1 Bioequivalence of Highly Variable Drugs: Regulatory Perspectives Sam H. Haidar, R.Ph., Ph.D. Pharmacometrics Office of Generic Drugs

2 Potential Advantages Reduction in regulatory burden Reduction in regulatory burden Facilitate market access for highly variable but safe and effective drugs Facilitate market access for highly variable but safe and effective drugs Make it easier to approve a generic drug product which is significantly less variable than the reference listed drug Make it easier to approve a generic drug product which is significantly less variable than the reference listed drug

3 Current BE* Requirements Major Regulatory Agencies U.S. Food and Drug Administration (FDA) U.S. Food and Drug Administration (FDA) Health Canada Health Canada Committee for Proprietary Medicinal Products (CPMP), Europe Committee for Proprietary Medicinal Products (CPMP), Europe National Institute of Health Sciences (NIHS), Japan National Institute of Health Sciences (NIHS), Japan *BE = Bioequivalence

4 Current BE Requirements FDA* AUC: 90% Confidence Interval Limits % AUC: 90% Confidence Interval Limits % C max : 90% Confidence Interval Limits % C max : 90% Confidence Interval Limits % Criteria applied to drugs of low and high variability Criteria applied to drugs of low and high variability *Guidance for Industry: Bioavailability and Bioequivalence Studies for Orally Administered Drug Products- General Considerations

5 Current BE Requirements Health Canada AUC: 90% Confidence Interval Limits % AUC: 90% Confidence Interval Limits % C max : Mean T/R ratio (point estimate) between % C max : Mean T/R ratio (point estimate) between % Criteria judged flexible enough to deal with highly variable drugs* Criteria judged flexible enough to deal with highly variable drugs* *Expert Advisory Committee on Bioavailability and Bioequivalence, June 26 – 27, 2003.

6 Current BE Requirements CPMP* AUC: 90% Confidence Interval Limits % AUC: 90% Confidence Interval Limits % C max : 90% Confidence Interval Limits % C max : 90% Confidence Interval Limits % C max : “In certain cases a wider interval is acceptable (e.g., %) C max : “In certain cases a wider interval is acceptable (e.g., %) *Note for Guidance on the Investigation of Bioavailability and Bioequivalence, January 2002

7 Current BE Requirements NIHS (Japan)* AUC: 90% Confidence Interval Limits % AUC: 90% Confidence Interval Limits % C max : 90% Confidence Interval Limits % C max : 90% Confidence Interval Limits % In cases of failure, add-on studies are acceptable (provided other criteria are met) In cases of failure, add-on studies are acceptable (provided other criteria are met) *Guideline for Bioequivalence Studies of Generic Drugs, December 22, 1997.

8 Performance of FDA Criteria Survey of ANDA Applications ( ) Survey of ANDA Applications ( ) Evaluated distribution of C max and AUC T/R mean ratios (point estimates) Evaluated distribution of C max and AUC T/R mean ratios (point estimates)

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13 Summary Although criteria allows for a mean difference of ± 20%, the vast majority of submissions were within ± 10% Although criteria allows for a mean difference of ± 20%, the vast majority of submissions were within ± 10% This was also true with regard to highly variable drugs and drug products This was also true with regard to highly variable drugs and drug products Additional confirmation of greater variability associated with C max Additional confirmation of greater variability associated with C max

14 Available Options Bioequivalence of Highly Variable Drugs Scaling based on intra-subject variability (C max, AUC) Scaling based on intra-subject variability (C max, AUC) Expansion of regulatory limits Expansion of regulatory limits

15 Scaling Approaches Reduction in sample size Reduction in sample size Limits are defined by degree of variability Limits are defined by degree of variability Need for point estimate constraint? Need for point estimate constraint?

16 Expansion of Limits C max only, or C max and AUC C max only, or C max and AUC Fixed Limits (e.g., 70 – 143%) for drugs meeting high variability “criterion” Fixed Limits (e.g., 70 – 143%) for drugs meeting high variability “criterion” Need for point estimate constraint? Need for point estimate constraint? Major concern: How to classify borderline drugs and drug products Major concern: How to classify borderline drugs and drug products

17 Expansion of Limits Study: Hauck et al.* AUC: 90% Confidence Interval Limits % AUC: 90% Confidence Interval Limits % C max : 90% Confidence Interval Limits % C max : 90% Confidence Interval Limits % Outcome: Sample size reduced by 60% Outcome: Sample size reduced by 60% C max ratios of 128% could pass using the % limit C max ratios of 128% could pass using the % limit *Hauck et al. Int J Clin Pharm Ther. 39 (8) pp (2001)

18 Conclusion If a need to make changes in the regulations is concluded: If a need to make changes in the regulations is concluded:  Either approach would result in significant reduction in sample size  Additional criterion constraining point estimates may be needed Based on prior experience, clustering around a T/R ratio of 1 would be expected for a modified BE criteria for highly variable drugs Based on prior experience, clustering around a T/R ratio of 1 would be expected for a modified BE criteria for highly variable drugs

19 Q & A Dale Conner, Pharm.D. Dale Conner, Pharm.D.