Physiologically Based Pharmacokinetic Modeling of Drug Penetration into the Human Brain and Brain Tumors

基于生理学的药物渗透到人脑和脑肿瘤的药代动力学模型

• 批准号: 10674753
• 负责人: Jing Li
• 金额: $ 36.94万
• 依托单位: WAYNE STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10674753
• 关键词: Active Biological Transport; Affect; Animal Model; Antineoplastic Agents; Area; Biochemical; Biological Models; Blood - brain barrier anatomy; Brain; Brain Neoplasms; Cardiovascular system; Carrier Proteins; Central Nervous System; Cerebral cortex; Characteristics; Clinical; Clinical Pharmacology; Clinical Trials; Collaborations; Computer Models; Data; Data Set; Decision Making; Development; Diffusion; Dose; Drug Delivery Systems; Drug Kinetics; Drug Modelings; Enzymes; Formulation; Glioblastoma; Goals; Health Personnel; Heterogeneity; Human; In Vitro; Individual; Infiltration; Kinetics; Knowledge; Malignant neoplasm of brain; Mediating; Metabolism; Methods; Modeling; Necrosis; Oncology; Outcome; Patients; Penetration; Permeability; Pharmaceutical Preparations; Pharmacology; Pharmacology Study; Pharmacotherapy; Physiological; Plasma; Predictive Factor; Process; Property; Proteins; Proteomics; Regimen; SDZ RAD; Specimen; Structure; System; Translational Research; Validation; biological systems; blood perfusion; blood-brain barrier disruption; blood-brain barrier function; blood-brain barrier permeabilization; blood-brain tumor barrier; brain parenchyma; clinical development; comparative; contrast enhanced; design; drug development; effective therapy; improved; in vitro Assay; in vitro Model; in vivo; innovation; inter-individual variation; inter-institutional; model development; neurosurgery; novel; novel therapeutics; pharmacokinetic model; physiologically based pharmacokinetics; pre-clinical; predictive modeling; programs; restraint; small molecule; tool; translational research program; tumor; uptake

ABSTRACT Drug delivery to the brain is restrained by the blood-brain barrier (BBB), a physical and biochemical barrier separating the brain from the circulatory system. Small molecule drugs move across the BBB mainly via transcellular passive diffusion and transporter-mediated active transport. The BBB in brain tumors is disrupted to varying extent, leading to large intra- and inter-individual variability in drug tumor exposure. Mechanistic understanding and prediction of heterogeneous drug penetration across the intact BBB and disrupted blood- brain tumor barrier (BBTB) is of paramount importance to rational drug development and treatment for brain cancer. Given the fact that the rate and extent of drug penetration across the BBB is determined by both biological system characteristics and drug properties, prediction of human BBB/BBTB permeability from preclinical in vitro or animal models is complicated by biological system differences. Hence, the development of innovative approaches is imperative. The in vitro-in vivo extrapolation-physiologically based pharmacokinetic (IVIVE-PBPK) model offers a unique platform that allows simultaneous incorporation of drug- and system- specific parameters into a PK model and enables a priori prediction of individual in vivo kinetic processes based on mechanistic scaling of in vitro data (e.g., in vitro enzyme and transporter kinetics). The overall goal of this project is to develop a mechanism-based PBPK model platform for predicting heterogeneous drug penetration into the human brain and brain tumors. We will employ an integrated translational research approach to achieve this goal, which leverages in vitro pharmacology studies, PK modeling, and clinical trials. Three drugs (AZD1775, ceritinib, and ribociclib) will be used for initial model development and verification, and additional 3 drugs (everolimus, abemaciclib, and LY3214996) will be used for further model validation. These drugs have been or is being evaluated in glioblastoma patients in our clinical trial program. Observed clinical plasma and brain tumor PK data are available for model development and validation. As the first step towards resolving the gap of our knowledge on BBB transporter abundances, which is essential to establishing IVIVE scaling factors for predicting transporter-mediated active clearance at the human BBB and BBTB, Aim 1 is to determine transporter protein abundances in isolated microvessels of non-cancerous cortex as well as contrast-enhancing and non-enhancing glioblastoma specimens. Aim 2 is to determine drug-specific parameters for metabolism, passive transcellular permeability, and interaction with efflux and uptake drug transporters. Aim 3 is to develop and validate a novel 7-compartment permeability-limited brain (7Brain) PBPK model, which accounts for brain and tumor regional physiological differences in blood perfusion, pH, BBB/BBTB integrity, and transporter expression. The 7Brain PBPK model is the first-of-its kind, mechanism-based model platform for the prediction of heterogeneous drug penetration across the human BBB and BBTB. It promises to be a valuable tool to assist the development and design of improved drugs and dosing regimens for more effective treatment of brain cancer.

摘要 血脑屏障（BBB）是一种物理和生物化学屏障，它限制药物向脑内的转运 将大脑与循环系统分离。小分子药物主要通过 跨细胞被动扩散和转运蛋白介导的主动转运。脑肿瘤中的血脑屏障被破坏 在不同程度上，导致药物肿瘤暴露的个体内和个体间差异很大。机械论 理解和预测异质药物穿透完整的血脑屏障和破裂的血液- 脑肿瘤屏障（BBTB）对于合理开发脑肿瘤药物和治疗脑肿瘤至关重要 癌考虑到药物穿透BBB的速率和程度由两个因素决定， 生物系统特征和药物性质，预测人BBB/BBTB渗透性， 临床前体外或动物模型由于生物系统差异而变得复杂。因此， 必须采取创新办法。体外-体内外推-生理药代动力学 （IVIVE-PBPK）模型提供了一个独特的平台，允许同时掺入药物和系统， 将特定参数输入PK模型，并能够基于个体体内动力学过程进行先验预测 关于体外数据的机械缩放（例如，体外酶和转运蛋白动力学）。总的目标是 本项目旨在开发一个基于机制的PBPK模型平台，用于预测异质性药物渗透 注入人脑和脑瘤我们将采用综合转化研究方法， 这一目标利用了体外药理学研究、PK建模和临床试验。三种药物（AZD 1775， ceritinib和ribociclib）将用于初始模型开发和验证，另外3种药物 （依维莫司、abemaciclib和LY 3214996）将用于进一步的模型验证。这些药物已经或 正在我们的临床试验项目中对胶质母细胞瘤患者进行评估。观察临床血浆和脑肿瘤 PK数据可用于模型开发和验证。作为解决我们之间差距的第一步， 关于BBB转运蛋白丰度的知识，这对于建立IVIVE比例因子以预测 在人血脑屏障和血脑屏障的转运蛋白介导的主动清除，目的1是确定转运蛋白 非癌皮质的孤立微血管中的丰度以及对比度增强和非增强 胶质母细胞瘤标本目的2是确定药物代谢、被动跨细胞转运 渗透性以及与外排和摄取药物转运蛋白的相互作用。目的3是开发和验证一种新的 7-隔室渗透性限制的脑（7 Brain）PBPK模型，其考虑脑和肿瘤区域 血液灌注、pH、BBB/BBTB完整性和转运蛋白表达的生理差异。7Brain PBPK模型是第一个基于机制的模型平台，用于预测异质性药物 通过人BBB和BBTB的渗透。它有望成为一个有价值的工具，以协助发展和 设计改进的药物和给药方案，以更有效地治疗脑癌。