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

PBPK 建模

• 批准号: 10706040
• 负责人: MARY F HEBERT
• 金额: $ 65.73万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10706040
• 关键词: ABCG2 gene; Address; Breast Epithelial Cells; Breast Feeding; Breastfed infant; CYP3A4 gene; Cell Separation; Cell membrane; Characteristics; Cimetidine; Clinical; Clinical Research; Confidence Intervals; Consumption; Data; Diffusion; Dose; Drug Exposure; Drug Kinetics; Drug toxicity; Drug usage; Enzymes; Excretory function; Exposure to; Goals; Health; Human; Human Milk; In Vitro; Individual; Infant; Knowledge; Lactation; Mammary gland; Maternal Health; Mediating; Methods; Midazolam; Milk; Modeling; Mus; Oral; Pharmaceutical Preparations; Pharmacology; Physiological; Plasma; Play; Population; Postpartum Period; Pregnancy; Property; Proteins; Proteomics; Regimen; Riboflavin; Risk; Risk Assessment; Role; System; Topotecan; Toxic effect; Transfection; Translating; Vesicle; Wild Type Mouse; Woman; Xenobiotics; absorption; design; enzyme activity; falls; in silico; in vivo; infant outcome; innovation; interest; mammary; milk secretion; models and simulation; neonatal health; pharmacokinetic model; physiologically based pharmacokinetics; predictive modeling; rosuvastatin; statistics

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.

总结 母乳喂养对孕产妇和新生儿健康有多种有益影响;然而，统计数据表明 在美国，高达96%的哺乳期妇女在母乳喂养时服用一种或多种药物。药物 哺乳期妇女食用的维生素E可能在很大程度上转移到母乳中， 婴儿意外接触药物，在某些情况下对婴儿造成不良健康后果。 定量药物转移到人类母乳中对于合理的风险评估平衡毒性是重要的 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 在哺乳期妇女人群中， 哺乳期妇女，有必要使用预测方法来解决这个问题。一种历史方法是 根据母体血浆浓度预测母乳中的药物浓度（或药物AUC）（或 AUC）和乳汁与血浆（M/P）浓度或AUC比。M/P比率本身可以用两种方法来预测。 药物的理化特性和母乳的生理参数。虽然这种方法可能 预测主要通过被动扩散进入乳汁的药物的M/P比，目前没有方法 可用于准确预测药物通过转运机制分泌乳汁。尽管如此， 已知许多药物、外源性物质和内源性物质是由表达于细胞内的转运蛋白介导的。 乳腺上皮细胞（MEC）。在这个应用中，我们提出了一个系统药理学的方法来预测 转运蛋白介导的乳汁分泌药物。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基于生理学的方法来预测人类母乳 药代动力学（PBPK）建模和模拟（M&S）。具体来说，我们提出了一种创新的方法， 其利用人MEC和转运蛋白转染的细胞或质膜囊泡表达 感兴趣的单个转运蛋白（即OCT 1、BCRP）。使用定量靶向蛋白质组学， MEC将使我们能够确定这些转运蛋白在乳腺中的蛋白丰度。的 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在体外的内在 药物通过单一转运体的转运清除率。然后，体外内源性转运蛋白介导的清除率 对于PBPK M&S，将外推至体内乳腺中。将验证PBPK模型预测 使用从使用转运蛋白进行的临床研究中获得的人母乳中的药物PK数据 衬底结合起来，这些数据将使我们能够预测转运蛋白介导的药物PK在乳汁中的哺乳期 妇女这些研究将解决我们对人类母乳中药物PK理解的关键差距 在哺乳期。由于我们的方法可以应用于其他药物，这些药物是任何转运蛋白的底物， 有趣的是，它的意义远远超出了这里研究的药物和转运体。