Fabrication and Characterization of Panobinostat Loaded PLA-PEG Nanoparticles

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Shruti Dharmaraj

A Master’s Thesis Presented in Partial Fulfillment of the Requirements for the Degree Master of Science

Approved April 2019 by the Graduate Supervisory Committee:

Rachael Sirianni; co-chair Sarah Stabenfeldt; co-chair Brent Vernon

ARIZONA STATE UNIVERSITY May 2019 ABSTRACT Medulloblastoma is the most common malignant pediatric brain cancer and is classified into four different subgroups based on genetic profiling: sonic hedgehog (SHH),

WNT, Group 3 and 4. Changes in gene expression often alter the progression and development of cancers. One way to control gene expression is through the acetylation and deacetylation of histones. More specifically in medulloblastoma SHH and Group 3, there is an increased deacetylation, and histone deacetylase inhibitors (HDACi) can be used to target this change. Not only can HDACi target increases in deacetylation, they are also known to induce cell cycle arrest and apoptosis. The combination of these factors has made

HDACi a promising cancer therapeutic. Panobinostat, a hydrophobic, small molecule

HDACi was recently identified as a potent molecule of interest for the treatment of medulloblastoma. Furthermore, panobinostat has already been FDA approved for treatment in multiple myeloma and is being explored in clinical trials against various solid tumors. The laboratory is interested in developing strategies to encapsulate panobinostat within nanoparticles composed of the biodegradable and biocompatible polymer poly(lactic acid)-poly(ethylene glycol) (PLA-PEG). Nanoparticles are formed by single emulsion, a process in which hydrophobic drugs can be trapped within the hydrophobic nanoparticle core. The goal was to determine if the molecular weight of the hydrophobic portion of the polymer, PLA, has an impact on loading of panobinostat in PLA-PEG nanoparticles. Nanoparticles formulated with PLA of varying molecular weight were characterized for loading, size, zeta potential, controlled release, and in vivo tolerability.

The results of this work demonstrate that panobinostat loaded nanoparticles are optimally formulated with a 20:5kDa PLA-PEG, enabling loading of ~3.2 % w/w panobinostat within nanoparticles possessing an average diameter of 102 nm and surface charge of -8.04 mV.

Panobinostat was released from nanoparticles in a potentially biphasic fashion over 72 hours. Nanoparticles were well tolerated by intrathecal injection, although a cell culture assay suggesting reduced bioactivity of encapsulated drug warrants further study. These experiments demonstrate that the molecular weight of PLA influences loading of panobinostat into PLA-PEG nanoparticles and provide basic characterization of nanoparticle properties to enable future in vivo evaluation.

Dedication

First and foremost, I would like to thank my family for their constant encouragement and enthusiasm. Not only are you interested about my time in Houston, but also about my time in the lab including all the experiments and projects I work on. Mom and Dad, while you may not understand all the technicalities of my work, your constant excitement reminds me of why I chose biomedical engineering when I knew nothing about the subject and it makes me excited to continue working even when it gets stressful.

iii

Acknowledgments

Thank you to Dr. Rachael Sirianni for mentoring me over the last two years and providing me the opportunity to continue this work in Houston. I am ready for the work we will have moving forward!

Thank you to Dr. Sarah Stabenfeldt, who 4 years ago took a chance on a student from another university to work in her lab for the summer. I am thankful for your continued support for my career goals and my research.

TABLE OF CONTENTS

CHAPTER Page

1. INTRODUCTION ...... 1

2. MATERIALS AND METHODS ...... 5

2.1 MATERIALS ...... 5

2.2 NANOPARTICLE FABRICATION ...... 5

2.3 NANOPARTICLE CHARACTERIZATION ...... 6

2.3.1 Drug Loading ...... 6

2.3.2 Size and Zeta Potential...... 6

2.4 IN-VITRO STUDY ...... 7

2.4.1 Cell Culture ...... 7

2.4.2 Measurement of Panobinostat Activity ...... 7

2.5 IN-VIVO TOLERABILITY...... 8

2.6 STATISTICAL ANALYSIS ...... 9

3. RESULTS ...... 10

3.1 NANOPARTICLE LOADING AND CHARACTERIZATION ...... 10

3.2 RELEASE CHARACTERISTICS ...... 14

3.3 IN-VITRO PANOBINOSTAT ACTIVITY ...... 15

3.4 IN-VIVO TOLERABILITY ...... 16

4. DISCUSSION ...... 17

5. REFERENCES ...... 22

1. INTRODUCTION

Medulloblastoma is the most common malignant pediatric brain tumor with a peak diagnosis between the ages of six and eight years old. Standard treatment includes maximum safe resection and subsequent radiation and chemotherapy. Although the overall

