PKPD Modeling and Simulations to Support Biosimilar Development of Biphasic Insulin Aspart 30

This paper presents an analysis of data from a comparative study of biosimilarity in terms of pharmacokinetics and pharmacodynamics in healthy volunteers using a hyperinsulinemic euglycemic clamp for reference and test biphasic insulin aspart 30 (BIAsp 30). As a result of the study, one of the secondary pharmacodynamic (PD) endpoints did not satisfy the classical criterion of 80%–125% (the lower limit for PD parameter area under the glucose infusion rate–time curve [AUCGIR0−t${\rm{AUC}}_{{\rm{GIR}}_{0 - {\rm{t}}}$] turned out to be 79.5%). The main hypothesis explaining this result is that the sample size is insufficient to conduct a PD test with 90% statistical power, since the sample size has been calculated based on the coefficient of variation (CV) of pharmacokinetic (PK) parameters. To test this hypothesis, population PKPD (popPKPD) modeling and subsequent simulations of the required number of PD profiles were used. Two popPKPD models were constructed (a one‐compartment double simultaneous absorption model for PK and an effect compartment Emax model for PD) to describe the PKPD data of reference and test insulins. As a result, using real data along with model‐based simulation data, a biosimilarity test for PD was performed, and the lower limit for AUCGIR0−t${\rm{AUC}}_{{\rm{GIR}}_{0 - {\rm{t}}}$ became 82.6%, while the CV decreased from 31.7% to 24.1%. Thus, popPKPD modeling and simulations have been shown to be effective in interpreting and supporting the results of clinical biosimilarity trials.