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High Throughput and Predictive Stability Approaches for Parallel Drug Product Development

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. Disclaimer.

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High Throughput and Predictive Stability Approaches for Parallel Drug Product Development

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  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 derWielen, Stefan Taylor

  2. Disclaimer • 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 • 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)

  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???

  6. Drug Product Development • 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 Narrowed design space Entire design space Good stability subspace Good processability subspace Good bioavailability subspace

  8. Challenges with down-scaled, automatic experiments Amount of information Smaller scale and more automation Progress of experiment

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

  10. Integrating Hardware and software: SM Development labs example

  11. Product Design and Developability Workflows • Support to Drug substance and drug product development • 16 active screening workflows implemented and used as part of our platform-based development approach

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

  13. Excipient Compatibility • 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

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

  16. Powder dispensing LEA Database • Time Stamp • Actual Dispenses RAS Automation Studio • Chemical Maps • Dispensing Tags • Processing Tags • Chemical Maps • Dispensing Tags • Processing Tags • Time Stamp • Actual Dispenses SV hopper Right Arm Z2Vial Plate gripper

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

  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 Blend Load (mg) Vortex mixing speed (rpm)

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

  20. Case Study I: Compound X formulation challenge • 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

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

  23. Case Study II: Bench Mark the Stability Behavior of Compound Y concepts • 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 The samples preparation is finished within 2 days on CM3 … • Automation enabled timely stability study for parallel drug product development • Shelf-life can be predicted via ASAP approach

  25. Conclusion & Challenges • 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 ?

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

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

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