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Explore the challenges facing the traditional pharmaceutical business model and the need for a fundamental change in manufacturing processes. Discover the future vision of the industry and what can be done to adapt.
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Breaking with Tradition:The Manufacturing Challenges Ahead! Ray Scherzer FDA ACPS October 26, 2005
Setting the stage • The Traditional Pharma Business Model … changes underway • Our current technology • The challenge ahead! • A vision of the future • What can you do??
The 70s, 80s and 90s … the traditional model Double Digit Growth + Profits, $$$$$ + Challenging Regulators
Politics Pricing Generics& Re-importation Attrition Payer resistance Regulatory Scrutiny Pharma Industry Industry pressures today
Past Avoid change Quality “tested in” Regulatory fear Silo organisations Empirical science Future Opportunities Innovation Good science Collaboration Efficiency Quality by design Real time release Regulatory hurdles Regulatory hurdles Fundamental change in regulatory framework PAT CGMPs Criticalpath
Regulatory changes • Major shift by FDA • Dedicated Pharma inspectorate • Approvals and inspections focused on scientific and engineering principles • Hiring physicists, chem engineers, C&I engineers, statisticians ... Plus! • Empirical methods are last resort
Significant impacts • Higher scrutiny of existing products • Higher expectations for new products “If you can’t explain how your manufacturing processes work in the first 25 pages of your submission … the approval process will become much more difficult!” Moheb Nasr, FDA, Director Office of New Drug Chemistry …
Discover Develop Test Launch Market $500m 80s: 7 -8 yrs $800m 90s: 8 -10 yrs $1,700m 00s: 10+? yrs The changing pharma business model Launch costs Launch time Avg. ROI, % > 10 9 -10 5
Today’s business is much different than yesterdays! The Industry will and is changing!!
Current Technology
Industry Manufacturing process knowledge Extent of knowledge Prediction of performance (in-vivo) 5 1st Principles 4 Control and release against process signature MECHANISTIC KNOWLEDGE 3 Relate critical process variables to quality attributes of finished product CAUSAL KNOWLEDGE 2 Correlate process inputs and outputs CORRELATIVE KNOWLEDGE 1 Establish processoutline DESCRIPTIVE KNOWLEDGE
“We’ve got a few problems going from lab scale to full scale commercial”
Industry target Manufacturing process knowledge Extent of knowledge Prediction of performance (in-vivo) 5 1st Principles 4 Control and release against process signature MECHANISTIC KNOWLEDGE 3 Relate critical process variables to quality attributes of finished product CAUSAL KNOWLEDGE 2 Correlate process inputs and outputs CORRELATIVE KNOWLEDGE 1 Establish processoutline DESCRIPTIVE KNOWLEDGE
Significant gaps exist: • Manufacturing and scale up sciences • Unit operation technology and control • Academic training & skilled resources • Industrial organization and structure • Correlation to in vivo performance
Reaction Crystallization Drying Separation Particle engineering Formulation Dispensing Blending Granulation Compression Coating Filling Aseptic operations Packaging First steps: Unit operation science Industry basic unit operations Material Handling, Analytical
Unit operations goals • Well understood platform technologies • Develop the science of all unit operations • Fully instrumented • Closed loop control … fully automated • Material interactions (formulation & devices) • Predictable scale effects • Design/use the right equipment • Predict performance without extensive experimentation • Math modeling to speed design • GOAL: Final testing to confirm operations
Once UOs understood and platform technologies developed, thenIntegrated Process Designs
Integrated process design: Objectives • Aligns with FDA’s Quality by Design Concept • Link “Platform Technologies” in an integrated process design • 1ST step of API to primary pack and device performance • Identify CCPs that affect up and down stream ops • Control systems will manage variability within the process • Link CCPs to traditional release testing; i.e. dissolution, assay, CU, ACI • Produce in spec product by monitoring and controlling critical parameters … rather than end point testing • Obtain real time release
Engineering models would: • Process design tool of preference • Rapid evaluation of excipients, DS, formulations, equipment, environmental, devices, etc. • Narrow alternatives in silica • Reduce scale up trial and error … focus testing on high probability results … time & money!! • After confirmation, use model to demonstrate full process understanding … regulatory expectation • Would be the basis for continuous improvement studies
The future manufacturing vision! • Fundamental understanding of the science • Develop mfg scale processes … before registration • Small scale, contained, dedicated, automated, continuous processes • Late stage customization • On line measurement and control • Real time release • Product plants … not component plants • Leverage relationships … internal, academia, industry, regulatory agencies to develop the science
Gaps in skills and facilities exist • Manufacturing sciences • Powder technology • Chemical / Process engineers • Rheologists (non Newtonian fluids) • Physicists • Spectromisists • Chemometricians • Process development pilot plants (not CT PPs) • “Soft skills” & Business skills
Some current activities • Industry/Company Culture changes underway • Empirical to fundamental sciences • Industry pressures key driver • External work lays foundation (FDA, ASTM, CAMP, ISPE, IFPATma) • Develop the next level of manufacturing science • PAT and cGMPs for 21st century • Pharma professional of the future … engineering + • Universities need to develop and teach the science • Capitalize on today’s situation to forge an even stronger future
Your role in this: • Support/create means for fundamental research in the Pharma manufacturing sciences • Encourage students into science & engineering careers • Encourage universities to create the programs • Be consistent and science based in your activities • Give this priority and attention
Verge Paradigm Shift