Predicting intracellular drug concentrations in the presence of transporters

描述（由申请人提供）：必须知道药物的游离细胞内浓度才能准确预测其对细胞内靶标的作用。 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赞赏。由于很难通过实验定量细胞内药物浓度，因此一种有吸引力且强大的替代方案是开发预测这些浓度的准确模型。 拟议工作的总体目标是开发模型，预测在存在外排和摄取转运蛋白的情况下未结合的细胞内药物浓度。 具体来说，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。 我们进一步建议根据我们的体外和体内研究开发数学模型，以表征和预测药物进出细胞的渗透性和转运。 为此，我们提出以下具体目标：1）表征 30 种不同药物的体外处置特性。将评估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、MRP2 和 OATP1B1 的底物。 2) 表征 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。 将根据目标 1 和 2 的结果对大鼠和人类进行 IVIVC。 3）扩展我们当前的药物渗透性和运输计算模型。将开发更多包含不同血浆和细胞内膜区室的生理模型。 这些模型将使用目标 1 和 2 的数据进行参数化和测试。这些模型有望预测转运蛋白存在时的细胞内药物浓度。 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-时间曲线相连接，作为输入函数来预测细胞内药物浓度曲线。这将改善对清除、分布和体内药物相互作用的预测。我们的模型将解决 通过提供新颖且有用的工具来大大改善对人类药物处置的预测，对具有成本效益的药物开发的迫切需求尚未得到满足。

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.