5- year survival is approximately 80%, the neuroendocrine, neurological and psychological damage from the aggressive treatment leave patients with long-term health complications.

Thus, researchers and clinicians are focused on finding a treatment that can reduce or eliminate these toxicities while improving the overall survival and quality of life. (30,40).

At the molecular level, medulloblastoma is classified into four subtypes: WNT, sonic hedgehog (SHH), Group 3 and Group 4. Each of these subtypes are associated with distinct genetic aberrations (29). Deregulated expression of genes is associated with development of tumors due to impaired control of differentiation and the cell cycle. One of controlling expression is through the modifications of histones (37). One of the best characterized modifications, histone acetylation, is mediated by histone acetyltransferase (HAT) and histone deacetylases (HDAC). Increased deacetylation is known to play a role in SHH and group 3 subgroups of medulloblastoma, and histone deacetylase inhibitors (HDACi) have been used to target this change (4,29,33,39). Furthermore, HDACi are known to induce cell cycle arrest and apoptosis and sensitize tumor cells to radiation and chemotherapy

(29,44).

Although the approach of HDACi has shown preclinical and clinical efficacy for hematological cancers (27), their efficacy has largely been limited when applied to treating solid tumors (37). However, panobinostat, a hydrophobic HDACi, has be identified as a potential candidate against both hematological and solid tumors (6,14,31,42). Research

1 conducted at Sanford Burnham Prebys Medical Discovery Institute by Dr. Robert

Weschler-Reya showed in a high-throughput screen against medulloblastoma human and murine group 3 cells that panobinostat potently inhibited growth and was effective against all medulloblastoma subgroups. However, in a preclinical in-vivo study panobinostat did not significantly increase survival when tolerable doses of panobinostat were administered to mice with xenograft of diffuse pontine glioma (DIPG) (17). The inconsistency of panobinostat can possibly be attributed to poor delivery to solid tumors, which have complex and abnormal vasculature that limits drug perfusion (20).

However, using panobinostat as a therapy for intrathecal administration poses a few problems. Panobinostat is poorly soluble and thus delivery of the drug safely to the central nervous system is difficult. Currently there are two market products of panobinostat:

Farydak’s oral capsule and Midatech’s solubilized panobinostat through their nanoinclusion technology. While Farydak developed a delivery mechanism, severe diarrhea occurred in 25% of patients, and cardiac toxicities are associated with the drug

(1,4). Midatech Pharma developed MTX110, a formulation that solubilizes panobinostat with their proprietary nano-inclusion technology (2). This compound is currently being used in clinical trials to treat DIPG through convection enhanced delivery (9). While

MTX110 provides a means to solubilize panobinostat without toxic solvents, it does not fully address the problems of short drug half-life and high toxicity. Efforts are also underway to encapsulate panobinostat into nanoparticles. Choi et al. have been able to load

PLGA particles with panobinostat with the goal of treating T-cell leukemias (5).

Nanoparticles are known to tackle limitations of free drug (pharmacodynamic, release and toxicity issues) by providing the drug with a modifiable carrier. Free drug formulations

2 tend to have a short half-life, whereas nanoparticle-encapsulated formulations can maintain the drug concentration in the location of the tumors, effectively killing tumor cells (19,34).

Extended-release nanoparticles can be help overcome delivery limitations of freely administered drug by providing a mechanism to control the release of the encapsulated drug and target the tumor. Various carriers exist, however the most commonly used are biodegradable polyesters like PLGA and PLA. Polymeric nanoparticles provide several benefits, including customizable surface modifications for targeting and especially improved payload tolerability. For example, camptothecin-loaded PLGA has improved tolerability of camptothecin and improved survival of mice with orthotopic gliomas in mice compared to free camptothecin alone (18).

