PBPK Modeling & Simulation to Predict Transporter-Mediated Drug Secretion into Human Breast Milk

摘要 母乳喂养对产妇和新生儿的健康有多方面的好处；然而，统计数据表明 在美国，高达96%的哺乳期妇女在哺乳期间服用一种或多种药物。用药 哺乳期妇女摄入的乳汁可能在很大程度上被转移到母乳中，导致 婴儿无意中接触药物，在某些情况下给婴儿带来不利的健康后果。 对进入母乳的药物转移进行量化对于合理评估风险、平衡毒性非常重要。 婴儿接触药物的风险和母乳喂养的好处。然而，临床药代动力学(PK)研究 在哺乳人群中，女性服用的每一种药物都是具有挑战性的，在后勤上也不可能 哺乳妇女，有必要使用预测方法来解决这一问题。一种历史上的方法是 根据母体血浆浓度预测母乳中药物浓度(或药物AUC) AUC)和乳浆浓度(M/P)或AUC比率。M/P比率本身可以使用这两种方法来预测 药物的理化特性和母乳的生理参数。虽然此方法可能 主要通过被动扩散来预测进入牛奶的药物的M/P比，目前还没有方法 可通过转运机制准确预测药物的乳汁分泌。尽管如此，乳汁分泌物 许多药物、外源物质和内源性物质都是由转运蛋白介导的 乳腺上皮细胞(MECs)。在这一应用中，我们提出了一种系统药理学方法来预测 转运蛋白介导的乳汁药物分泌。我们的假设是转运蛋白介导的药物PK在 可以使用体外实验数据结合生理学基础来预测母乳 药代动力学建模与仿真(M&S)。具体来说，我们提出了一种创新的方法 它利用人微血管内皮细胞和转运蛋白转染的细胞或质膜囊泡表达 感兴趣的单个转运体(即OCT1、BCRP)。利用定量靶向蛋白质组学，人类 MECS将使我们能够确定这些转运蛋白在乳腺中的蛋白丰度。这个 转运蛋白转染的细胞或质膜囊泡的研究将使我们能够确定体外固有的 由单一运输商对毒品的运输清关。然后，体外内源性转运体介导的清除 将外推到活体乳腺中的PBPK M&S。PBPK模型的预测将得到验证 使用从转运体进行的临床研究中获得的母乳中的药物PK数据 底物。综合起来，这些数据将使我们能够预测哺乳期牛奶中转运蛋白介导的药物PK 女人。这些研究将解决我们对母乳中药物PK的理解上的一个关键差距。 在哺乳期间。由于我们的方法可以应用于作为任何转运体底物的其他药物 它的意义远远超出了这里调查的毒品和运输商的范围。

SUMMARY Breastfeeding has multiple beneficial effects on maternal and neonatal health; however, the statistics indicate that up to 96% of lactating women in the US take one or more medications while breastfeeding. Medications consumed by lactating women may be transferred into breast milk to a significant extent, resulting in unintentional infant exposure of medications and in some cases adverse health outcomes for the infants. Quantifying drug transfer into human breast milk is important for rational risk assessment balancing the toxicity risk of drug exposure to infants and the benefits of breastfeeding. However, clinical pharmacokinetic (PK) studies in the population of lactating women are challenging and logistically not possible for every drug taken by lactating women, necessitating the use of prediction methods to address this issue. One historical approach is the prediction of drug concentrations (or drug AUC) in breast milk based on maternal plasma concentration (or AUC) and the milk-to-plasma (M/P) concentration or AUC ratio. The M/P ratio itself can be predicted using both physicochemical characteristics of drugs and physiological parameters of breast milk. While this approach may predict the M/P ratios of drugs that enter the milk predominantly by passive diffusion, no methods are currently available to accurately predict milk secretion of drugs via transport mechanisms. Nonetheless, milk secretions of many drugs, xenobiotics and endogenous substances are known to be mediated by transporters expressed in mammary epithelial cells (MECs). In this application, we propose a systems pharmacology approach to predict transporter-mediated milk secretion of drugs. Our hypothesis is that the transporter-mediated drug PK in human breast milk can be predicted using in vitro experimental data combined with Physiologically Based Pharmacokinetic (PBPK) modeling and simulation (M&S). Specifically, we propose an innovative approach which utilizes human MECs and transporter-transfected cells or plasma membrane vesicles expressing individual transporters of interest (i.e. OCT1, BCRP). Using quantitative targeted proteomics, the human MECs will allow us to determine the protein abundance of these transporters in the mammary gland. The transporter-transfected cell or plasma membrane vesicle studies will allow us to determine the in vitro intrinsic transport clearance of a drug by a single transporter. Then, the in vitro intrinsic transporter-mediated clearances will be extrapolated to in vivo in the mammary gland for PBPK M&S. PBPK model predictions will be verified using the drug PK data in human breast milk obtained from a clinical study conducted with a transporter substrate. Combined, these data will allow us to predict transporter-mediated drug PK in the milk of lactating women. These studies will address a critical gap in our understanding of drug PK in human breast milk during lactation. Since our approach can be applied to other drugs that are substrates of any transporters of interest, its significance goes well beyond the drug and transporters investigated here.