Detection of data manipulation in bioequivalence trials.

ABSTRACT

In recent years regulators have documented how pharmaceutical companies or clinical research organisation can manipulate bioequivalence trial data for non-approvable formulations by performing an interim analysis followed by re-analysis of pharmacokinetic profiles under new subject aliases, with a switch of Test and Reference and/or dilutions. The net effect is that point estimates for failing products will be forced artifically towards 1 and that trials will pass the test for bioequivalence. This is not detectable by any pharmacopoeial method, and is not addressed by common assessment practices at agencies. This paper aims at demonstrating how the signals of such fraudulent study conduct can be detected. The approaches presented are called "Buster" and "SaToWIB" routines; these are computer programs that have been used extensively by regulators to detect signals of fraud but they have not been described in the public domain. The Buster routines visualize trends in the form of partial statistics, residual plots, cumulative confidence intervals, cumulative mean squared errors, and more. Runs tests on the sign of the residuals may constitute a potential test for the manipulation. It is noteworthy that in 2020, regulators in the European Union have publicly begun questioning trial validity on basis of PK profile similarity. The SaToWIB routines rank profile pairs according to numerical similarity on basis of an objective function. It is shown that the rank (as determined by score) is an indicator of fraud in that the actual fraud cases will have higher rank than if there were no relationship between rank and score. The paper also comments on the use of multivariate statistics and discusses the need for development of formal tests for manipulation in view of e.g. multiplicity.