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临床哺乳研究以及药代动力学建模和模拟在预测母乳喂养婴儿药物暴露中的作用。

Clinical lactation studies and the role of pharmacokinetic modeling and simulation in predicting drug exposures in breastfed infants.

机构信息

Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA.

出版信息

J Pharmacokinet Pharmacodyn. 2020 Aug;47(4):295-304. doi: 10.1007/s10928-020-09676-2. Epub 2020 Feb 7.

Abstract

The relative lack of information on medication use during breastfeeding is an ongoing problem for health professionals and mothers alike. Most nursing mothers are prescribed some form of medication, yet some mothers either discontinue breastfeeding or avoid medications entirely. Although regulatory authorities have proposed a framework for clinical lactation studies, data on drug passage into breastmilk are often lacking. Model-based approaches can potentially be used to estimate the passage of drugs into milk, predict exposures in breastfed infants, and identify drugs that need clinical lactation studies. When a human study is called for, measurement of the drug concentration in milk are often adequate to characterize safety. Data from these studies can be leveraged to further refine pharmacokinetic models with subsequent Monte Carlo simulations to estimate the spread of exposure values. Both clinical lactation studies and model-based approaches have some limitations and pitfalls which are discussed.

摘要

母乳喂养期间用药信息相对缺乏,这是卫生专业人员和母亲共同面临的一个问题。大多数哺乳期母亲都会被开某种形式的药物,但有些母亲要么停止母乳喂养,要么完全避免用药。尽管监管机构已经为临床哺乳期研究提出了一个框架,但药物进入母乳的数据往往缺乏。基于模型的方法可以用来估计药物进入乳汁的情况,预测母乳喂养婴儿的暴露情况,并确定需要进行临床哺乳期研究的药物。当需要进行人体研究时,测量乳汁中的药物浓度通常足以确定安全性。可以利用这些研究的数据进一步完善药代动力学模型,然后进行蒙特卡罗模拟,以估计暴露值的分布。临床哺乳期研究和基于模型的方法都有一些局限性和缺陷,对此进行了讨论。

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