In addition to the polymer identity, the molecular weight of the polymer or material for carrier can affect the release mechanisms (11,13,16, 21, 24, 34, 37, 46). As reviewed in

Kamaly et al., molecular weight affects the degradation rate such that lower molecular weight polymers degrade more rapidly compared to higher molecular weight polymers.

Moreover, lower molecular weight polymers produce particles of smaller sizes, which can be relevant to biological processes, since smaller particles remain in circulation for longer

(20).

Nanoparticles may be loaded in two ways: first, the drug may enter the particle and be held inside the particle, or second, the drug may associate with the surface of the particle.

While prior studies in the lab showed that quisinostat, an HDACi, was maximally loaded into PLA-PEG nanoparticles via surface association (19), additional studies suggested that surface loading was not an effective fabrication strategy for producing panobinostat PLA-

PEG nanoparticles. We were therefore motivated to determine conditions under which panobinostat would load effectively into the core of nanoparticles.

In this study, we present an attempt to understand the factors that influence loading of

PLA-PEG nanoparticles with panobinostat. We hypothesized that increasing molecular weight of PLA would enhance loading of panobinostat into the core of the nanoparticle.

We further predicted that molecular weight and hydrodynamic size will be correlated, as previously described by Govender and Kamaly, and that size will increase as the molecular weight increases (15, 21).

2. MATERIALS AND METHODS 2.1 Materials

Panobinostat (LBH-589) was obtained from APExBIO (Houston, TX, USA). Poly(d, l-lactide)-b-methoxy poly(ethylene glycol) (PLA-mPEG) was purchased from

PolySciTech (West Lafayette, IN USA) with varying molecular weights (PEG: PLA;

~5000 : 14kDa, 16kDa, 18kDa, 20kDa, 35kDa). HyClone endotoxin free water (<0.005

EY/mL) was purchased from Fisher Scientific (Pittsburg, PA USA) and was used throughout the nanoparticle fabrication process. Dichloromethane (DCM), dimethyl sulfoxide (DMSO), sodium cholate and 10x phosphate buffered saline were purchased from Fisher Scientific (Pittsburg, PA USA). Dulbecco’s modified Eagle medium (DMEM), fetal bovine serum (FBS), 0.25% trypsin-EDTA were purchased from Gibco Invitrogen

(Carlsbad, CA, USA). Greiner T25 tissue culture flasks with filter cap and Costar 96-well assay plates were purchased from VWR International (Radnor, PA, USA). Beetle luciferin

(potassium salt) and CellTiter-Glo Luminescent Cell Viability Assay were purchased from

Promega (Madison, WI, UAS).

2.2 Nanoparticle Fabrication

Nanoparticles were fabricated using a modified single emulsion technique as previously reported (19,20,28). A schematic of the process is shown in Figure 1. PLA-PEG

(50 mg) was dissolved in DCM (2 mL). Panobinostat (5 mg) was dissolved in 300 μL of

DMSO and added to the polymer solution. The polymer and drug solution were then added dropwise to 4 mL of 1% (w/v) sodium cholate while vortexing. The solution was then probe sonicated 3 times in 10 second bursts at 40% amplification over ice. The resulting emulsion was added to 20 mL of 0.1% (w/v) of sodium cholate and then left gently stirring for 3 hours to allow the DCM to evaporate. After 3 hours the particles were washed and

5 concentrated using an Amicon Ultra-15 Centrifugal Filters (100 kDa cut-off) for 3, 20 min spins at 5000 RCF. Particles were aliquoted and lyophilized to determine their concentration and loading. The remaining particles were kept frozen at -80°C for storage.

Figure 1: Schematic of nanoparticle fabrication process

2.3 Nanoparticle Characterization

2.3.1 Drug Loading

Lyophilized particles were dissolved in DMSO to achieve a concentration of 5 mg/mL.

