Predicting intracellular drug concentrations in the presence of transporters

预测转运蛋白存在下的细胞内药物浓度

• 批准号: 8605201
• 负责人: Kenneth Ray Korzekwa
• 金额: $ 29.89万
• 依托单位: TEMPLE UNIV OF THE COMMONWEALTH
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-01-15 至 2016-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8605201
• 关键词: Address; Affect; Brain; Cell Membrane Permeability; Cell membrane; Cell model; Cells; Communities; Computer Simulation; Data; Data Set; Diffusion; Dose; Drug Interactions; Drug Kinetics; Drug Transport; Drug or chemical Tissue Distribution; Goals; Human; In Situ; In Vitro; Individual; Intracellular Membranes; Intravenous Bolus; Knock-out; Literature; Liver; Measurement; Measures; Membrane; Modeling; Organ; Perfusion; Permeability; Pharmaceutical Preparations; Physiological; Plasma; Plasma Proteins; Property; Protein Binding; Rattus; Role; Simulate; Testing; Time; Tissues; Toxic effect; Work; base; cost effective; drug development; drug distribution; drug metabolism; improved; in vivo; inhibitor/antagonist; mathematical model; monolayer; novel; public health relevance; research study; tool; uptake; user-friendly

DESCRIPTION (provided by applicant): A drug's free intracellular concentration must be known to accurately predict its effect on an intracellular target. Intracellular drug concentratios are affected by active efflux as well as uptake transporters. The role of these transporters in drug-drug interactions and drug disposition is greatly appreciated. Since it is difficult to experimentally quantitate intracellular drug concentrations, an attractive and powerful alternative is to develop accurate models that predict these concentrations. The overall goal of the proposed work is to develop models that predict unbound intracellular drug concentrations in the presence of efflux as well as uptake transporters. Specifically, we propose to conduct in vitro and in vivo studies to quantitate the effect of transporters on intracellular drug concentration. We further propose to develop mathematical models based on our in vitro and in vivo studies to characterize and predict permeability and transport of drugs in and out of cells. To this end, we propose the following specific aims: 1) Characterize the in vitro disposition properties of a diverse set of 30 drugs. The plasma protein binding, membrane partitioning, permeability, transport, and metabolism for these drugs will be evaluated. These drugs are substrates for P-gp, BCRP, MRP2, and OATP1B1. 2) Characterize the in situ and in vivo disposition properties of a diverse set of 30 drugs. Brain and liver partitioning will be measured by in situ perfusion. In vivo pharmacokinetics will be measured in the rat. Transporter knockout rats will be utilized for in vivo PK studies. IVIVCs will be performed with results from Aims 1 an 2 for both rat and human. 3) Expand our current computational models for drug permeability and transport. More physiological models that incorporate different plasma and intracellular membrane compartments will be developed. These models will be parameterized and tested with the data from Aims 1 and 2. These models are expected to predict the intracellular concentrations of drugs in the presence of transporters. Together, results from the proposed studies will provide, for the first time, integration of in vitro transporter data, in situ transprter-related disposition data, and in vivo PK to predict intracellular concentrations at the target sit. Additionally, models will be interfaced with systemic (plasma) drug concentration-time profiles as input functions to predict intracellular drug concentration profiles. This will result in improed prediction of clearance, distribution, and in vivo drug-drug interactions. Our models will address an unmet critical need for cost-effective drug development by providing novel and useful tools to vastly improve prediction of drug disposition in humans.

描述（由申请人提供）：必须知道药物的游离细胞内浓度，以准确预测其对细胞内靶点的作用。 细胞内药物浓度受主动外排和摄取转运蛋白的影响。 这些转运蛋白在药物相互作用和药物处置中的作用受到高度重视。由于很难通过实验定量细胞内药物浓度，一个有吸引力的和强大的替代方案是开发预测这些浓度的准确模型。 拟议的工作的总体目标是开发模型，预测未结合的细胞内药物浓度的存在下，外排以及摄取转运蛋白。 具体而言，我们建议进行体外和体内研究，以定量转运蛋白对细胞内药物浓度的影响。 我们进一步建议开发基于我们的体外和体内研究的数学模型，以表征和预测药物在细胞内外的渗透性和运输。 为此，我们提出了以下具体目标：1）表征一组不同的30种药物的体外处置特性。将评价这些药物的血浆蛋白结合、膜分配、渗透性、转运和代谢。这些药物是P-gp、BCRP、MRP 2和OATP 1B 1的底物。2)描述30种不同药物的原位和体内处置特性。将测量大脑和肝脏的分配 通过原位灌注。将在大鼠中测量体内药代动力学。转运蛋白敲除大鼠将用于体内PK研究。 将使用目的1和2的结果对大鼠和人进行IVIVIVC。 3)扩展我们目前的药物渗透性和运输的计算模型。更多的生理模型，包括不同的血浆和细胞内膜室将被开发。 这些模型将被参数化，并使用目标1和2的数据进行测试。这些模型预计将预测的转运蛋白的存在下，药物的细胞内浓度。 总之，拟议研究的结果将首次提供体外转运蛋白数据、原位转运蛋白相关处置数据和体内PK的整合，以预测靶位点的细胞内浓度。此外，模型将与全身（血浆）药物浓度-时间曲线连接，作为预测细胞内药物浓度曲线的输入函数。这将改善对清除率、分布和体内药物相互作用的预测。我们的模型将解决 通过提供新的和有用的工具来极大地改善药物在人体中的分布的预测，对具有成本效益的药物开发的未满足的关键需求。