Physiologically Based Pharmacokinetic Modeling to Identify Physiological and Molecular Characteristics Driving Variability in Drug Exposure

Abstract

Prospectively defining the physiological and molecular characteristics most likely driving between-subject variability (BSV) in drug exposure provides the opportunity to inform the assessment of biomarkers to account for this variability. A physiologically based pharmacokinetic (PBPK) model was constructed and verified for dabrafenib. This model was then used to evaluate the physiological and molecular characteristics driving BSV in dabrafenib exposure. The capacity to discriminate a steady-state dabrafenib trough concentration >48 ng/mL was also evaluated. The mean simulated/observed ratios for the parameters describing dabrafenib exposure in single-dose, multiple-dose, and drug-drug interaction studies were between 0.78 and 1.23. Multivariable analysis indicated that consideration of baseline weight, body mass index, and CYP2C8, CYP3A4, and P-gp abundance strongly predicts steady-state dabrafenib trough concentration above 48 ng/mL (ROC AUC = 0.94; accuracy = 86%). This is the first study to use a verified PBPK model to identify baseline physiological and molecular characteristics driving BSV in drug exposure.