期刊
EUROPEAN JOURNAL OF PHARMACEUTICAL SCIENCES
卷 109, 期 -, 页码 S39-S46出版社
ELSEVIER
DOI: 10.1016/j.ejps.2017.05.028
关键词
Model-informed drug discovery and development; Quantitative systems pharmacology; Pharmacokinetics and pharmacodynamics; Pharmacometrics; Disease modeling
Modeling & simulation (M & S) methodologies are established quantitative tools, which have proven to be useful in supporting the research, development (R & D), regulatory approval, and marketing of novel therapeutics. Applications of M& S help design efficient studies and interpret their results in context of all available data and knowledge to enable effective decision-making during the R & D process. In this mini-review, we focus on two sets of modeling approaches: population-based models, which are well-established within the pharmaceutical industry today, and fall under the discipline of clinical pharmacometrics (PMX); and systems dynamics models, which encompass a range of models of (patho-) physiology amenable to pharmacological intervention, of signaling pathways in biology, and of substance distribution in the body (today known as physiologically-based pharmacokinetic models) - which today may be collectively referred to as quantitative systems pharmacology models (QSP). We next describe the convergence - or rather selected integration - of PMX and QSP approaches into 'middle-out' drug-disease models, which retain selected mechanistic aspects, while remaining parsimonious, fit-for-purpose, and able to address variability and the testing of covariates. We further propose development opportunities for drug-disease systems models, to increase their utility and applicability throughout the preclinical and clinical spectrum of pharmaceutical R & D.
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