Samples were plated in triplicate (40 μL of particles and 10 μL of DMSO) on a clear, flat- bottomed 96 well plate. The standard curve was determined using 40 μL of blank particles in each well, adding 10 μL of panobinostat at known concentrations to achieve a total volume of 50 μL. A total of 9 concentrations were used in the range. The loading was then quantified by absorbance (290 nm) using BioTek reader and the Gen 5 software. The loading was calculated as the mass of panobinostat divided by the mass of polymer (w/w

%).

2.3.2 Size and Zeta Potential

The hydrodynamic size and zeta potential of the particles were measured using

NanoBrook 90Plus Zeta (Brookhaven Instruments, Holtsville, NY USA). Nanoparticles were suspended at a concentration of 1 mg/mL in sterile filtered 1 mM KCl.

2.3.3 Controlled Release

To determine the release profile of panobinostat, a protocol from Wang et al (43) was adapted. Nanoparticles were diluted to a concentration of 1 mg/mL and 400 μL was added to a 3.5 k MWCO Slide-A-Lyzer Dialysis cassette (Thermo Fisher Scientific, Waltham,

MA USA). The cassettes were then submerged in 4L of PBS maintained at 37 °C (pH 7) with gentle stirring. The PBS was refreshed after 6 hours, 12 hours and every 12 hours after. At each time point, samples (30 μL) were removed from the cassette. Samples were placed in a clear, flat bottomed 96 well plate and read by absorbance as described in 2.3.1.

2.4 In-vitro Study

2.4.1 Cell Culture

GL261 cells were grown in T25 tissue culture flasks in DMEM with 10% FBS at 37

°C and 5% CO2. To collect cells for passaging or counting, media was removed and replaced with 1 mL 0.25% trypsin-EDTA. The flask was tapped and shaken to help cells detach. To quench the trypsin-EDTA, 1 mL of media with 10% FBS was added. The cells were centrifuged at 800 RPM for 6 minutes and resuspended in 3 mL of media containing

10% FBS. The Cellometer mini (Nexcelom Bioscience, Lawrence, MA, USA) was used to count cells prior to in vitro experiments.

2.4.2 Measurement of Panobinostat Activity

GL261 cells were seeded on a 96-well clear-bottomed, white-walled plate with a density of 3000 cells/well in 100 μL of media. The cells were left to incubate and adhere to well for 4 hours prior to treatment. Each plate was treated with 10 μL/well of 17 serial dilutions (1:2) of panobinostat nanoparticles or free drug, which generated concentrations

7 in the wells between 0.5 mM and 8 μM. DMSO and drug empty nanoparticles were used as vehicle controls. PBS were used as the negative control. After 72-hour incubation, cell viability was determined using CellTiter-Glo. An IC50 value was calculated in GraphPad

Prism 8 (San Diego, CA USA) by a nonlinear fit of the log (inhibitor) vs. response function.

2.5 In-vivo Tolerability

All procedures and animal care practices were performed in accordance with the

University of Texas Health Science Center’s Institutional Animal Care and Use

Committee. To determine the maximum tolerated dose (MTD) of panobinostat nanoparticles, incremental doses were administered via intracisternal injection to

C57BL/6J mice. Mice were anesthetized with isoflurane during the duration of the surgery and mounted on a stereotactic frame (Kopf Instruments, Tujunga, CA, USA) using

HotHands (KOBAYASHI, Dalton, GA, USA) hand warmers to maintain temperature of mice.

Animals were given buprenorphine SR and bupivacaine subcutaneously for pain management. The animal’s head was shaved and sterilized with three alternating passes each of betadine and ethanol. An incision was made from middle of the head in rostral- caudal direction, 1 cm. Using soft tissue scissors and forceps, the membrane was removed that covers the skull and cerebellar regions. Using hemostats, muscles were retracted to expose the cisterna magna, and a Hamilton syringe loaded with 2 μL of nanoparticles at the required drug concentration was inserted into the cisterna magna at a depth of 1.5 mm.

