1 / 11

Bioequivalence of Highly Variable (HV) Drugs: Clinical Implications Why HV Drugs are Safer

Bioequivalence of Highly Variable (HV) Drugs: Clinical Implications Why HV Drugs are Safer. Leslie Z. Benet, Ph.D. Professor of Biopharmaceutical Sciences University of California San Francisco FDA Advisory Committee for Pharmaceutical Science Rockville, MD April 14, 2004.

arlo
Download Presentation

Bioequivalence of Highly Variable (HV) Drugs: Clinical Implications Why HV Drugs are Safer

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. Bioequivalence of Highly Variable (HV) Drugs: Clinical ImplicationsWhy HV Drugs are Safer Leslie Z. Benet, Ph.D. Professor of Biopharmaceutical Sciences University of California San Francisco FDA Advisory Committee for Pharmaceutical Science Rockville, MD April 14, 2004

  2. The Current U.S. Procrustean Bioequivalence Guidelines • The manufacturer of the test product must show using two one-sided tests that a 90% confidence interval for the ratio of the mean response • (usually AUC and Cmax) of its product to that of • the reference product is within the limits of 0.8 and 1.25 using log transformed data. • (Procrustean  marked by an arbitrary, often ruthless disregard for individual differences or special circumstances.) • Note: BCS is a non-Procrustean advance • We should consider other non-Procrustean advances

  3. Bioequivalence IssuesWhat are we trying to solve? • For all drugs, but particularly for NTI drugs, practitioners need assurance that transferring a patient from one drug product to another yields comparable safety and efficacy (switchability). • For wide-therapeutic index, highly variable drugs we should not have to study an excessive number of patients to prove that two equivalent products meet preset (one size fits all) statistical criteria. • To give patients and clinicians confidence that a generic equivalent approved by the regulatory authorities will yield the same outcome as the innovator product.

  4. Why is meeting bioequivalence criteria a relatively minor concern for drugs with narrow therapeutic indices? • By definition, approved drugs • with narrow therapeutic • indices exhibit small • intrasubject variability. • If this were not true, patients • would routinely experience • cycles of toxicity and lack of • efficacy, and therapeutic • monitoring would be useless.

  5. NTIDrugs Frequently Proposed to Limit Generic Substitution CV% Inter Intra Subject Subject Carbamazepine 38 Conjugated Estrogens 42 14-15 Digoxin 52 Levothyroxine sodium 20 <20 Phenytoin sodium 51 10-15 Theophyllin sustained 31 11-14 release Warfarin sodium 53 6-11

  6. Individual Bioequivalence (IBE) (µT - µR)2 + D2 + (WT2 - WR2) <  WR2 • Initial Promises for IBE • Addresses the correct question (switchability) • Considers subject by formulation interaction (D ) • Incentive for less variable test product • Scaling based on variability of the reference product • both for highly variable drugs and for certain • agency-defined narrow therapeutic range drugs • Encourages use of subjects more representative of • the general population

  7. Re-examination of the Initial Promises for IBE • Addresses the correct question (switchability)—Necessity questionable • Considers subject by formulation interaction—Unintelligible parameter • Incentive for less variable test product—ABE with scaling could also solve this issue • Scaling based on variability of the reference product both for highly variable drugs and for certain agency-defined narrow therapeutic range drugs– ABE with scaling could also solve this issue • Encourages use of subjects more representative of the general population—Failed

  8. Highly Variable Drugs (CV>30%) For wide-therapeutic index highly variable drugs we should not have to study an excessive number of patients to prove that two equivalent products meet preset (one size fits all ) statistical criteria. This is because ,by definition, highly variable approved drugs must have a wide therapeutic index, otherwise there would have been significant safety issues and lack of efficacy during Phase 3 Highly variable narrow therapeutic index drugs are dropped in Phase 2 since it is not possible to prove either efficacy or safety.

  9. ProgesteroneThe Poster Drug for High Variability • A repeat measures study of Prometrium® 2x200 mg capsules in 12 healthy post-menopausal females yielded: • Intrasubject CV for AUC of 61% • Intrasubject CV for Cmax of 98% • A generic company calculated that a 2 period crossover BE study for Progesterone Capsules, 200 mg would require dosing in 300 postmenopausal women to achieve adequate statistical power

  10. Recommendationsof the FDA Expert Panel on Individual Bioequivalence to this Advisory Committee on November 21, 2001 • Sponsors may seek bioequivalence approval using either ABE or IBE (with SxF deleted) • Scaling of ABE should be considered. • If an IBE study is carried out and the test product fails, the data or a subset of the data may not be reanalyzed by ABE for approval • A point estimate criteria on mean AUCs of ±15% and on mean Cmax of ±20% should be required for both ABE and IBE. • Consideration should be given for narrower point estimate criteria for NTI drugs (e.g., AUC ±10%, Cmax ±15%)

  11. Recommendations • • Methodology should be developed to allow approvals based on weighting of average bioequivalence analyses for highly variable drugs (i.e., WR> 30%). • • A point estimate criteria on mean AUCs of ±10% and on mean Cmax of ±15% should be required for NTI drugs where WR  20%. • • A point estimate criteria on mean AUCs of ±15% and on mean Cmax of ±20% should be required for all other drugs, including NTI drugs where WR> 20%.

More Related