Abstract Lurasidone is an antipsychotic drug used to treat schizophrenia and bipolar depression, primarily metabolized by cytochrome P450 3A4 (CYP3A4). Its pharmacokinetics (PK) can vary depending on CYP3A4 genetic polymorphisms and liver function, often requiring clinical dose adjustments. However, there is a lack of systematic tools for quantitatively predicting such interindividual variability. This study aimed to develop a physiologically based pharmacokinetic (PBPK) model of lurasidone that incorporates CYP3A4 polymorphisms and hepatic impairment to support dose optimization across clinical populations. The PBPK model was constructed using published in vitro and clinical PK data. Model validation was performed by comparing simulations with independent clinical trials. We conducted single‐ and multiple‐dose simulations reflecting CYP3A4 genotype (wild‐type vs. *15 allele) and hepatic impairment (Child‐Pugh A, B, C). Predicted exposures were compared with a reference population (CYP3A4 wild‐type, normal liver, 80 mg/day) to explore dose adjustment needs. Simulation results demonstrated increased exposure with worsening liver function, and decreased exposure in the presence of the *15 allele due to enhanced metabolism. Based on these results, reduced doses (20‐40 mg/day) were recommended for wild‐type patients with hepatic impairment, while higher doses (up to 240 mg/day) were needed for *15 carriers with normal liver function. Adjusted doses resulted in stable therapeutic exposures across groups. This PBPK model offers a quantitative strategy for individualizing lurasidone dosing based on genotype and hepatic function. It provides a valuable precision dosing tool to ensure safety and efficacy in vulnerable patient populations.
Jeong et al. (Sun,) studied this question.