Model-based drug development: The road to quantitative pharmacology

被引:79
作者
Zhang, Liping
Sinha, Vikram
Forgue, S. Thomas
Callies, Sophie
Ni, Lan
Peck, Richard
Allerheiligen, Sandra R. B. [1 ]
机构
[1] Eli Lilly & Co, Lilly Corp Ctr, Lilly Res Labs, Drug Disposit & Global PK PD, Indianapolis, IN 46285 USA
[2] Bristol Myers Squibb Co, Princeton, NJ USA
关键词
model-based drug development; quantitative pharmacology; disease model; drug exposure-response model; knowledge management; decision making; gemcitabine; raloxifene;
D O I
10.1007/s10928-006-9010-8
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
High development costs and low success rates in bringing new medicines to the market demand more efficient and effective approaches. Identified by the FDA as a valuable prognostic tool for fulfilling such a demand, model-based drug development is a mathematical and statistical approach that constructs, validates, and utilizes disease models, drug exposure-response models, and pharmacometric models to facilitate drug development. Quantitative pharmacology is a discipline that learns and confirms the key characteristics of new molecular entities in a quantitative manner, with goal of providing explicit, reproducible, and predictive evidence for optimizing drug development plans and enabling critical decision making. Model-based drug development serves as an integral part of quantitative pharmacology. This work reviews the general concept, basic elements, and evolving role of model-based drug development in quantitative pharmacology. Two case studies are presented to illustrate how the model-based drug development approach can facilitate knowledge management and decision making during drug development. The case studies also highlight the organizational learning that comes through implementation of quantitative pharmacology as a discipline. Finally, the prospects of quantitative pharmacology as an emerging discipline are discussed. Advances in this discipline will require continued collaboration between academia, industry and regulatory agencies.
引用
收藏
页码:369 / 393
页数:25
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