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Bioequivalence Criteria Research Plan Stella G. Machado, Ph.D. Office of Biostatistics and the Replicate Design Technical Committee Advisory Committee.

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Presentation on theme: "Bioequivalence Criteria Research Plan Stella G. Machado, Ph.D. Office of Biostatistics and the Replicate Design Technical Committee Advisory Committee."— Presentation transcript:

1 Bioequivalence Criteria Research Plan Stella G. Machado, Ph.D. Office of Biostatistics and the Replicate Design Technical Committee Advisory Committee for Pharmaceutical Science Rockville, Maryland November 29, 2001

2 Background Guidances for Industry –Bioavailability and Bioequivalence Studies for Orally Administered Drug Products - General Considerations: October 2000 –Statistical Approaches to Establishing Bioequivalence: January 2001 Advisory Committee for Pharmaceutical Science Meeting 9/23/1999 –Discussed FDA plans for further research and projects associated with the use of ABE and IBE criteria

3 Background continued ACPS endorsed plans for furthering mechanistic understanding, clinical pharmacology studies, influence of outliers on SxF interaction ACPS requested creation of research document to guide activities during an interim period Document sent for review (9/1999) to Population and Individual BE Expert Panel Draft Research Document modified by Population and Individual Working Group of CDER’s Biopharmaceutics Coordinating Committee in response to comments received (4/2000)

4 Research Program Overview Goal is to provide information to support final regulatory decisions regarding criteria for comparing BA in BE studies Research Plan has 3 projects –A) Criteria for BE comparisons –B) Data analyses and Statistical Methodology –C) Mechanistic understanding of Mean and Variances differences between T and R

5 Program overview - continued Studies conducted by drug sponsors will be major source of data for our evaluations General Guidance recommends replicate designs for highly variable drugs and modified release dosage forms

6 A) Criteria for BE comparisons Choice of ABE, IBE criteria for BE studies in particular types of regulatory submissions: IND, NDA, ANDA and post-approval supplement filings Replicate-designed data sets are analyzed upon receipt, and interpreted in light of recommendations in Guidance These analyses add to knowledge base for evaluating performance of approaches

7 A) Criteria for BE comparisons - continued Identify and evaluate : –clinically important T/R differences in within- and between-subject variances, and SxF interactions –importance and impact of mean/variance trade- offs –other outcomes based on selected disaggregate criteria study discontinuity aspect of IBE and possible resolution

8 B) Data Analysis and Statistical Methodology Criteria and methods for assessing ABE and IBE as laid out in the Guidance are reasonable and valid –open to new approaches - as yet no persuasive alternatives have been presented Primary objectives –assess estimation methods in presence of missing data –assess properties of estimates of parameters of interest –assess impact of apparent outlier data on properties of aggregate IBE criterion

9 B) Data Analysis and Statistical methodology - continued Secondary objectives –monitor and assess carryover effects using data from replicate designs –assess numbers of subjects and good study designs for heterogeneous populations, including both genders, different ethnic groups and different age ranges

10 C) Mechanistic Understanding Develop mechanistic understanding as needed for: –important differences in means –important differences in within subject variances for Test and Reference products for highly variable and modified release drug products –subject-by-formulation interactions

11 Focus for immediate future continue evaluation of replicate designed studies as received address design and other issues via simulation studies evaluate impact of changing constraint on mean difference respond to recommendations of ACPS

12 Concluding remarks some issues in 4/2000 Research Plan were addressed and incorporated into Guidances now in evaluation phase of data sets and performance of estimation methods


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