Two-stage designs versus European scaled average designs in bioequivalence studies for highly variable drugs: Which to choose?

The Global Bioequivalence Harmonisation Initiative (GBHI): Report of the fifth international EUFEPS/AAPS conference

The series of conferences of the Global Bioequivalence Harmonisation Initiative (GBHI) was started in 2015 by the European Federation for Pharmaceutical Sciences (EUFEPS). All GBHI meetings so far were co-organised together with the American Association of Pharmaceutical Scientists (AAPS). Beginning with the 3rd workshop US-FDA joined as co-sponsor - to support global harmonisation of regulatory recommendations for bioequivalence (BE) assessment. At the 5th GBHI conference, the following BE topics were intensively discussed, and the following main conclusions were drawn: (1) Statistical considerations for BE assessment in specific situations covering scaling approaches for highly variable drug (HVD) products, two-stage adaptive design and opportunities of modelling and simulation to support BE: even though special BE study concepts like adaptive designs are not often used in practise so far, a majority of the workshop participants were in favour of a more frequent application of such approaches. The regulatory conditions relevant in this context need further concretisation and harmonisation between the regions. Moreover, modelling and simulation were considered as a promising and evolving approach, also for BE development programmes. (2) Fed versus fasting conditions in BE trials: Findings that BE between generic products could be confirmed only after fasted administration but failed under fed conditions seem more an exception than the rule. Obviously, BCS class IV compounds are most problematic in this context. Differences in critical excipients such as surfactants or pH-modifiers may be relevant reasons for different sensitivity for interactions in fasted versus fed conditions. Consequently, such deviations in composition of generic preparations should be avoided. Moreover, confirmation of BE may be generally difficult comparing different dosage forms, such like capsules versus tablets, especially in fed state. (3) BE assessment of locally acting drug products applied topically to the skin: Appropriateness and potential benefit of in-vitro tests as alternatives to clinical efficacy studies have been comprehensively discussed. In addition to the already well-established in-vitro release and permeation tests, other techniques were suggested, e.g., Raman spectroscopy or dermal open flow microperfusion. Validation of those methods is challenging and, despite significant progress already achieved during previous years, more research is needed before they may be fully accepted for regulatory purposes. (4) BE evaluation of narrow therapeutic index (NTI) drugs: The discrepancies amongst regulatory agencies in necessity of tighter BE acceptance ranges, the recommendations for inclusion of peak and total drug exposure into BE assessment with more restrictive criteria and the importance of comparison of the product-related within-subject variability for NTI drugs were debated. Arguments in favour and against the different approaches were presented and discussed but need further consideration before harmonisation can be achieved. The highly interactive meeting and extensive exchange between regulators and scientists from industry and academia resulted in useful progress in open BE issues and supported the goal of science-driven harmonisation.

An iterative method to protect the type I error rate in bioequivalence studies under two-stage adaptive 2×2 crossover designs

Bioequivalence studies are the pivotal clinical trials submitted to regulatory agencies to support the marketing applications of generic drug products. Average bioequivalence (ABE) is used to determine whether the mean values for the pharmacokinetic measures determined after administration of the test and reference products are comparable. Two-stage 2×2 crossover adaptive designs (TSDs) are becoming increasingly popular because they allow making assumptions on the clinically meaningful treatment effect and a reliable guess for the unknown within-subject variability. At an interim look, if ABE is not declared with an initial sample size, they allow to increase it depending on the estimated variability and to enroll additional subjects at a second stage, or to stop for futility in case of poor likelihood of bioequivalence. This is crucial because both parameters must clearly be prespecified in protocols, and the strategy agreed with regulatory agencies in advance with emphasis on controlling the overall type I error. We present an iterative method to adjust the significance levels at each stage which preserves the overall type I error for a wide set of scenarios which should include the true unknown variability value. Simulations showed adjusted significance levels higher than 0.0300 in most cases with type I error always below 5%, and with a power of at least 80%. TSDs work particularly well for coefficients of variation below 0.3 which are especially useful due to the balance between the power and the percentage of studies proceeding to stage 2. Our approach might support discussions with regulatory agencies.

