Impact of model misspecification on model-based tests in PK studies with parallel design: real case and simulation studies

• Published in: Journal of pharmacokinetics and pharmacodynamics Vol. 49; no. 5; pp. 557 - 577
• Main Authors: Guhl, Mélanie, Mercier, François, Hofmann, Carsten, Sharan, Satish, Donnelly, Mark, Feng, Kairui, Sun, Wanjie, Sun, Guoying, Grosser, Stella, Zhao, Liang, Fang, Lanyan, Mentré, France, Comets, Emmanuelle, Bertrand, Julie
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.10.2022; Springer Nature B.V; Springer Verlag
• Subjects: Alzheimer's disease; Biochemistry; Biomedical and Life Sciences; Biomedical Engineering and Bioengineering; Biomedicine; Life Sciences; Monoclonal antibodies; Neurodegenerative diseases; Original Paper; Pharmaceutical sciences; Pharmacokinetics; Pharmacology/Toxicology; Pharmacy; Veterinary Medicine/Veterinary Science; Equivalence test; Non-compartmental analysis; Sparse design; Non-linear mixed effects models; Pharmacokinetics
• ISSN: 1567-567X; 1573-8744; 1573-8744
• DOI: 10.1007/s10928-022-09821-z

This article evaluates the performance of pharmacokinetic (PK) equivalence testing between two formulations of a drug through the Two-One Sided Tests (TOST) by a model-based approach (MB-TOST), as an alternative to the classical non-compartmental approach (NCA-TOST), for a sparse design with a few time points per subject. We focused on the impact of model misspecification and the relevance of model selection for the reference data. We first analysed PK data from phase I studies of gantenerumab, a monoclonal antibody for the treatment of Alzheimer’s disease. Using the original rich sample data, we compared MB-TOST to NCA-TOST for validation. Then, the analysis was repeated on a sparse subset of the original data with MB-TOST. This analysis inspired a simulation study with rich and sparse designs. With rich designs, we compared NCA-TOST and MB-TOST in terms of type I error and study power. With both designs, we explored the impact of misspecifying the model on the performance of MB-TOST and adding a model selection step. Using the observed data, the results of both approaches were in general concordance. MB-TOST results were robust with sparse designs when the underlying PK structural model was correctly specified. Using the simulated data with a rich design, the type I error of NCA-TOST was close to the nominal level. When using the simulated model, the type I error of MB-TOST was controlled on rich and sparse designs, but using a misspecified model led to inflated type I errors. Adding a model selection step on the reference data reduced the inflation. MB-TOST appears as a robust alternative to NCA-TOST, provided that the PK model is correctly specified and the test drug has the same PK structural model as the reference drug.