Evaluation framework for systems models

被引:15
作者
Braakman, Sietse [1 ,4 ]
Pathmanathan, Pras [2 ]
Moore, Helen [3 ]
机构
[1] Math Works Inc, Applicat Engn, Natick, MA USA
[2] US FDA, Off Sci & Engn Labs OSEL, Ctr Devices & Radiol Hlth CDRH, Silver Spring, MD USA
[3] Univ Florida, Dept Med, Div Pulm Crit Care & Sleep Med, Lab Syst Med, Gainesville, FL 32610 USA
[4] AbbVie Inc, Quantitat Translat Pharmacol, San Francisco, CA USA
来源
CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY | 2022年 / 11卷 / 03期
关键词
SENSITIVITY-ANALYSIS; IDENTIFIABILITY ANALYSIS; QSP MODELS; TOOL; UNCERTAINTY; INNOVATION; WORKFLOW; DESIGN;
D O I
10.1002/psp4.12755
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
As decisions in drug development increasingly rely on predictions from mechanistic systems models, assessing the predictive capability of such models is becoming more important. Several frameworks for the development of quantitative systems pharmacology (QSP) models have been proposed. In this paper, we add to this body of work with a framework that focuses on the appropriate use of qualitative and quantitative model evaluation methods. We provide details and references for those wishing to apply these methods, which include sensitivity and identifiability analyses, as well as concepts such as validation and uncertainty quantification. Many of these methods have been used successfully in other fields, but are not as common in QSP modeling. We illustrate how to apply these methods to evaluate QSP models, and propose methods to use in two case studies. We also share examples of misleading results when inappropriate analyses are used.
引用
收藏
页码:264 / 289
页数:26
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