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.

中文翻译：

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临床哺乳期研究以及药代动力学模型和模拟在预测母乳喂养婴儿药物暴露中的作用。

母乳喂养期间用药信息的相对缺乏是卫生专业人员和母亲都面临的一个持续问题。大多数哺乳期的母亲会被开出某种形式的药物，但有些母亲要么停止母乳喂养，要么完全避免用药。尽管监管机构提出了临床哺乳期研究的框架，但通常缺乏药物进入母乳的数据。基于模型的方法可用于估计药物进入乳汁的途径，预测母乳喂养婴儿的暴露量，并确定需要临床哺乳期研究的药物。当需要进行人体研究时，牛奶中药物浓度的测量通常足以表征安全性。可以利用这些研究的数据进一步完善药代动力学模型，随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陷阱，我们对此进行了讨论。