SOME ISSUES ON THE DETERMINATION OF BIOEQUIVALENCE FOR HIGHLY VARIABLE DRUGS Laszlo Endrenyi University of Toronto Laszlo Tothfalusi Semmelweis University.

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SOME ISSUES ON THE DETERMINATION OF BIOEQUIVALENCE FOR HIGHLY VARIABLE DRUGS Laszlo Endrenyi University of Toronto Laszlo Tothfalusi Semmelweis University of Budapest FDA/CDER Advisory Committee on Pharmaceutical Sciences Rockville, MD October 6, 2006

SYNOPSIS 1. What kinds of replicate designs should be applied? 2. Should there be a constraint on the estimated ratio of geometric means?

USUAL METHOD OF EVALUATION: UNSCALED AVERAGE BIOEQUIVALENCE 1/BEL  GMR  BEL BEL: BE limit - Usually 1.25 GMR: Ratio of geometric means - lgBEL  log(GMR)  lgBEL - lgBEL  m T - m R  lgBEL lgBEL: logarithm of BEL m T, m R : Estimated logarithmic means

AN APPROACH FOR HIGHLY VARIABLE DRUGS: SCALED AVERAGE BIOEQUIVALENCE Difference between logarithmic means is normalized by estimated variation: - lgBEL sc  (m T - m R )/s  lgBEL sc A general procedure was suggested for setting BE limits (BEL sc ) Advantages: - Statistical power is independent of variation - Statistical power is, with same sample size, much higher than of unscaled average BE - Interpretation: Compare expected change due to switching with expected difference between replicate administrations - Interpretation: Standardized effect size, as in clinical comparisons

REPLICATE STUDY DESIGNS FOR APPLYING SCALED AVERAGE BIOEQUIVALENCE Difference between logarithmic means is normalized by estimated variation: - lgBEL sc  (m T - m R )/s  lgBEL sc s: Often regarded as within-subject variation of reference product (s WR ) For estimating s WR a single-sequence 3 period design could be sufficient: RRT

REPLICATE STUDY DESIGNS FOR APPLYING SCALED AVERAGE BIOEQUIVALENCE An additional goal: To compare variations of the two drug products: s WT /s WR Could identify highly variable drug products Replications of both RR and TT are required For example: RRT TTR

REPLICATE STUDY DESIGNS FOR APPLYING SCALED AVERAGE BIOEQUIVALENCE Refine the additional goal: To compare variations of the two drug products: s WT /s WR within the same subject More effective identification of highly-variable drug products Also: can identify (some) outlying observations Example of study design: RTRT TRTR

REPLICATE STUDY DESIGNS FOR APPLYING SCALED AVERAGE BIOEQUIVALENCE NOTE: 3- and 4-period designs require approximately the same number of observations

SHOULD THERE BE A CONSTRAINT ON GMR? Concern about possibly large deviations between estimated logarithmic means [i.e., about log(GMR)] L. Benet, AAPS Workshop on Individual BE, Concern about interpretation to physicians

SHOULD THERE BE A CONSTRAINT ON GMR? Larger deviation between the (logarithmic) means arises as a natural, direct consequence of the higher variability Larger deviations occur at higher variations They would be truncated by GMR constraint Moreover:

QUALITY CONTROL OR THERAPEUTIC SURROGATE? QUALITY CONTROLTHERAP. SURROGATE HIGH SENSITIVITYCLINICAL RELEVANCE HIGH STATISTICAL POWER Young, healthy (male) volunteers * Heterogeneous study popul'n * Single dosing Steady state Cmax/AUC * Cmax * Parent drug Active metabolite * Recommendations of FDA Does one guidance/method satisfy both goals? BioInternational 1994:: Both! But: Ambivalence

Endpoint Goal of the study Therapeutic Quality Control Equivalence = New Drugs Generic Drugs Pharmacodynamic and Therapeutic Pharmacokinetic (AUC, Cmax, Css) Phase III or Phase IV calInhalation devices Nasal and dermatological products Product labelling trials: Interaction and food effect Patient subpopulation trials: Renal, hepatic impairment New ER formulations Dose linearity Generic drug development (including food effect)

SHOULD THERE BE A CONSTRAINT ON GMR? Possible concern about large estimated GMR may possibly apply to the introduction of generic products, but NOT during the development of new drugs. Therefore: a secondary regulatory criterion should NOT be generally invoked

CONCLUSIONS 3- or preferably 4-period study designs in which both the reference and test products are replicated (RR and TT), enable the comparison of within-subject variations and the identification of highly-variable drug products. A constraint of the estimated ratio of geometric means is not warranted scientifically or, generally, for the sake of public relations.