1 / 21

Why Bioequivalence of Highly Variable Drugs is an Issue

Why Bioequivalence of Highly Variable Drugs is an Issue. Charles E. DiLiberti Vice President, Scientific Affairs Barr Laboratories, Inc. Presentation to the Advisory Committee for Pharmaceutical Sciences April 14, 2004. Definition of Highly Variable Drugs (HVDs).

tuan
Télécharger la présentation

Why Bioequivalence of Highly Variable Drugs is an Issue

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Why Bioequivalence of Highly Variable Drugs is an Issue Charles E. DiLiberti Vice President, Scientific Affairs Barr Laboratories, Inc. Presentation to the Advisory Committee for Pharmaceutical Sciences April 14, 2004

  2. Definition of Highly Variable Drugs (HVDs) • Any drug whose rate and extent of absorption shows large dose-to-dose variability within the same patient • Commonly understood to include those drugs whose intrapatient coefficient of variation (Cmax and/or AUC) is approximately 30% or more

  3. Current Bioequivalence Criteria • Comparison between test and reference product • Use natural log transformation of Cmax and AUC • Criterion: 90% confidence intervals about geometric mean test/reference ratios for both Cmax and AUC must fall within 80 – 125% • Applies to all systemically acting drugs (i.e., not locally acting) with measurable blood or urine levels without regard to the drug’s inherent variability • Same criteria used by pioneer firms to support formulation changes

  4. Why Alternative Acceptance Criteria Are Needed for HVDs • Reduce human experimentation (number of participants) in BE studies • Prohibitive size of BE studies for some HVDs means no generic is available – many American patients go untreated/undertreated • Changing criteria to reduce number of participants in BE studies on HVDs can be accomplished without compromising safety/efficacy • 80 – 125% BE criteria not universally implemented worldwide

  5. Foreign BE Criteria

  6. Types of Drugs That Are Highly Variable • Includes many therapeutic classes • Includes both newer and older products • Potential savings to patients in the billions of dollars if generics are approved • Examples: atorvastatin, esomeprazole, pantoprazole, clarithromycin, paroxetine (CR), risedronate, metaxalone, itraconazole, balsalazide, acitretin, verapamil, atovaquone, disulfiram, erythromycin, sulfasalazine, etc.

  7. Fed BE Studies • Confidence interval criteria now required for BE studies under fed conditions • General paucity of information on variability under fed conditions • Some drugs show much more variability under fed conditions than fasting conditions, making them HVDs (e.g., esomeprazole, pantoprazole, tizanidine) • May be more HVDs than generally appreciated

  8. Why Current 80-125% Criteria Are Not Appropriate For HVDs • Current criteria are appropriate for drugs with low to moderate variability because dose-to-dose variability within a patient is comparable to the width of the criteria • Current criteria are not appropriate for HVDs because dose-to-dose variability within a patient is much larger than the width of the criteria • HVDs are “wide therapeutic index” drugs – i.e., have shallow dose response curves, and wide safety margins • Modifying BE acceptance criteria for HVDs to reduce the number of participants in BE studies can be accomplished while maintaining assurance of safety and efficacy

  9. Different HVDs May Require Different Approaches – One Size Does Not Fit All

  10. Example 1: HVDs Not Subject to Significant Accumulation at Steady State • Half-life short with respect to dosing interval • Examples: omeprazole, tizanidine, azathioprine • Consider reference-scaled criteria for both Cmax and AUC • Dose-to-dose variability within a patient not smoothed out at steady state for either Cmax or AUC • Drug exhibits wide dose-to-dose variations in blood levels irrespective of chronic dosing • Same logic applies to HVDs not dosed chronically

  11. Example 2: HVDs Subject to Significant Accumulation at Steady State • Chronically used and with half-life long with respect to dosing interval • Examples: itraconazole, metaxalone, acitretin • Consider reference scaling criteria for Cmax only • Steady state T/R for AUC same as under single dose conditions (assuming linear kinetics) but variability in AUC will be reduced at steady state  drug may not have highly variable AUC at steady state • T/R for Cmax will be closer to unity at steady state than under single dose conditions, so adjusting criteria for Cmax could be accomplished without impacting assurance of safety/efficacy

  12. Example 2: HVDs Subject to Significant Accumulation at Steady State (cont’d) • Alternatively, could permit demonstration of bioequivalence with multiple dose steady state study • Not suitable for all drugs due to safety concerns, e.g., toxic drugs, inclusion of females, etc.

  13. Special Considerations

  14. Parallel Studies for Long Half-Life Drugs • For long half-life drugs, crossover studies may not be feasible, necessitating parallel designs • Powering parallel studies depends on between-subject variability, not within-subject variability • Between-subject variability is often large, necessitating large BE studies on such products, as for HVDs • High between-subject variability does not necessarily imply high within-subject variability (HVD) – instead it may be due to interindividual differences in absorption/metabolism (e.g., genetic polymorphism) • Multiple dose steady state studies generally not feasible • Consider reference-scaled criteria

  15. Pooling Data from Multiple Dosing Groups • Large n required for HVDs often requires two or more dosing groups • FDA currently requires a statistical test for poolability of data from multiple dosing groups (group x treatment interaction) • If interaction term is significant, then the groups may not be pooled • If the groups may not be pooled, each group is evaluated on its own for confidence interval criteria, and is likely to fail due to underpowering • This procedure results in discarding (and having to repeat) about 5% of studies based on random chance alone • Even if there were some underlying explanation for the statistical significance (e.g., differences in demographics among the dosing groups), there is no reason not to use the data from all dosing groups (they would be useable if the same subjects had been dosed in a single group)

  16. Conclusions • While current BE acceptance criteria are appropriate for drugs with ordinary variability, they are not appropriate for HVDs • Current BE acceptance criteria make it difficult or impossible to develop generic equivalents to some HVDs, effectively denying treatment to many patients • Practical, scientifically sound, alternative BE acceptance criteria could be implemented for HVDs to reduce BE study size while maintaining assurance of safety and efficacy • Different approaches may be needed for different types of drugs, depending particularly on accumulation following multiple dosing • Other, related situations (e.g., parallel studies, multiple dosing groups) should be considered in conjunction with any changes to acceptance criteria for HVDs

More Related