Escitalopram Dose Optimization During Pregnancy: A PBPK Modeling Approach

妊娠期艾司西酞普兰剂量优化:基于生理药代动力学模型的方法

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Abstract

Background/Objectives: Escitalopram, a first-line antidepressant, is primarily metabolized by CYP2C19. Its pharmacokinetics are altered during pregnancy. This study aims to predict maternal and fetal exposure to escitalopram during pregnancy and to propose safe and effective dosing strategies using physiologically based pharmacokinetic (PBPK) modeling. Methods: Predictive PBPK models for escitalopram were developed in nonpregnant women, pregnant women, and the fetoplacental unit using the Simcyp(®) simulator. Additional models incorporating CYP2C19 phenotypes were constructed. Model performance was evaluated using visual predictive checks and by comparing predicted-to-observed ratios for the maximum plasma concentration (C(max)) and the area under the curve (AUC), within an acceptance criterion of 0.7-1.3. Results: Escitalopram concentrations at doses of 10-20 mg declined with advancing gestation. The cord-to-maternal concentration ratio was approximately 0.70 for both doses. Simulations of maternal and fetoplacental PBPK models across CYP2C19 phenotypes showed that most observed concentrations fell within the 95% confidence intervals of the predictions. Based on the therapeutic range attained and the maintenance of steady-state exposure, a once-daily 20 mg escitalopram dose was predicted to be appropriate during pregnancy. Conclusions: These findings suggest that a once-daily 20 mg dose appears optimal during pregnancy, highlighting the need to consider the gestational stage and CYP2C19 phenotype in dose optimization.

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