Abbiati Roberto A, Wientjes M Guillaume, Au Jessie L-S
Institute of Quantitative Systems Pharmacology, Carlsbad, California, 92008, USA.
Department of Pharmaceutical Sciences, University of Oklahoma, Oklahoma City, Oklahoma, 73117, USA.
AAPS J. 2021 Aug 25;23(5):102. doi: 10.1208/s12248-021-00635-4.
Mathematical modeling has been an important tool in pharmaceutical research for 50 + years and there is increased emphasis over the last decade on using modeling to improve the efficiency and effectiveness of drug development. In an earlier commentary, we applied a multiscale model linking 6 scales (whole body, tumor, vasculature, cell, spatial location, time), together with literature data on nanoparticle and tumor properties, to demonstrate the effects of nanoparticle particles on systemic disposition. The current commentary used a 4-scale model (cell membrane, intracellular organelles, spatial location, time) together with literature data on the intracellular processing of membrane receptors and transporters to demonstrate disruption of transporter homeostasis can lead to drug-drug interaction (DDI) between victim drug (VD) and perpetrator drug (PD), including changes in the area-under-concentration-time-curve of VD in cells that are considered significant by the US Food and Drug Administration (FDA). The model comprised 3 computational components: (a) intracellular transporter homeostasis, (b) pharmacokinetics of extracellular and intracellular VD/PD concentrations, and (c) pharmacodynamics of PD-induced stimulation or inhibition of an intracellular kinetic process. Model-based simulations showed that (a) among the five major endocytic processes, perturbation of transporter internalization or recycling led to the highest incidence and most extensive DDI, with minor DDI for perturbing transporter synthesis and early-to-late endosome and no DDI for perturbing transporter degradation and (b) three experimental conditions (spatial transporter distribution in cells, VD/PD co-incubation time, extracellular PD concentrations) were determinants of DDI detection. We propose modeling is a useful tool for hypothesis generation and for designing experiments to identify potential DDI; its application further aligns with the model-informed drug development paradigm advocated by FDA.
五十多年来，数学建模一直是药物研究中的重要工具，并且在过去十年中，人们越来越强调利用建模来提高药物开发的效率和有效性。在早期的一篇评论中，我们应用了一个连接六个尺度（全身、肿瘤、脉管系统、细胞、空间位置、时间）的多尺度模型，结合有关纳米颗粒和肿瘤特性的文献数据，来证明纳米颗粒对全身处置的影响。当前的评论使用了一个四尺度模型（细胞膜、细胞内细胞器、空间位置、时间），并结合有关膜受体和转运蛋白细胞内加工的文献数据，来证明转运蛋白稳态的破坏会导致受害者药物（VD）和肇事者药物（PD）之间的药物相互作用（DDI），包括美国食品药品监督管理局（FDA）认为具有显著意义的细胞中VD浓度-时间曲线下面积的变化。该模型由三个计算组件组成：（a）细胞内转运蛋白稳态，（b）细胞外和细胞内VD/PD浓度的药代动力学，以及（c）PD诱导的细胞内动力学过程刺激或抑制的药效学。基于模型的模拟表明：（a）在五个主要的内吞过程中，转运蛋白内化或再循环的扰动导致最高的发生率和最广泛的DDI，而转运蛋白合成以及早期到晚期内体的扰动导致的DDI较小，转运蛋白降解的扰动则不会导致DDI；（b）三个实验条件（细胞内转运蛋白的空间分布、VD/PD共孵育时间、细胞外PD浓度）是DDI检测的决定因素。我们提出，建模是生成假设和设计实验以识别潜在DDI的有用工具；其应用进一步符合FDA倡导的模型指导药物开发范式。
