AUTHOR=Shao Huarui , Tao Yi , Tang Chengyong 

TITLE=Factors influencing bioequivalence evaluation of insulin biosimilars based on a structural equation model

JOURNAL=Frontiers in Pharmacology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2023.1143928

DOI=10.3389/fphar.2023.1143928

ISSN=1663-9812

ABSTRACT=Objective: This study aimed to explore the factors affecting the bioequivalence of test and reference insulin preparations, so as to provide a scientific basis for the consistency evaluation of the quality and efficacy of insulin biosimilars.
Methods: Randomized, open, two-sequence, single-dose, crossover design was used in this study, subjects were randomly divided into TR or RT groups in equal proportion. Glucose infusion rate and blood glucose were measured by a 24h glucose clamp test to evaluate the pharmacodynamic parameters of the preparation. Plasma insulin glargine concentration was determined by liquid chromatography-mass spectrometry (LC-MS/MS) to evaluate pharmacokinetic parameters. WinNonlin 8.1 and SPSS 23.0 were applied to PK/PD parameters calculation and statistical analysis. The structural equation model (SEM) was constructed to analyze the influencing factors of bioequivalence by using Amos 24.0.
Results: A total of 177 healthy male subjects aged 18 to 45 years were analyzed. Subjects were assigned to equivalent group (N=55) and non-equivalent group (N=122) by bioequivalence results according to EMA guideline. Univariate analysis showed statistical differences in albumin, creatinine, Tmax, bioactive substance content and adverse events between the two groups. In the structural equation model, adverse events (β=0.342, p<0.001) and bioactive substance content (β=-0.189, p=0.007) had significant impacts on bioequivalence of two preparations, bioactive substance content significantly affected adverse events (β=0.200, p=0.007).
Conclusion: a multivariate statistical model was used to explore the influencing factors of the bioequivalence of two preparations. According to the result of structural equation model, we proposed adverse events and bioactive substance content should be optimized in consistency evaluation of quality and efficacy of insulin biosimilars. Furthermore, bioequivalence trials of insulin biosimilars  should strictly obey inclusion and exclusion criteria to ensure the consistency of subjects and avoid confounding factors affecting the equivalence evaluation.