Modelling Exposure-Driven Adverse Event Time Courses in Oncology Exemplified by Afatinib.

Models were developed to characterize the relationship between afatinib exposure and diarrhoea and rash/acne adverse event (AEs) trajectories, and their predictive ability was assessed. Based on pooled data from seven phase II/III clinical studies including 998 patients, mixed-effects models for ordered categorical data were applied to describe daily AE severity. Clinical trial simulation (CTS) aided by trial execution models was used for internal and external model evaluation. The final exposure-safety model consisted of longitudinal logistic regression models with first-order Markov elements for both AEs. Drug exposure was included as daily AUC, and drug effects on the AEs were correlated. CTS allowed adequate prediction of maximum AE grades and AE severity time courses, but over-estimated the proportion of AE-dependent dose reductions and discontinuations. Both diarrhoea and rash/acne were correlated with afatinib exposure. The developed modelling framework allows prospective comparison of dosing strategies and study designs with respect to safety. This article is protected by copyright. All rights reserved.