progress Report 2015. http://cancerprogressreport.org/2015/Documents/AACR_CPR2015.pdf American Association for Cancer Research. AACR Cancer Progress Report 2015. Clin Cancer Res 2015;21(Supplement 1):SI-S128 Personalized healthcare next Comprehensive tumor profiling drives therapy combinations

Targeted Therapy

Tumor Heterogeneity

Immune Therapy Tumor Driver and Immune Resistance Mechanisms Checkpoint Status

Immune Therapy Questions and answers Doing now what patients need next MMR status and pembrolizumab response Mismatch-reppfyair deficiency correlates with improved response and survival

Le et al. N Engl J Med 372;26 2015 MMR status and pembrolizumab response Mismatch-reppfyair deficiency correlates with improved response and survival MMR status and pembrolizumab response Mismatch-reppfyair deficiency correlates with improved response and survival