After 1 minute, the syringe was pulled up to 1mm and the nanoparticles were injected over

2 minutes controlled using a syringe pump 11 elite nanomite (Harvard apparatus, Holliston,

MA, USA). One-minute post infusion, the syringe was removed, and the incision was closed using staples. Mice were placed in a clean cage post-surgery to wake up from

8 anesthesia and were observed for 3 hours post-surgery for any acute reaction to drug.

Weights were obtained daily for 3 days to determine tolerability of the drug. Euthanasia was performed if animals lost more than 15% post-surgery or if humane endpoints were reached. Humane endpoints include: significant motor deficits, reduced splay of limbs when animal is lifted, vocalization, and lethargy.

2.6 Statistical Analysis

Statistical analyses were performed with GraphPad Prism 8 software. The Pearson correlation coefficient was first measured to assess the strength of any possible relationships. Then a linear regression using least squares was conducted to determine if these relationships could be explained by a linear model. An unpaired two-tailed t-tests with Welch’s correction was utilized to determine significance of loading between particles made with different molecular weights. Significance thresholds used include p < 0.001

(***), p < 0.01 (**), and p < 0.05 (*).

3. RESULTS

The molecular weight values referenced in this report refer to the product labels provided by PolySciTech. However, there are differences in the molecular weight and weight number that the global product classification (GPC) standard testing reports (3).

The molecular weight reported for the PLA are based on the molecular numbers that the

GPC analysis provided. The 14kDa and 18kDa molecular weights are significantly different from their molecular number. The polymers with 20 kDa and 35kDa have molecular numbers closer than reported. Overall, the polydispersity for these polymers is also greater than 1.5, thus the weight average is near double the number average.

Table 1: Molecular weight and number are the GPC reported values for the PLA used to produce the various formulations of nanoparticles. Molecular Number Average Molecular Weight Average Molecular Weight (Da) Weight (Da) Weight (Da) 14,000 16640 30226 18,000 23644 66613 20,000 28427 43369 35,000 35808 65506

The following analysis between molecular weight, size, zeta and percent loading are based on the molecular number and molecular weight.

3.1 Nanoparticle Loading and Characterization

Diameters of nanoparticles ranged from 84 to 130 nm with the average polydispersity index among all batches and molecular weights being 0.11. The particles with the smallest size were made with 16,640:5000 Da PLA-PEG and the particles that were the largest was made out of 358080:5000 Da. There is a strong correlation between molecular weight and the hydrodynamic size with the Pearson’s correlation coefficient r= 0.89. Furthermore, the slope is significantly different than 0, with the adjusted R squared value of 0.78, meaning

10 that 78% of the variability in size can be described by the linear relationship (Figure 2A).

The residual plot in B further confirms that the linear relationship is a good model to describe the data as the residuals do not follow a pattern (Figure 2B).

Furthermore, it was predicted that there would be a correlation between molecular weight and percent loading. The particles made with 23644: 5000 Da PLA: PEG loaded the least, with an average loading of 0.42% w/w, and the particle with the molecular weight of 28427:5000 Da PLA: PEG with an average loading of 3.16%. Interestingly, the particle made with the lowest molecular weight (16,640:5000 Da PLA: PEG) had a significantly greater loading than the (23644: 5000 Da PLA: PEG) (Figure 3). Furthermore, there is a significant jump between 23644: 5000 Da PLA: PEG and 28427:5000 Da PLA: PEG

A B 15

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C D 5 2

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3 a

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Molecular Weight of PLA (Da) Molecular weight of PLA (Da)

Figure 2: (A) The relationship between molecular weight (Da) and hydrodynamic size (nm) with a Pearson’s coefficient r = 0.89, the line of best fit is represented on the graph with a slope of 0.002 (B) Represents the residuals from (A). (C) The relationship between molecular weight (Da) and percent loading (nm) with a Pearson’s coefficient of r = 0.75 (D) Represents the residuals from (C) 11

Figure 3: Particle A- 16640 Da PLA, Particle B- 23644 Da PLA, Particle C- 28427 Da PLA, Particle D- 35808 Da PLA. When treated as a categorical variable, we see that particle A load significantly more than particle B (p = 0.037 < 0.05), but significantly less than particle C and D (p = 0.00023 < 0.001), which were roughly equivalent in loading (p = 0.63 > 0.05).

