In Silico Biosciences, Berwyn, PA, USA.
J Pharmacokinet Pharmacodyn. 2013 Jun;40(3):257-65. doi: 10.1007/s10928-013-9297-1. Epub 2013 Jan 22.
Quantitative systems pharmacology (QSP) is a recent addition to the modeling and simulation toolbox for drug discovery and development and is based upon mathematical modeling of biophysical realistic biological processes in the disease area of interest. The combination of preclinical neurophysiology information with clinical data on pathology, imaging and clinical scales makes it a real translational tool. We will discuss the specific characteristics of QSP and where it differs from PK/PD modeling, such as the ability to provide support in target validation, clinical candidate selection and multi-target MedChem projects. In clinical development the approach can provide additional and unique evaluation of the effect of comedications, genotypes and disease states (patient populations) even before the initiation of actual trials. A powerful property is the ability to perform failure analysis. By giving examples from the CNS R&D field in schizophrenia and Alzheimer's disease, we will illustrate how this approach can make a difference for CNS R&D projects.
定量系统药理学（QSP）是药物发现和开发的建模和模拟工具包中的一个新成员，它基于对相关疾病领域中生物物理现实生物过程的数学建模。将临床前神经生理学信息与病理学、影像学和临床量表上的临床数据相结合，使其成为真正的转化工具。我们将讨论 QSP 的具体特征及其与 PK/PD 建模的区别，例如在目标验证、临床候选药物选择和多靶标 MedChem 项目中提供支持的能力。在临床开发中，该方法甚至在实际试验开始之前就可以提供对伴随药物、基因型和疾病状态（患者人群）的影响的额外和独特评估。一个强大的特性是进行故障分析的能力。通过从精神分裂症和阿尔茨海默病的中枢神经系统研发领域举例，我们将说明这种方法如何为中枢神经系统研发项目带来改变。
