BioMetrics.com

Replicate Designs and Average, Individual, and Population BioEquivalence: II. Simulation Assessment of Performance of Novel Procedures and the Proposed FDA Methods for Bioequivalence Assessment

Scott D Patterson and Byron Jones

Abstract. Since the early 1990’s, average bioequivalence (ABE) has served as the international standard for demonstrating that two formulations of drug product will provide the same therapeutic benefit and safety profile. Population (PBE) and Individual (IBE) bioequivalence have been the subject of intense international debate since methods for their assessment were proposed in the late 1980’s. Guidance has been proposed by the FDA for the implementation of these techniques in the pioneer and generic pharmaceutical industries. As of the year 2002, no consensus among regulators, academia, and industry has been established on the use of the IBE and PBE metrics.

The need for more stringent bioequivalence criteria has not been demonstrated, and it is known that the PBE and IBE criteria proposed by FDA are actually less stringent under certain conditions. The statistical properties of method-of-moments and restricted maximum likelihood modelling in replicate designs will be summarised, and the application of these techniques in the assessment of ABE, IBE, and PBE are considered based on a database of 51 replicate design studies and using simulation.

The constrained REML procedure recommended by FDA Guidance (2001) using Satterthwaite (1941-1946) or Kenward-Roger (1997) degrees of freedom for ABE testing in replicate designs results in biased estimates for variance components on occasion; however, it uniformly constrains the rate of Type I error (of more immediate concern to regulators and consumers) to be less than 5% in ABE testing.

It is concluded that the Cornish-Fisher expansion (Hyslop et al., 2000) will adequately serve for IBE and PBE testing except in the presence of missing data where method-of-moments estimates become biased. In situations where missing data and the resulting bias in estimates are of great concern, an asymptotic testing procedure using REML (though conservative) may be used to assess inference. While valid statistical tests for PBE have been developed under the proposed FDA standards, this procedure quite easily allows for market access with very large changes in mean exposure for highly variable drug products. The potential for threats to public health generated by generic-to-generic switching should not be underestimated if IBE is used to allow market access. We recommend that the FDA reconsider the use of the IBE and PBE procedures for market access and not allow their use without major modification
to ensure patient safety and efficacy.

Pharmacokinetic Bridging and ICH-E5: Retrospective and Simulation Assessment of Proposals for Pharmacokinetic Equivalence Assessment between Independent Populations

Scott D Patterson and Byron Jones

Abstract: A topic associated with bioequivalence is considered; that of comparing rate and extent of exposure between differing ethnic groups as described in ICH-E5 (1998). The properties of the population bioequivalence metric and an alternative metric will be characterised in small and large samples from parallel group studies. Inference will be illustrated using data from a recent submission and simulation studies. The emphasis of this report is on the practical statistical design and use of pharmacokinetic data for ICH-E5 (1998) bridging assessment and for enhancing the understanding of the role of this data in enabling informed clinical development.

The Construction of Universally Optimal Uniform Cross-over Designs

Simon Bate and Byron Jones

ABSTRACT. In this report we derive the conditions that a uniform cross-over
design must satisfy to be optimal for estimating treatment and first-order carryover effects. In particular we use the notion of universal optimality introduced by Kiefer (1975). Existing appropriate methods are reviewed and new methods of construction are described. The constructed designs fall into four families, which include the balanced and strongly balanced designs as special cases: the remaining designs we refer to as nearly strongly balanced, a term first introduced by Kunert (1983). The nearly strongly balanced designs form an important family of cross-over designs which provide designs where balanced or strongly balanced designs do not exist. These designs impose no limits on the number of periods and subjects, other than that these must be a multiple of the number of treatments. Some illustrative examples are included.