Furthermore, the molecular weight and encapsulation efficiencies mirror the relationship between molecular weight and percent loading. The particles made with the lower molecular weights had a lower encapsulation efficiency while the particles made with the larger molecular weight PLA had a greater encapsulation efficiency (Table 2).

However, all encapsulation efficiencies were less than 50%. Thus, a significant portion of drug was not encapsulated and must have been lost during the fabrication process.

Table 2: Encapsulation efficiencies for particles of drug based on the molecular weight of the PLA.

Molecular Number Average Molecular Encapsulation Efficiency (%) Weight (Da) Weight (Da) 14,000 16640 9.38 18,000 23644 4.15 20,000 28427 31.6 35,000 35808 30.2

Surface charge governs how nanoparticles interact with cells and proteins. Thus, we assessed zeta potential of each nanoparticle formulation.

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Figure 4: (A) The Pearson’s Correlation Coefficient between molecular weight and zeta shows no positive or negative correlation (r= 0.28). (B) The Pearson’s Correlation Coefficient between loading and zeta potential shows no correlation (r= 0.26)

Zeta potential (mV) ranged between -4.3 and -8.9 mV. The particle made with 16,640:5000

Da PLA: PEG had the most negative potential (-8.8mV), and the particle made with

28427:5 Da PLA: PEG had the most neutral potential (-4.3mV). There is no linear correlation between molecular weight and zeta potential, as there is no significance in the slope from slope of 0 (p=0.57 > 0.05). Particles with molecular weights 16,640, 23644 and

35808 Da PLA had the most variability in the zeta potential between particle batches, with standard deviations of 3, 3.4, and 5 respectively. As zeta potential can be indicative of loading location, the relationship between to variables was also assessed. There is no strong correlation between loading and zeta potential r= 0.26 furthermore the slope is not significantly greater than 0 (p=0.07> 0.05).

The following sections will present the time-dependent release characteristics, in- vitro activity, and in-vivo tolerability of 20:5 kDa PLA-PEG encapsulated panobinostat particles. We chose to further investigate and characterize this particle because it

demonstrated the highest average loading in the earlier studies. Furthermore, the zeta

potential was less variable and the yield of these particles were more consistent.

3.2 Release Characteristics

The release of panobinostat from the particles was measured for a total of 72 hours.

During the 72-hour period, 88% of the loaded drug was released from the particles. The

release profile may be divided into three distinct phases. In the first period (period A),

which lasted 6 hours, there was a rapid release of 55% of the drug. In the second period

(period B), which occurred between 6 and 12, there was a slight plateau in the drug’s

release. Only a total of 59% of the drug was released by the end of period B, indicating that

only 4% of the drug had been released over these 6 hours. Over the next 60 hours which

comprised period C, the remaining 29% of the drug was released. During period C there

was initially a period where there was more rapid release of the drug than in period B, after

which the drug release plateaued. Thus, the release profile may be generally characterized

as biphasic, with a period of relative diminished release in between the two release phases.

This was seen in both experimental replicates, which were different batches of particles.

C 100

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Figure 5: 28427:5 kDa PLA-PEG encapsulated panobinostat reveals a biphasic release profile over the course of 72 hours to release a total of 88% of the encapsulated drug (n=2). 14

3.3 In-vitro Panobinostat activity

To determine if the activity of panobinostat had been maintained after encapsulation, a cell viability assay was conducted as described in 2.4.2. If activity is maintained the concentration drug to kill half the cells would be equivalent or less for particles compared to free drug. Equivalent concentrations of drug were tested starting at 0.5mM. Blank particles were used for no drug. The nanoparticle IC50 was 177 nM. However, the free drug appeared to kill a significant portion of the cells at all concentrations tested due to an excess of DMSO solvent, and an accurate IC50 could not be determined.

Figure 6: n=3 In vitro panobinostat-loaded nanoparticle efficacy against GL261. Three different batches of nanoparticles were used as a treatment. 100% cell survival is based on the negative control (PBS) and 0% cell survival is based on the blank particle control.

