Risk of false pharmaceutical equivalence (non-equivalence) decisions due to measurement uncertainty

J Pharm Biomed Anal. 2021 Sep 10:204:114269. doi: 10.1016/j.jpba.2021.114269. Epub 2021 Jul 16.

Abstract

The pharmaceutical equivalence between test (generic or similar) and reference medicine is evaluated through in vitro quality tests involving multiple compliance parameters. Despite efforts to ensure the reliability of the analytical results obtained in the pharmaceutical equivalence studies, measurement uncertainties lead to a risk of false decisions. Thus, the aim of this work was to evaluate the measurement uncertainties associated with the analytical results obtained in the pharmaceutical equivalence studies of different pharmaceutical forms and to estimate the risks of false decisions in the evaluation of pharmaceutical equivalence. The measurement uncertainties associated with the test results were evaluated using the bottom-up and top-down approaches. The consumer's or producer's combined particular risks and combined total risks were estimated using the Monte Carlo method implemented in MS-Excel spreadsheet (available as supplemental material). Considering the seven pharmaceutical equivalence studies performed in this work, three studies were not conclusive (risk of false pharmaceutical equivalence decisions higher than 5 %). Moreover, we concluded pharmaceutical equivalence and pharmaceutical non-equivalence in one and three studies, respectively. The particular and total combined risks are useful to make decisions regarding the evaluation of pharmaceutical equivalence between the test (generic or similar) and reference medicines. Regulatory bodies and pharmaceutical equivalence centers are very interested in the estimation of the risks of false decisions, particularly to evaluate the quality of medicines that are not submitted to bioequivalence studies.

Keywords: Conformity assessment; Measurement uncertainty; Pharmaceutical equivalence; Risk of false decisions.

MeSH terms

  • Drugs, Generic*
  • Monte Carlo Method
  • Reproducibility of Results
  • Uncertainty

Substances

  • Drugs, Generic