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FDA’s Critical Path to Medical Product Development: Opportunities for Generic Drugs

FDA’s Critical Path to Medical Product Development: Opportunities for Generic Drugs. Lawrence X. Yu, Ph. D. Director for Science Office of Generic Drugs Food and Drug Administration. Advisory Committee for Pharm. Science October 19, 2004. The Critical Path for Medical Product Development.

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FDA’s Critical Path to Medical Product Development: Opportunities for Generic Drugs

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  1. FDA’s Critical Path to Medical Product Development:Opportunities for Generic Drugs Lawrence X. Yu, Ph. D. Director for Science Office of Generic Drugs Food and Drug Administration Advisory Committee for Pharm. Science October 19, 2004

  2. The Critical Path for Medical Product Development • Ensuring Safety • Demonstrating Medical Utility • Industrialization Process

  3. President Bush on Health Care “There are other ways to make sure drugs are cheaper. One is to speed up generic drugs to the marketplace, quicker.” October 8 Presidential Debate

  4. FDA’s Critical Path Initiative • Janet Woodcock, M.D. (June 4, 2004) • A serious attempt to bring attention and focus to the need for targeted scientific efforts to modernize the techniques and methods used to evaluate the safety, efficacy and quality of medical products as they move from product selection and design to mass manufacture.

  5. Definition of a Generic Drug A drug product that is therapeutically equivalent to a brand-name drug; Comparable to a brand-name drug product in dosage form, strength, route of administration, quality and performance characteristics, and intended use. • FDA’s Critical Path • Ensuring Safety • Demonstrating Medical Utility • Industrialization Process Bioavailability/ Bioequivalence

  6. FDA’s Critical Path - OGD • Bioavailability/Bioequivalence Modeling and Prediction • Bioequivalence of Locally Acting Drugs • Product Design, Characterization, and in vitro Performance Testing

  7. BCS Based Biowaiver Solubility Permeability Metabolism Protein Binding CAT Predictive Model New Molecules Animal Models ADME HTS Screens Solubility, Permeability Metabolism QSARs Low F? Quantitative Structure- Bioavailability Relationships, QSBR e-ADME: Predicting Bioavailability and Bioequivalence

  8. Biopharmaceutics Classification System Guidance for Industry Waiver of In Vivo Bioavailability and Bioequivalence Studies for Immediate Release Solid Oral Dosage Forms Based on a Biopharmaceutics Classification System US Department of Health and Human Services Food and Drug Administration Center for Drug Evaluation and Research (CDER) August 2000 • Waiver for BCS Class III drugs • Excipient effect • Transporters • BCS Class boundaries • Solubility • Permeability Molecular Pharm. 1:356-362 (2004) J. Pharm. Sci. 93:1375-81(2004) Eur. J. Pharm. Sci. 22:297-304(2004)

  9. Compartmental Absorption and Transit (CAT) Model • An in silico mechanistic model describes • How a drug gets into the blood • How much it gets into the blood • How fast it gets into the blood • Research at OGD continues to identify critical bioavailability/ bioequivalecne factors Int. J. Pharm. 270:221-227 (2004) Molecular Pharm. In press

  10. Quantitative Structure Bioavailability Relationship (QSBR) Model QSBR Model Rat Dog Pharm. Res. 17:639-644 (2000)

  11. Predicting Bioavailability/ Bioequivalence • Biopharmaceutics Classification System • Classification refinement and waiver extension • Compartmental Absorption and Transit Model • Understand critical absorption factors • QSBR Model • Very promising; not widely used (due to …)

  12. Bioequivalence Methods for Locally Acting Drugs • Key Scientific Challenges • Topical Dermatological • Nasal Spray and Inhalation • Gastrointestinal, vaginal, and ophthalmic • Often require clinical testing • Target research to provide a scientific basis for in vitro or in vivo bioequivalence methods

  13. Locally Acting Drugs Site of Action Dose Effect Plasma concentration is usually not relevant to local delivery bioequivalence Plasma Concentration • 21 CFR 320.24 allows alternatives: • in vivo pharmacodynamics • in vivo clinical comparisons • in vitro comparisons • other appropriate approaches Need for OGD Research Program

  14. Clinical Bioequivalence Studies • Test, reference, placebo arms in patients • 90% confidence interval on test – reference cure rate • Estimated CV’s ~100%

  15. Bioequivalence of Locally Acting Drugs • Barrier to generic competition • Barrier to product improvement • Need to demonstrate BE after formulation change or in product development • Clinical endpoints have high variability • Inefficient detection of formulation differences • Unnecessary human testing

  16. Product Design and Characterization • Same drug substance • Pharmaceutical solid polymorphism • Same dosage form • Topical products • Product quality • Quality standards • Adhesion tests for transdermal products • Nasal and inhalation products • Novel drug delivery systems

  17. Stomach pH 1.4-2.1 Jejenum pH 4.4-6.6 Ileum pH 6.5-7.4 Product Performance Testing

  18. Product Performance Testing • Role of Dissolution Testing • A quality control tool • Monitor batch-to-batch consistency of the drug release from a product • An in vivo performance test • An in vitro surrogate for product performance that can guide formulation development and ascertain the need for bioequivalence tests Are these goals consistent?

  19. Process Identification, Simulation, and Optimization Tools • Historically, pharmaceutical production involves the manufacture of the finished product using batch processes, followed by excessive laboratory testing and analysis to verify its quality • Process identification, simulation, and optimization tools need to be developed for pharmaceutical batch processes so that any manufacturing process failure can be readily identified and corrected • Product quality is assured by high quality of starting materials, robust manufacturing processes, and limited laboratory testing and analysis

  20. Future Directions • Continue to build world class scientific expertise in predicting bioavailability/ bioequivalence and process optimization • Prioritize scientific efforts • Pursue collaborations • Within FDA (OTR, CBER, CDRH) • With academia (U of Michigan, U of Kentucky, Ohio State U, U of Maryland, and CSM) • With NIST and other government agencies • With industry

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