A Three-Treatment Two-Stage Design for Selection of a Candidate Formulation and Subsequent Demonstration of Bioequivalence

This paper introduces a two-stage bioequivalence design involving the selection of one out of two candidate formulations at an initial stage and quantifies the overall power (chance of ultimately showing bioequivalence) in a range of scenarios with CVs ranging from 0.1 to 1. The methods introduced are derivates of the methods invented in 2008 by Diane Potvin and co-workers (Pharm Stat. 7(4): 245-262, 2008). The idea is to test the two candidate formulations independently in an initial stage, making a selection of one of these formulations basis of the observed point estimates, and to run, when necessary, a second stage of the trial with pooling of data. Alpha levels are identified which are shown to control the maximum type I error at 5%. Results, expressed as powers and sample sizes, are also published for scenarios where the two formulations are far apart in terms of the match against the reference (one GMR being 0.80, the other GMR being 0.95) and in scenarios where the two test formulations have an actual better match (one GMR being 0.90, the other GMR being 0.95). The methods seem to be compliant with wording of present guidelines from EMA, FDA, WHO, and Health Canada. Therefore the work presented here may be useful for companies developing drugs whose approval hinges on in vivo proof of bioequivalence and where traditional in vitro screening methods (such as dissolution trials) may have poor ability to predict the best candidate.

10th Anniversary of a Two-Stage Design in Bioequivalence. Why Has it Still Not Been Implemented?

PURPOSE

In 2010 the European Medicines Agency allowed a two-stage design in bioequivalence studies. However, in the public domain there are mainly articles describing the theoretical and statistical base for the application of the two-stage design. One of the reasons seems to be the lack of practical guidance for the Sponsors on when and how the two-stage design can be beneficial in bioequivalence studies.

METHODS

Different variants with positive and negative outcomes have been evaluated, including a pivotal study, pilot + pivotal study and two-stage study. The scientific perspective on the two-stage bioequivalence study has been confronted with the industrial one.

RESULTS

Key information needed to conduct a bioequivalence study - such as in vitro data and pharmacokinetics - have been listed and organized into a decision scheme. Advantages and disadvantages of the two-stage design have been summarized.

CONCLUSION

The use of the two-stage design in bioequivalence studies seems to be a beneficial alternative to the 2 × 2 crossover study. Basic information on the properties of the active substance and the characteristics of the drug form are needed to make an initial decision to carry out the two-stage study.

Pharmacokinetics and Bioequivalence of Clopidogrel Hydrogen Sulfate Tablets in Fed and Fasted Conditions: An Open-Label, Randomized, Semireplicated Crossover Study in Healthy Chinese Volunteers

Clopidogrel is an antiplatelet drug with high intraindividual variability in systemic exposure and efficacy. It has been used for treating atherosclerosis and acute coronary syndrome and in preventing stent restenosis and thrombotic complications after stent implantation in clinical practice for nearly 20 years. In this study we aimed to evaluate the bioequivalence of 2 clopidogrel hydrogen sulfate formulations (75-mg tablets) under fed (n = 66) and fasted (n = 66) conditions by using the reference-scaled average bioequivalence method. An open-label, randomized, 3-sequence and 3-period crossover (3×3), semireplicated study was designed and conducted. Clopidogrel concentration of plasma samples was measured by high-precision liquid chromatography and tandem mass spectrometry. The pharmacokinetic parameters were derived by a noncompartmental model. In the fed condition the geometric least-squares mean ratios of peak concentration (C_max ) and area under the concentration-time curve (AUC_0-t ) were, respectively, 103.38% and 98.97%, and the corresponding 90%CIs were 95.68% to 111.70% and 94.67% to 103.47%. In the fasted condition the geometric least squares mean ratios of C_max and AUC_0-t were, respectively, 106.53% and 105.77%, and the corresponding 90%CIs were 97.62% to 116.25% and 96.96% to 115.38%. According to the criteria for bioequivalence (80.00% to 125.00%), the test formulations of clopidogrel and Plavix were determined to be bioequivalent.

Bayesian Two-Stage Adaptive Design in Bioequivalence

Bioequivalence (BE) studies are an integral component of new drug development process, and play an important role in approval and marketing of generic drug products. However, existing design and evaluation methods are basically under the framework of frequentist theory, while few implements Bayesian ideas. Based on the bioequivalence predictive probability model and sample re-estimation strategy, we propose a new Bayesian two-stage adaptive design and explore its application in bioequivalence testing. The new design differs from existing two-stage design (such as Potvin's method B, C) in the following aspects. First, it not only incorporates historical information and expert information, but further combines experimental data flexibly to aid decision-making. Secondly, its sample re-estimation strategy is based on the ratio of the information in interim analysis to total information, which is simpler in calculation than the Potvin's method. Simulation results manifested that the two-stage design can be combined with various stop boundary functions, and the results are different. Moreover, the proposed method saves sample size compared to the Potvin's method under the conditions that type I error rate is below 0.05 and statistical power reaches 80 %.