Simulations Plus, Inc., 42505 10th Street West, Lancaster, California, 93534, USA.
PhinC Development, 36 Rue Victor Basch, 91300, Massy, France.
AAPS J. 2021 Jun 24;23(4):89. doi: 10.1208/s12248-021-00603-y.
The purpose of this study was to develop a physiologically based pharmacokinetic (PBPK) model predicting the pharmacokinetics (PK) of different compounds in pregnant subjects. This model considers the differences in tissue sizes, blood flow rates, enzyme expression levels, glomerular filtration rates, plasma protein binding, and other factors affected during pregnancy in both the maternal and fetal models. The PBPKPlus™ module in GastroPlus was used to model the PK of cefuroxime and cefazolin. For both compounds, the model was first validated against PK data in healthy non-pregnant volunteers and then applied to predict pregnant groups PK. The model accurately described the PK in both non-pregnant and pregnant groups and explained well differences in the plasma concentration due to pregnancy. The fetal plasma and amniotic fluid concentrations were also predicted reasonably well at different stages of pregnancy. This work describes the use of a PBPK approach for drug development and demonstrates the ability to predict differences in PK in pregnant subjects and fetal exposure for compounds excreted renally. The prediction for pregnant groups is also improved when the model is calibrated with postpartum or non-pregnant female group if such data are available.
本研究旨在开发一种基于生理学的药代动力学(PBPK)模型,以预测不同化合物在孕妇体内的药代动力学(PK)。该模型考虑了母体和胎儿模型中在怀孕期间受影响的组织大小、血流速率、酶表达水平、肾小球滤过率、血浆蛋白结合等差异因素。使用 GastroPlus 中的 PBPKPlus™ 模块对头孢呋辛和头孢唑林的 PK 进行建模。对于这两种化合物,首先根据健康非孕妇志愿者的 PK 数据对模型进行验证,然后应用于预测孕妇群体 PK。该模型准确地描述了非妊娠和妊娠组的 PK,并很好地解释了由于妊娠导致的血浆浓度差异。在妊娠的不同阶段,胎儿血浆和羊水浓度也得到了合理的预测。这项工作描述了使用 PBPK 方法进行药物开发,并展示了预测在肾排泄的化合物中,妊娠受试者和胎儿暴露的 PK 差异的能力。如果有产后或非孕妇群体的数据,通过模型校准可以进一步改善对孕妇群体的预测。