Division of Biopharmaceutics and Pharmacokinetics, Xiangya School of Pharmaceutical Sciences, Central South University, Tongzipo Road 172, Changsha, 410013, China.
The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University, Changsha, China.
Pharm Res. 2024 May;41(5):899-910. doi: 10.1007/s11095-024-03705-2. Epub 2024 Apr 29.
Evaluating drug transplacental clearance is vital for forecasting fetal drug exposure. Ex vivo human placenta perfusion experiments are the most suitable approach for this assessment. Various in silico methods are also proposed. This study aims to compare these prediction methods for drug transplacental clearance, focusing on the large molecular weight drug vancomycin (1449.3 g/mol), using maternal-fetal physiologically based pharmacokinetic (m-f PBPK) modeling.
Ex vivo human placenta perfusion experiments, in silico approaches using intestinal permeability as a substitute (quantitative structure property relationship (QSPR) model and Caco-2 permeability in vitro-in vivo correlation model) and midazolam calibration model with Caco-2 scaling were assessed for determining the transplacental clearance (CL) of vancomycin. The m-f PBPK model was developed stepwise using Simcyp, incorporating the determined CL values as a crucial input parameter for transplacental kinetics.
The developed PBPK model of vancomycin for non-pregnant adults demonstrated excellent predictive performance. By incorporating the CL parameterization derived from ex vivo human placenta perfusion experiments, the extrapolated m-f PBPK model consistently predicted maternal and fetal concentrations of vancomycin across diverse doses and distinct gestational ages. However, when the CL parameter was derived from alternative prediction methods, none of the extrapolated maternal-fetal PBPK models produced fetal predictions in line with the observed data.
Our study showcased that combination of ex vivo human placenta perfusion experiments and m-f PBPK model has the capability to predict fetal exposure for the large molecular weight drug vancomycin, whereas other in silico approaches failed to achieve the same level of accuracy.
评估药物经胎盘清除率对于预测胎儿药物暴露至关重要。离体人胎盘灌注实验是评估药物经胎盘清除率最适宜的方法。同时,也提出了各种计算方法。本研究旨在通过母体-胎儿生理药代动力学(m-f PBPK)模型,比较这些预测药物经胎盘清除率的方法,重点关注大分子量药物万古霉素(1449.3 g/mol)。
采用离体人胎盘灌注实验、以肠通透性为替代指标的计算方法(定量构效关系(QSPR)模型和 Caco-2 体外-体内相关性模型)以及基于 Caco-2 比例的咪达唑仑校准模型来评估万古霉素的胎盘清除率(CL)。使用 Simcyp 逐步建立 m-f PBPK 模型,将确定的 CL 值作为胎盘动力学的关键输入参数。
建立的非妊娠成人万古霉素 PBPK 模型具有良好的预测性能。通过将源自离体人胎盘灌注实验的 CL 参数化纳入其中,外推的 m-f PBPK 模型能够一致地预测不同剂量和不同妊娠龄的母体和胎儿万古霉素浓度。然而,当 CL 参数源自其他预测方法时,没有一个外推的母胎 PBPK 模型能够产生与观察数据相符的胎儿预测值。
本研究表明,离体人胎盘灌注实验与 m-f PBPK 模型相结合能够预测大分子量药物万古霉素的胎儿暴露情况,而其他计算方法则无法达到相同的准确性。