van Hoogdalem Matthijs W, Wexelblatt Scott L, Akinbi Henry T, Vinks Alexander A, Mizuno Tomoyuki
Division of Clinical Pharmacology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; James L. Winkle College of Pharmacy, University of Cincinnati, Cincinnati, OH, USA.
Perinatal Institute, Division of Neonatology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA; Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, OH, USA; Center for Addiction Research, College of Medicine, University of Cincinnati, Cincinnati, OH, USA.
Pharmacol Ther. 2022 Jun;234:108045. doi: 10.1016/j.pharmthera.2021.108045. Epub 2021 Nov 20.
Physiologically-based pharmacokinetic (PBPK) modeling has emerged as a useful tool to study pharmacokinetics (PK) in special populations, such as pregnant women, fetuses, and newborns, where practical hurdles severely limit the study of drug behavior. PK in pregnant women is variable and everchanging, differing greatly from that in their nonpregnant female and male counterparts typically enrolled in clinical trials. PBPK models can accommodate pregnancy-induced physiological and metabolic changes, thereby providing mechanistic insights into maternal drug disposition and fetal exposure. Fueled by the soaring opioid epidemic in the United States, opioid use during pregnancy continues to rise, leading to an increased incidence of neonatal opioid withdrawal syndrome (NOWS). The severity of NOWS is influenced by a complex interplay of extrinsic and intrinsic factors, and varies substantially between newborns, but the extent of prenatal opioid exposure is likely the primary driver. Fetomaternal PBPK modeling is an attractive approach to predict in utero opioid exposure. To facilitate the development of fetomaternal PBPK models of opioids, this review provides a detailed overview of pregnancy-induced changes affecting the PK of commonly used opioids during gestation. Moreover, the placental transfer of these opioids is described, along with their disposition in the fetus. Lastly, the implementation of these factors into PBPK models is discussed. Fetomaternal PBPK modeling of opioids is expected to provide improved insights in fetal opioid exposure, which allows for prediction of postnatal NOWS severity, thereby opening the way for precision postnatal treatment of these vulnerable infants.
基于生理的药代动力学（PBPK）模型已成为研究特殊人群（如孕妇、胎儿和新生儿）药代动力学（PK）的有用工具，在这些人群中，实际障碍严重限制了药物行为的研究。孕妇的PK具有变异性且不断变化，与通常参与临床试验的非孕妇女性和男性有很大不同。PBPK模型可以适应妊娠引起的生理和代谢变化，从而为母体药物处置和胎儿暴露提供机制性见解。在美国阿片类药物流行率飙升的推动下，孕期阿片类药物的使用持续增加，导致新生儿阿片类药物戒断综合征（NOWS）的发病率上升。NOWS的严重程度受外在和内在因素复杂相互作用的影响，在新生儿之间差异很大，但产前阿片类药物暴露程度可能是主要驱动因素。胎儿-母体PBPK建模是预测子宫内阿片类药物暴露的一种有吸引力的方法。为促进阿片类药物胎儿-母体PBPK模型的开发，本综述详细概述了妊娠期间影响常用阿片类药物PK的妊娠引起的变化。此外，还描述了这些阿片类药物的胎盘转运及其在胎儿体内的处置情况。最后，讨论了将这些因素纳入PBPK模型的方法。阿片类药物的胎儿-母体PBPK建模有望为胎儿阿片类药物暴露提供更好的见解，从而能够预测产后NOWS的严重程度，从而为这些脆弱婴儿的精准产后治疗开辟道路。
