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Highly Variable Drugs FDA Case Studies

Highly Variable Drugs FDA Case Studies. Barbara M. Davit, Ph.D. Deputy Director, Division of Bioequivalence Office of Generic Drugs Advisory Committee for Pharmaceutical Sciences April 14, 2004. Overview. Is high variability a significant issue in BE studies of ANDA submissions?

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Highly Variable Drugs FDA Case Studies

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  1. Highly Variable DrugsFDA Case Studies Barbara M. Davit, Ph.D. Deputy Director, Division of Bioequivalence Office of Generic Drugs Advisory Committee for Pharmaceutical Sciences April 14, 2004

  2. Overview • Is high variability a significant issue in BE studies of ANDA submissions? • From evaluating case studies of BE submissions, can we learn some of the reasons for high variability?

  3. Statistics on BE Submissions: Objectives • Identify the scope of the problem • What percentage of our submissions are for “highly variable drugs”? • How many subjects are enrolled in studies of highly variable drugs? • How narrow or wide are the 90% CIs of T/R ratios for AUC and Cmax?

  4. Statistics on BE Submissions: Methods • Collected summary BE statistical data on all in vivo studies submitted and reviewed in DBE in 2003 • Used Root Mean Square Error as estimate of intrasubject variability • Defined highly variable = RMSE > 0.3 • Surveyed only solid oral dosage forms • All studies passed 90% CI criteria

  5. DBE Submissions with In Vivo Studies

  6. Observed frequency of RMSE values, Cmax

  7. Observed frequency of RMSE values, AUC0-t

  8. Drug products and food effects in 33 HV studies

  9. Highly variable Cmax in fed but not fasting study * Prodrug parent compound

  10. Highly variable Cmax in fasting but not fed study * Prodrug parent ** Active metabolite of prodrug

  11. Highly variable Cmax in both fed & fasted studies * Prodrug Parent Compound

  12. Both AUC, Cmax highly variable

  13. Test and Reference Product Variability

  14. PK variability can vary with drug product

  15. Number of study subjects and variability in Cmax

  16. Width of Cmax90% CI versus number of subjects

  17. Highly variable AUC, 90% Confidence Intervals PE; 90% CI N 1.16; 1.00 – 1.34 24 Fed, RMSE=0.34 Fed, RMSE=0.37 0.90; 0.76 – 1.07 26 Fasted, RMSE=0.38 0.95; 0.82 – 1.11 36 Fasted, RMSE=0.30 45 1.01; 0.90 – 1.12 62 Fasted, RMSE=0.30 1.07; 0.97 – 1.18 77 0.93; 0.89 – 0.98 Fasted, RMSE=0.30 0.75 1.00 1.25

  18. Conclusions • In 2003, 15.5% of all BE studies submitted were for drugs that met the “highly variable” criteria • Cmax more variable than AUC • In general, higher PK variability occurred in fed BE studies • Replicate design studies showed comparable PK variability for T and R

  19. Conclusions • In two cases, variability was associated with formulation or other factors in conducting the BE studies • In general, the width of the 90% CI became narrower as N increased • Of 212 passing BE studies, only 14 enrolled > 50 subjects • Of 33 passing BE studies of HV drugs, only 5 enrolled > 50 subjects

  20. Acknowledgements • Mei-Ling Chen • Dale Conner • Sam Haidar • Qian Li • Devvrat Patel • Don Schiurmann

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