Between the treatments (different batches of particles) are different and thus leading to the large standard deviation. After determining the in-vitro toxicity of the particles, the next step was to determine the tolerability of the particles after an intrathecal injection.

3.4 In-vivo tolerability

Panobinostat from the nanoparticles was observed to kill GL261 cells, therefore in- vivo tolerability was investigated. The highest dose administered to the mice via cisterna magna injection, is 20 ug equivalent to the highest dose in the in vitro study. Overall within the first 3 days, the mice regained weight to pre-surgical weight. However, mouse 3 given

4.6 ug took more time to regain weight. Initial weight loss is due to surgery.

15 0

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Figure 7: Maximum tolerated dose study on C576J black mice, with intracisternal injection. A loss of more than 12% indicates low tolerability. None of the mice lost more than 12% of body weight. Within 3 days post-surgery a majority of the animals (excluding M3) began to regain weight.

4. DISCUSSION

As the interest in developing HDACi- based therapeutics for treating cancer growing, improving delivery is an important step in enhancing efficacy, reducing toxicities, and developing targeted strategies for cancer treatment. Treating solid tumors with free drug formations have been challenging due to the complex vasculature and hindrance from extracellular matrix. Nanoparticle formulations provide a promising avenue forward to deliver precise doses of a drug to its desired location. To achieve nanoparticle delivery, drugs must be effectively encapsulated. Many factors are likely at play, including molecular size, hydrophilicity/hydrophobicity, surface charge, and physicochemical properties of both the drug and the polymer. By characterizing the relationship between these parameters, we sought to find factors that would increase the loading of panobinostat in PLA-PEG nanoparticles.

Prior studies in the lab had focused on encapsulating another HDACi, quisinostat, in

PLA-PEG nanoparticles by exploiting alkaline solutions to increase the loading of the drug up to 9% w/w. However, preliminary studies with panobinostat failed to show the same increases in loading with changes in pH. Furthermore, while quisinostat must be added at the evaporation phase to achieve maximal loading, panobinostat may be added to the organic phase, suggesting differences in the way that the two drugs load into PLA-PEG nanoparticles (19). The molecular weight of the copolymer was investigated for two reasons as a factor that might enhances drug encapsulation. First, molecular weight increases the size of a particle, potentially providing more “room” for the drug, and second, molecular weight has been shown to impact the release of the drug (11,13,16, 21, 24, 34,

37, 46).

However, we did not find a strong correlation between molecular weight and loading.

This does not preclude the possibility that molecular weight still has some effect on loading. We did observe that the highest molecular weights (28427 Da and 35808 Da PLA) had the highest average loading, which suggests that maybe higher molecular weight particles do in fact have a higher drug capacity. Interestingly, the 23644 Da PLA particle had significantly lower loading than the 16640 Da particle, which suggests that other factors are at play. Perhaps increases in molecular weight do not generate increases in capacity. This could be due to differences in internal structure that were not assayed, and may be an avenue of future investigation through transmission electron microscopy. Rather than increased capacity, as the size of these particles do not greatly change to be directly associated with more loading, it may be the interaction of the drug and polymer. Generally, improving the solubility of drug in the hydrophobic core of a polymeric particle will increase its loading. Thus, the higher molecular weight PLA was able to increase the loading of panobinostat by improving its solubility in this core. A similar relationship was noticed with another co-polymer methoxy poly (ethylene oxide)-block- poly(ε- caprolactone) (PEO-b-PCL). The longer chains of PCL were able to increase the loading of amiodarone, a more amphiphilic drug (48). Panobinostat interacting with the longer PLA chain lengths in the 28427 Da and the 35808 Da PLA particles, increased its loading.

However, it is interesting to note that the loading was not strongly correlating with molecular weight, as the particles made with the lowest molecular weight (16640 Da) did have a higher loading than the 23644 Da particle. While it was expected that the 23644 Da

PLA: PEG would have a higher loading, since it is the longer PLA chain, there may be other factors that contributed to a lower loading in those particles. That potentially that

18 specific ratio of PLA:PEG may not have contributed to a favorable interaction with the panobinostat.

