Mechanisms of Altered Hepatic Transport: Impact on Drug Therapy

肝胆转运蛋白在药物处置、安全性和有效性方面的重要性是很好的。 被认可了。确定参与这些过程的关键肝转运蛋白，并了解 影响它们的功能是成功的药物开发和最佳药物治疗的关键。总目标 这项研究计划的目的是解决肝胆药物转运方面的主要知识空白，并开发新的 评估和预测药物相互作用(DIS)、基因改变转运蛋白功能的影响的策略 变异和疾病。这些信息是精确医学科学的基础，并将有助于 预防DIS和药物引起的肝损伤(DILI)。我的实验室率先使用了三明治培养法 肝细胞，目前广泛用于研究肝胆药物转运和肝脏的强大体外工具 转运蛋白介导的分布。我们是第一个评估非酒精性脂肪性肝炎的功能影响的人- 与药物/代谢物处置相关的肝脏基侧外流转运体表达增加 并利用人类肝脏核素扫描数据来评估肝脏DI。我们的协作团队是 开发可在早期药物开发中先验用于识别化合物的计算工具 我们制定了一种策略，将生理参数和实验数据与 定量系统药理学(QSP)模型评价DILI机制。这些极具创新性的产品 方法可以改善对肝脏转运蛋白介导的DIS和DILI易感性的预测，从而导致更安全 药物。在目前的应用中，我们建议继续翻译基本的分子和细胞 通过解决以下关键问题对临床应用的机制：哪种肝基侧流出 转运蛋白对胆汁酸(BA)内环境平衡和阴离子药物处置至关重要？基底侧向的作用 BAS和阴离子药物/代谢物的肝脏和全身处置中的转运体(例如，Ostα/β)将 已澄清。这些信息将使我们能够更准确地预测BA介导的主要药物DILI 开发安全问题和批准的药物退出市场的原因。肝病怎么样？ 基底外侧BA和阴离子药物外流转运体受调控？关于英航之间的相互作用的信息很少 暴露、肝脏转运体动力学以及这些蛋白质在人类中的调节。我们将填补这些关键的 知识差距，目前危及对肝转运蛋白功能、DIS和BA的准确预测- 调解帝力。在体外、硅胶和活体中，什么工具可以帮助更有效和准确地预测 转运蛋白功能改变对BA和阴离子药物处置的临床影响？常规使用的体外试验 要预测转运蛋白介导的失代偿，无法确定复杂的相互作用机制。发展中的 新的体外工具、体内探针和硅胶模型将提供一种强有力的有效方法来识别 肝转运蛋白介导的DIS、BA介导的DILI易感因素，并提高预测准确性 优化药物治疗，避免不良反应。

The importance of hepatobiliary transport proteins in medication disposition, safety and efficacy is well recognized. Identifying key hepatic transporters involved in these processes and understanding the factors that impact their function is critical to successful drug development and optimal pharmacotherapy. The overall goal of this research program is to address major knowledge gaps in hepatobiliary drug transport and develop novel strategies to assess and predict the impact of transporter function altered by drug interactions (DIs), genetic variation, and disease. This information is fundamental to the science of precision medicine, and will aid in preventing DIs and drug-induced liver injury (DILI). My laboratory pioneered the use of sandwich-cultured hepatocytes, a powerful in vitro tool now widely used to study hepatobiliary drug transport and hepatic transporter-mediated DIs. We were the first to assess the functional impact of non-alcoholic steatohepatitis- associated increases in hepatic basolateral efflux transporter expression on drug/metabolite disposition in humans, and to utilize human liver scintigraphy data to evaluate a hepatic DI. Our collaborative team is developing computational tools that can be used a priori in early drug development to identify compounds with DILI liability, and we formulated a strategy integrating physiological parameters and experimental data with a quantitative systems pharmacology (QSP) model to evaluate DILI mechanisms. These highly innovative approaches can improve predictions of hepatic transporter-mediated DIs and DILI liability, leading to safer medications. In the current application, we propose to continue translating fundamental molecular and cellular mechanisms to clinical applications by addressing the following key questions: Which hepatic basolateral efflux transporters are critical to bile acid (BA) homeostasis and anionic drug disposition? The role of basolateral transporters (e.g., OSTα/β) in the hepatic and systemic disposition of BAs and anionic drugs/metabolites will be elucidated. This information will enable us to more accurately predict BA-mediated DILI, a major drug development safety issue and reason that approved drugs are withdrawn from the market. How are hepatic basolateral BA and anionic drug efflux transporters regulated? Information is scarce on the interplay of BA exposure, hepatic transporter dynamics, and the regulation of these proteins in humans. We will fill these critical knowledge gaps, which currently compromise accurate predictions of hepatic transporter function, DIs, and BA- mediated DILI. What in vitro, in silico, and in vivo tools could help predict, more efficiently and accurately, the clinical impact of altered transporter function on BA and anionic drug disposition? In vitro assays routinely used to predict transporter-mediated DIs are unable to identify complex interaction mechanisms. Development of novel in vitro tools, in vivo probes, and in silico models will provide a powerfully efficient approach to identify hepatic transporter-mediated DIs, BA-mediated DILI susceptibility factors, and improve prediction accuracy to optimize pharmacotherapy and avoid adverse effects.