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Byline: Shubha. Rani
The design, performance and evaluation of bioavailability and bioequivalence have evolved over the last two decades. Bioequivalence (BE) means the absence of a greater-than-allowable difference between the systemic bioavailability of a test product and that of a reference product. Due to efforts by academia, the pharmaceutical industry and health authorities, there is far-reaching consensus on essential questions of bioequivalence trials which have been reflected in the many regulatory guidelines. Despite the introduction and wide acceptance of stringent requirements for bioequivalence studies, there is, however, increasing awareness that some fundamentals of bioequivalence assessment need to be reconsidered in principal. This includes several debatable issues such as practical strategies for bioequivalence of highly variable drugs, drugs with long half life, drugs under genetic polymorphic metabolism, biopharmaceuticals and endogenous substances; single bioequivalence range for all drugs; inclusion of female volunteers; individual versus average bioequivalence; metrics of absorption; etc. This article is an attempt to highlight current thinking on issues in bioequivalence.
The design, performance, and evaluation of bioavailability and bioequivalence (BE) studies have received significant attention from academia, the pharmaceutical industry, and health authorities[sup] ,,,, over the last decade, and there has been an attempt to achieve international harmonization of regulatory requirements. According to the FDA Orange Book, test and reference products are said to be bioequivalent 'if the rate and extent of absorption of the test drug do not show a significant difference from the rate and extent of absorption of the reference drug, when administered at the same molar dose of the therapeutic ingredient under similar experimental conditions in either single dose or multiple doses.' The International Consensus statement is: 'two pharmaceutical products are considered to be equivalent when their bioavailabilities, from the same molar dose, are so similar that they are unlikely to produce clinically relevant differences in therapeutic and / or adverse effects.'
Approaches for testing the BE of drug formulations have been evolving over the past quarter century. Consequently, several resolved and unresolved issues pertaining to practical strategies for highly variable drug BE studies, individual vs average BE, metrics of absorption, shape analysis in single and multiple dose BE studies, statistical comparison of intra-subject variability of test and reference products in BE studies, special BE problems with biotechnology-derived drugs, problems in BE of endogenous substance and long half-life drugs, pharmacokinetic and clinical pharmacodynamic considerations in BE, and problems in BE of drugs under genetic polymorphic metabolism have been the focus of discussion and debate.
Scientific discussions between academia, the pharmaceutical industry, and health authorities were encouraged during workshops and conferences organized by the various organizations to resolve these issues. [sup] ,,,, Due to these efforts, there is a far-reaching consensus on the essential questions of BE trials. All these aspects have been reflected in the many regulatory guidelines. A glimpse of the statistical evolution in BE trials has been given in our earlier paper.[sup]  This article is an attempt to highlight the current thinking on some of the above mentioned issues.
Highly Variable Drugs
The definition of high intra-subject variability of pharmacokinetic data, proposed at the Bio-International Conference 1989 and confirmed at the one in 1992[sup]  is as follows: 'Drugs that exhibit intra-subject variability of> 30% (CV[sub] ANOVA ) are to be classified as highly variable.' The assessment of BE for highly variable drugs has been very difficult and problematic.[sup] , One of the consequences of high intra-subject variability is that an unwieldy number of subjects may be required to provide an adequate statistical power, even when both the formulations are bioequivalent. With the common sample size of 20 in a BE study, with a = 0.05 and intra-subject CV = 15%, the possibility of a true ratio of 100% (AUC or C[sub] max ) meeting the 90% confidence interval criterion is about 100%. However, when intra-subject CV increases to 30% (or higher), the possibility of a true ratio of 100% (AUC or C[sub] max ) meeting the 90% confidence interval criterion (with the sample size of 20), reduces to 45% (or less); to attain only a 90% chance of passing the BE criteria for intra-subject variability of 30%, 40 subjects have to be recruited. The sample sizes become very large as the %CV increases (e.g., if the %CV is 45%, the required number of subjects to show BE is 88).[sup] 
At the Bio-International '92 Conference,[sup]  to overcome this problem, it was suggested to investigate the highly variable drug products in steady-state situations. This suggestion was the outcome of experience gained from several BE studies; e.g., verapamil was examined in a single dose vs multiple dose (replicate design) study and it was observed that coefficients of variation were 31% for AUC and 32% for C[sub] max for the single dose study; however, it was 19% for AUC and 23% for C[sub] max in the multiple dose study. In another study, a reduction from 26% to 18% in the coefficient of variation of AUC was observed from the single to the multiple dose study for nifedipine.[sup] 
The AAPS/FDA Workshop's (Crystal City, Arlington, VA, March 6-8, 1995) report stated that, 'For some highly variable drugs and drug products, the bioequivalency standard should be modified by changing the BE limits while maintaining the current confidence interval at 90%.' The intention was to scale the BE limits based on the intra-subject variance associated with the reference formulation, while maintaining the consumer risk at 5%.[sup]  This requires the estimation of intra-subject variation. In a test vs reference, two-period cross-over design, the residual error term includes several components:
*Intra-subject variation in ADME (with a component of assay variability) *Intra-formulation variation (tablet-to-tablet variation) *A subject-by-formulation interaction term *Other random variations, not explained by the ANOVA model
If a solution of the drug is given on two occasions in a two-period cross-over design, the residual error contains no intra-formulation variations and no subject-by-formulation interaction term. Consequently, the residual error gives the intra-subject variation. Thus, a pilot study would be needed to provide estimates of intra-subject variability to scale the BE limits. The drawback of this method is that the scaled BE criterion relaxes the BE requirements for highly variable drugs but imposes more stringent BE requirements on low variability drugs with a wide therapeutic window.[sup] , The limited sampling method[sup]  (LSM) and metabolite assessment[sup]  were also suggested to determine the BE of highly variable drugs. However, severely limited utility of these methods[sup] , have been shown by researchers. Hence, there is a need for new concepts in the design and analysis of BE experiments for drugs with high intra-subject variability.
Average vs Individual Bioequivalence
It is well known now that two formulations are considered bioequivalent if the confidence interval of the 'test/reference' ratio of the geometric means (in the population) of the bioavailability characteristics under investigation lie in the BE range of 80-125%, i.e., the BE of two drug formulations is determined by the drug regulatory authorities in terms of the mean responses following administration of test and reference formulations. This definition of the BE has been termed 'average BE.'
Anderson and Hauck[sup]  and Sheiner[sup]  defined two situations. In the first, the subject is naive to the drug and has not taken any of its formulations. Here the overall efficacy and safety of the drug is important, while it has already been established for the reference …