Physiologically based pharmacokinetic modeling (PBPK's) prediction potential in clinical pharmacology decision making during pregnancy.
Physiologically based pharmacokinetic modeling (PBPK's) prediction potential in clinical pharmacology decision making during pregnancy.
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DOI：
10.1002/ijgo.13150
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发表时间：
2020-09
期刊：
影响因子：
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通讯作者：
Gebreyohannes RD
中科院分区：
文献类型：
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作者：
Eke AC;Gebreyohannes RD
利用基于生理学的药代动力学（PBPK）建模技术已被证明在预测几种药物的药代动力学（PK）方面是非常宝贵的。在过去的十年中，PBPK模型作为预测妊娠期间药物处置的一种有前途的方法而受到关注。1 PBPK建模的优势在于结合生理和药物特异性参数来解决广泛的临床问题，例如探索药物-药物/食物-药物相互作用的影响，优化药物给药，为药物有效性提供支持性证据，为药物临床试验设计提供信息，并指导监管政策。2然而，妊娠期间PBPK模型的使用有限。例如，bictegravir（BIC）和doravidine（DOR）这两种新的艾滋病毒药物都在2018年被FDA批准用于非妊娠成人，但这些研究排除了孕妇。3，4将BIC和DOR的理化特性（表1）与其他体外、离体和体内数据整合，将允许开发PBPK模型，以预测健康孕妇和既存疾病孕妇中的母体和胎儿BIC和DOR PK。
Utilizing physiologically based pharmacokinetic (PBPK) modeling techniques has proven invaluable in predicting the pharmacokinetics (PK) of several medications. Over the past decade, PBPK modeling has gained attention as a promising approach to predict drug disposition during pregnancy. 1 PBPK modeling has the advantage of incorporating both physiologic and drug-specific parameters to address a wide range of clinical questions, such as exploring the effects of drug-drug/food-drug interactions, optimizing medication dosing, providing supportive evidence for drug effectiveness, informing drug clinical trial design, and guiding regulatory policy. 2 However, there is limited use of PBPK modeling during pregnancy. For example, bictegravir (BIC) and doravidine (DOR), two new HIV medications, were both FDA-approved for use in non-pregnant adults in 2018, but these studies excluded pregnant women. 3, 4 Integrating the physico-chemical characteristics of BIC and DOR (Table 1) with other in-vitro, ex-vivo, and in-vivo data would allow for the development of a PBPK model to predict maternal and fetal BIC and DOR PK in healthy pregnant women and those with pre-existing disease.