Institute of Quantitative Systems Pharmacology, Carlsbad, California (J.L.-S.A., R.A.A., M.G.W., Z.L.); Department of Pharmaceutical Sciences, University of Oklahoma, Oklahoma City, Oklahoma (J.L.-S.A., R.A.A.); Optimum Therapeutics LLC, Carlsbad, California (J.L.-S.A., M.G.W., Z.L.); and College of Pharmacy, Taipei Medical University, Taipei, Taiwan, Republic of China (J.L.-S.A.)
Institute of Quantitative Systems Pharmacology, Carlsbad, California (J.L.-S.A., R.A.A., M.G.W., Z.L.); Department of Pharmaceutical Sciences, University of Oklahoma, Oklahoma City, Oklahoma (J.L.-S.A., R.A.A.); Optimum Therapeutics LLC, Carlsbad, California (J.L.-S.A., M.G.W., Z.L.); and College of Pharmacy, Taipei Medical University, Taipei, Taiwan, Republic of China (J.L.-S.A.).
Pharmacol Rev. 2019 Apr;71(2):157-169. doi: 10.1124/pr.118.016816.
Quantitative systems pharmacology (QSP), an emerging field that entails using modeling and computation to interpret, interrogate, and integrate drug effects spanning from the molecule to the whole organism to forecast treatment outcomes, is expected to enhance the efficiency of drug development. Since late 2017, the U.S. Food and Drug Administration has advocated the use of an analogous approach of model-informed drug development. This review focuses on issues pertaining to nanosized medicines (NP) and the potential utility of QSP to determine NP delivery and residence at extracellular or intracellular targets in vivo. The kinetic processes governing NP disposition and transport, interactions with biologic matrix components, binding and internalization in cells, and intracellular trafficking are determined, sometimes jointly, by NP properties (e.g., dimension, materials, surface charge and modifications, shape, and geometry) and target tissue properties (e.g., perfusion status, vessel pore size and wall thickness, vessel and cell density, composition of extracellular matrix, and void volume fraction). These various determinants, together with the heterogeneous tissue structures and microenvironment factors in solid tumors, lead to environment-, spatial-, and time-dependent changes in NP concentrations that are difficult to predict. Adding to the complexity is the recent discovery that NP surface-coating protein corona, whose composition depends on NP properties and which undergoes continuous evolution with time and local protein environments, is yet another unpredictable variable. Examples are provided to demonstrate the potential utility of QSP-based multiscale modeling to capture the physicochemical and biologic processes in equations to enable computational studies of the key kinetic processes in cancer treatments.
定量系统药理学（QSP）是一个新兴领域，它涉及使用建模和计算来解释、探究和整合药物效应，从分子到整个生物体，以预测治疗结果，有望提高药物开发的效率。自 2017 年末以来，美国食品和药物管理局一直倡导采用类似的模型指导药物开发方法。本综述重点关注纳米药物（NP）相关问题，以及定量系统药理学在确定 NP 体内递送至细胞外或细胞内靶点的传递和驻留方面的潜在应用。NP 处置和转运的动力学过程、与生物基质成分的相互作用、在细胞中的结合和内化以及细胞内转运，有时由 NP 特性（例如，尺寸、材料、表面电荷和修饰、形状和几何形状）和靶组织特性（例如，灌注状态、血管孔径和壁厚、血管和细胞密度、细胞外基质的组成和空隙体积分数）共同决定。这些各种决定因素，加上实体瘤中不均匀的组织结构和微环境因素，导致 NP 浓度的环境、空间和时间依赖性变化，难以预测。更为复杂的是，最近发现 NP 表面涂层蛋白冠，其组成取决于 NP 的特性，并且随着时间和局部蛋白质环境的不断演变，这是另一个不可预测的变量。提供了一些示例，以展示基于 QSP 的多尺度建模在捕获物理化学和生物学过程方面的潜在应用，以便能够对癌症治疗中的关键动力学过程进行计算研究。
