A physiologically-based pharmacokinetic precision dosing approach to manage dasatinib drug–drug interactions

Abstract

Dasatinib, a second-generation tyrosine kinase inhibitor, is approved for treating chronic myeloid and acute lymphoblastic leukemia. As a sensitive cytochrome P450 (CYP) 3A4 substrate and weak base with strong pH-sensitive solubility, dasatinib is susceptible to enzyme-mediated drug–drug interactions (DDIs) with CYP3A4 perpetrators and pH-dependent DDIs with acid-reducing agents. This work aimed to develop a whole-body physiologically-based pharmacokinetic (PBPK) model of dasatinib to describe and predict enzyme-mediated and pH-dependent DDIs, to evaluate the impact of strong and moderate CYP3A4 inhibitors and inducers on dasatinib exposure and to support optimized dasatinib dosing. Overall, 63 plasma profiles from perorally administered dasatinib in healthy volunteers and cancer patients were used for model development. The model accurately described and predicted plasma profiles with geometric mean fold errors (GMFEs) for area under the concentration–time curve from the first to the last timepoint of measurement (AUC_last) and maximum plasma concentration (C_max) of 1.27 and 1.29, respectively. Regarding the DDI studies used for model development, all (8/8) predicted AUC_last and C_max ratios were within twofold of observed ratios. Application of the PBPK model for dose adaptations within various DDIs revealed dasatinib dose reductions of 50%–80% for strong and 0%–70% for moderate CYP3A4 inhibitors and a 2.3–3.1-fold increase of the daily dasatinib dose for CYP3A4 inducers to match the exposure of dasatinib administered alone. The developed model can be further employed to personalize dasatinib therapy, thereby help coping with clinical challenges resulting from DDIs and patient-related factors, such as elevated gastric pH.