Determination of Vatiquinone Drug‐Drug Interactions, as CYP450 Perpetrator and Victim, Using Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation

Abstract

Vatiquinone, a 15‐lipoxygenase inhibitor, is in development for patients with Friedreich's ataxia. Physiologically based pharmacokinetic (PBPK) modeling addressed drug‐drug interaction gaps without additional studies. A PBPK model (Simcyp Simulator version 21, full model) was developed using parameters obtained from in vitro studies, in silico estimation and optimization, and two clinical studies. A venous blood dosing model best characterized vatiquinone lymphatic absorption. Apparent oral clearance (CL/F) was used to optimize intrinsic clearance (CL _int). Intestinal availability (F _g) was estimated using the hybrid flow term (Q _gut), unbound fraction in the enterocytes (fu _gut), and gut intrinsic metabolic clearance (CLu _G,int). Renal clearance (CL _R) was set to zero. Assuming an F _a of 1, CYP3A4 contribution (fm _CYP3A4) was further optimized. The PBPK model was verified with two clinical studies and demonstrated that it adequately characterized vatiquinone PK. As a perpetrator, the model predicted no risk for vatiquinone to significantly alter the drug exposures of CYP3A4 and CYP1A2 substrates as evident bynegligible reduction in both midazolam and caffeine area under the curve (AUC) _inf and C _max. As a victim, the model predicted that vatiquinone exposures are weakly influenced by moderate CYP3A4 inhibitors and inducers. With fluconazole coadministration, vatiquinone AUC _inf and C _max increased by nearly 50% and 25%, respectively. With efavirenz coadministration, vatiquinone AUC _inf and C _max decreased by approximately 20% and 10%, respectively. Results suggested that vatiquinone does not significantly impact CYP3A4 and CYP1A2 substrates and that moderate CYP3A4 inhibitors and inducers weakly impact vatiquinone AUC.