Another important piece of information was the encapsulation efficiency of these particles was all less than 50%. Again, this establishes that potentially the interaction between the panobinostat and PLA: PEG may not have been as favorable thus encapsulating less efficiently. As expected particles that had lower percent loadings also had significantly lower encapsulation efficiencies. Other factors would need to be investigated such as the solvent for the single emulsion technique and the polymer itself having an impact on how the drug is encapsulating.

A further characterization of particles made with 28644 Da PLA displayed some interesting characteristics of these particles. First the particles displayed a biphasic release profile. Secondly the drug was tolerable at higher doses, which could be attributed to the decrease in bioactivity of panobinostat loaded in these particles.

The biphasic release profile seen was that a majority of the drug released in the first 6 hours, a plateau where little drug was released over the next 6 hours, and a final phase where the remainder of the drug was released over the next 60 hours. This again points to an interaction between the drug and the polymer. Xiao et al. described that the ratio between PLA and PEG has a major impact on the release characteristics of the particle

(39). This could because there is a significant interaction between the PLA and hydrophobic drugs. Yang et al. observed this phenomenon when they noted that insoluble

Amphotericin B interacted with the hydrophobic PLA element of the nanoparticle (46).

They additionally found that the drug close to the surface is released fastest, with the remainder of the drug at the interior diffusing out more slowly over the course of 80 hours.

As the higher molecular chains did have an interaction with the drug therefore solubilizing panobinostat more effectively in the hydrophobic core, the drug was able to release slower.

However, we were not able to compare the release of these particles to the formulations made with other PLA lengths as concentrating the particles reduced the polydispersity of these particles. Furthermore, in order to accurately collect the release data, an initial high drug concentration is required and thus for the lower loading particles, achieving a high concentration is crucial.

In order to determine the potency of the encapsulated panobinostat cell viability assays were conducted. However, while investigating there were a few roadblocks. As panobinostat is poorly soluble, 100% DMSO was used to dissolve to the required concentration 5 mg/ml. However, after 72 hours, when the free drug 96-well plate was read, the cell death was observed at lower drug concentrations including no drug and the

DMSO vehicle control. It is inconclusive whether the free drug or DMSO is killing the cells especially at low concentrations of drug. While concentrations of DMSO above 10% are known to be cytotoxic to cells, the exact threshold for toxicity depends on the cell type

(12,42). While these roadblocks were faced, IC50 data from Pei et al suggests that the encapsulation of panobinostat in this study may have reduced the bioactivity of the drug.

The IC50 for panobinostat was 10nM against the murine group 3 medulloblastoma cell line

(33). This is significantly less than 177 nM observed in this study. It is important to note, that between replicates of this experiment there are concerns over the accuracy of this IC50.

First, the raw data and the variability between the replicates makes it difficult to determine if the average IC50 data is representative of the potency of these particles.

This bioactivity data provides some insight into reasons why the intrathecally administered nanoparticles were tolerable in mice at higher doses. Since the drug may not be as potent as free drug, the tolerability may have improved in the encapsulated drug only due to reduced potency. Currently these particles have been administered at a dose of 20 ug without any toxic effects such as acute neurological symptoms and weight loss. This was the highest deliverable dose as the concentration of the particles and the volume of infusion were limiting factors. The major limiting factor in administering drug to the central nervous system with the intracisternal injection is making sure that the intracerebral pressure is not acutely increased. It is possible that a maximum tolerated dose may not be determined however, more studies will be conducted to deliver greater than 20ug. Future studies will use the maximum tolerated dose to explore if the formulation is effective at increasing overall survival of mice with medulloblastoma metastasis.

There are a few steps that will be conducted for this research moving forward. First more cell viability assays need to be conducted to determine a more accurate IC50.

Furthermore, reducing the concentration of DMSO and changing the vehicle to solubilize panobinostat will provide a direct comparison for the IC50 of panobinostat nanoparticles.

As the encapsulation efficiency of panobinostat was low, potentially changing the drug and polymer ratios, solvent and the polymer are other factors that may impact and increase the efficiency of encapsulation. Finally, improving the concentrations of particles while maintaining a monodisperse particle solution to conduct more release profiles as molecular weight is also known to impact the release of the drug.

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