1. High Throughput and Predictive Stability Approaches for Parallel Drug Product Development Pharmaceutical Development and Manufacturing Sciences, PDMS, Janssen pharmaceutica NV Likun Wang, Sabine Thielges, Maarten van der Wielen, Stefan Taylor

2. Disclaimer 2 The opinions expressed in this presentation are those of the presenter only and do not necessarily reflect the positions or opinions of Janssen Research & Development, LLC. (“Janssen”) or any other individuals or affiliates of Janssen. The presenter makes no warranties with respect to the accuracy or completeness of the data or materials presented. All information is provided for informational purposes only and does not constitute advice or endorsement of any products or processes.

3. Janssen Pharmaceutica NV 3 A Global Pharmaceutical Company A pharmaceutical company of Johnson & Johnson HQ in Beerse, Belgium Multiple R&D sites in Europe, US, China and India Janssen, Beerse, Belgium Janssen, Geel, Belgium

4. Outline Background & Challenges in Pharmaceutical R&D Overview of LEA platform in Janssen Pharmaceutical Research & Development Case Studies: Excipient Compatibility Accelerated Stability Assessment Program (ASAP) 4

5. Our challenge in pharmaceutical R&D More complex products (the easy ones are gone) Constantly increasing regulatory and patient expectations Cost of drug development is rising exponentially, and timelines are expanding We need more shots on goal due to high attrition Need more killer experiments The solution??? 5

6. Drug Product Development 6 Drug Product BioavailabilityStabilityProcessability Can be developed only if Bioavailability Processability Stability are achieved simultaneously Parallel concept development is the major approach to accelerate drug product development process

7. Parallel concept development – a design space perspective Need systematic experimentation, e.g.DoE Parallel concept development Need higher throughput Down-scaling and automation is the key 7 Entire design space Narrowed design space Good bioavailability subspace Good processability subspace Good stability subspace

8. Challenges with down-scaled, automatic experiments Central information storage DoE Material handling AnalysisReporting DoE (Minitab, Design expert, etc.) Material handling (different softwares) Analysis (different software) Reporting (Excel ?) Smaller scale and more automation Amount of information Progress of experiment 8

9. LEA: centralized information handling platform Database RAS Library Studio Automation Studio CM3 Hamilton UPLC … DoE Execution & analysis Symyx data browser LEA data viewer Data query & processing Report generation Pipeline Pilot 9

10. Integrating Hardware and software: SM Development labs example 10

11. Product Design and Developability Workflows 11 Support to Drug substance and drug product development 16 active screening workflows implemented and used as part of our platform-based development approach API workflowsDP workflows 1. Polymorph screen1. Thermodynamic solubility screen 2. Salt screen2. Excipient compatibility 3. Re-crystallization screen3. Solid Dispersion 4. Morphology screen4. Aqueous solution formulation 5. Forced degradation5. IV formulation screen 6. Accelerated Stability Assessment Program (DS) 6. Accelerated Stability Assessment Program (DP) 7. Miniaturized powder flowability6. Precipitation Inhibition 7. Nano-milling & physical stability 8. Co-solvent & lipid formulation screen 9. Powder blend segregation

12. PART I. Excipient Compatibility – The Dynamics of Drug Product Stability 12

13. Excipient Compatibility 13 Study chemical compatibility behavior between API and excipients Closely related to drug safety and efficacy Normally carried out in early development phase Sometimes included in the preformulation package Solid state form selection need to be done before excipient compatibility Final morphology, particle size are preferred Final synthesis route is best in place

14. Different Approaches Towards Excipient Compatibility 1:1 mixtures Easy to set-up May overestimate (Not the actual ratio) May underestimate (Synthetic effect) Full Blend then N-1 method (remove one excipients per time) Gives more information 2-step method More time consuming DoE approach – Mixture Design Able to predict the dynamics of mixture Much more samples need to be prepared 14

15. Challenges to conquer before getting the benefits of mixture DoE Powder dispensing Mixing powder homogeneously in small scale 15

16. Powder dispensing Right Arm Z2 Vial Plate gripper SV hopper LEA Database RAS Chemical Maps Dispensing Tags Processing Tags Chemical Maps Dispensing Tags Processing Tags Time Stamp Actual Dispenses Automation Studio Time Stamp Actual Dispenses 16

17. Powder dispensing LEA Database RAS Automation Studio Symyx data browser LEA data viewer Pipeline Pilot RAS 17

18. Mixing in Small Scale Vortex Mixing  Particle size/morphology not affected  Mixing efficiency depends on load  Gentle mixing Magnetic stirrer bar/disk  Particle size/morphology may affected  Longer mixing time Turbula Mixer  Particle size/morphology may affected  Good mixing efficiency  Gentle mixing 18 Blend Load (mg) Vortex mixing speed (rpm)

19. Case Study I: Compound X formulation challenge 19 Standard capsule formulation Poor flowability (formulator suggested to add more silicon dioxide) High Dose (around 50% API load) No silicon dioxide Medium silicon dioxideHigh silicon dioxide

20. Case Study I: Compound X formulation challenge 20 Silicon dioxide could cause degradation Interactions between silicon dioxide with fillers were revealed Optical formulation ranges can be suggested from stability perspective The amount of silicon dioxide need to be carefully controlled Mixture DoE and small-scale experiments can be used for excipient compatibility studies

21. PART II. Accelerated Stability Assessment Program– The Kinetics of Drug Product Stability 21

22. The concept of Accelerated Stability Assessment Program (ASAP) 22 Relative Humidity corrected Arrhenius equation Isoconversion Monte-Carlo simulation Packaging KC Waterman, AAPS PharmSciTech Vol 12 No.3, September 2011 % Degradant Time 70°C 50°C 25°C

23. Case Study II: Bench Mark the Stability Behavior of Compound Y concepts 23 Compound Y is under BCS Class II (Low solubility, high permeability) Need amorphous solid dispersion to boost bioavailabiilty 28 amorphous solid dispersion concepts were investigated Need to predict/compare shelf life for each concepts 12 samples need to be prepared for each concept according to ASAP 336 samples in total prepared by CM3

24. Case Study II: Bench Mark the Stability Behavior of Compound Y concepts 24 … The samples preparation is finished within 2 days on CM3 ConceptsY/PVPVA 64Y/HPMC-ASY/HPMC E5Y/Eudragit L100-55 … Predicted Shelf- Life (year) Based on worst degradant <12.42.32.6… Automation enabled timely stability study for parallel drug product development Shelf-life can be predicted via ASAP approach

25. Conclusion & Challenges 25 With DoE and ASAP, down-scale and automation has added-on value for stability studies Parallel drug product development could benefit from down-scale and automation CM3 is not GMP certified yet Combine dynamics and kinetics studies Data handling challenge (HPLC peak identification)

26. Thank for your attention! Questions ? 26

27. 27 50°C 60°C 70°C Accelerated Aging—ASAPprime TM Approach Bimodal Degradation 0.5% specification limit 0.2% specification limit ASAP isoconversion: % degradant fixed at specification limit, time adjusted

28. 28 50°C 60°C 70°C Accelerated Aging—ASAPprime TM Approach Bimodal Degradation 0.5% specification limit