On the analysis of complex biological supply chains: From process systems engineering to quantitative systems pharmacology

被引：4

作者：

Rao, Rohit T. ^{[1
]}

Scherholz, Megerle L. ^{[1
]}

Hartmanshenn, Clara ^{[1
]}

Bae, Seul-A ^{[1
]}

Androulakis, Ioannis P. ^{[1
,2
]}

机构：

[1] Rutgers State Univ, Dept Chem & Biochem Engn, 98 Brett Rd, Piscataway, NJ 08854 USA

[2] Rutgers State Univ, Dept Biomed Engn, 599 Taylor Rd, Piscataway, NJ 08854 USA

来源：

COMPUTERS & CHEMICAL ENGINEERING | 2017年 / 107卷

基金：

美国国家科学基金会; 美国国家卫生研究院;

关键词：

Pharmacokinetics; Pharmacodynamics; Multi-scale systems biology; Quantitative systems pharmacology; CIRCADIAN-RHYTHMS; DRUG DISCOVERY; PHYSIOLOGICAL VARIABILITY; METABOLIC SYNDROME; CHRONIC DISEASE; INFLAMMATION; MODEL; SIMULATION; MECHANISM; CANCER;

D O I：

10.1016/j.compchemeng.2017.06.003

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The use of models in biology has become particularly relevant as it enables investigators to develop a mechanistic framework for understanding the operating principles of living systems as well as in quantitatively predicting their response to both pathological perturbations and pharmacological interventions. This application has resulted in a synergistic convergence of systems biology and pharmacokinetic-pharmacodynamic modeling techniques that has led to the emergence of quantitative systems pharmacology (QSP). In this review, we discuss how the foundational principles of chemical process systems engineering inform the progressive development of more physiologically-based systems biology models. (C) 2017 Elsevier Ltd. All rights reserved.

引用

页码：100 / 110

页数：11

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