A physiologically based toxicokinetic model of P-glycoprotein transporter-mediated placenta perfusion of dexamethasone in the pregnant rat

• Published in: Food and chemical toxicology 2024-01, Vol.183, p.114213-114213, Article 114213
• Main Authors: Du, Ruihu, Zhao, Xiaoqi, Song, Ling, Wang, Hui, Liu, Dongyang, Wang, Qi
• Format: Article
• Language: English
• Subjects: absorption; animal experimentation; brain; computer software; dexamethasone; lungs; P-glycoproteins; placenta; progeny; rats; risk; toxicity
• ISSN: 0278-6915; 1873-6351
• DOI: 10.1016/j.fct.2023.114213

The present dosage of Dexamethasone (DEX) administered to pregnant women may pose a risk of toxicity to their unborn offspring. We aimed to develop a maternal-fetal physiologically based toxicokinetic (PBTK) model for DEX in pregnant rats, with a specific focus on the role of the P-glycoprotein (P-gp) transporter in placenta perfusion, and finally facilitate the optimization of clinical DEX dosage. We conducted animal experiments to determine DEX concentrations in various rat tissues, and constructed the PBTK model using MATLAB software. Sensitivity analysis was performed to assess input parameters and the model stability, with fold error (FE) values serving as evaluation indices. Our results indicate the successful construction of the PBTK model, with the fitting key parameters such as the absorption rate constant (K ), intrinsic hepatic clearance (CL ) and intrinsic P-gp clearance (CL ). The median concentration of DEX in maternal plasma, fetal plasma, fetal lung, and fetal brain were determined, which allowed us to fit the tissue-to-plasma partition coefficients for the fetal lung (K ) and fetal brain (K ). After making adjustments, all calculated FE values were found to be less than 2, demonstrating the acceptability and accuracy of our model's predictions. Our model integrated external literature data and internal animal experimentation to comprehensively evaluate the maternal-fetal PK characteristics of DEX. These findings provide valuable support for the optimization of clinical DEX dosing.