2011 年 32 巻 Special_Issue_2 号 p. 179-193
In the recent business and regulatory climate in drug development, the principle of Model-Based Drug Development (MBDD) is growing in importance as a driving force in development. MBDD is a strategy which is able to produce the essential clue to quantitative decision-making and the design of clinical trials by Monte-Carlo simulation. Throughout the process of MBDD, a nonlinear mixed effect model plays a very important role to describe the pharmacokinetics/pharmacodynamics (PK-PD) of an investigational drug and the disease progression. In order to be familiar with he technical aspect of MBDD, it is quite important to understand some real examples of models, which are already reported. In this article, four examples are introduced; 1) Apokyne PK-PD model, which impacted the decision of labeling in FDA’s review process, 2) HAE-1 PK-PD model, developed according to formerly developed drug and used for the design of Phase 2 study, 3) Rivoglitazone model integrating PK, PD and AE, and 4) QT-drug concentration model. Since the models in MBDD are complicated, pharmacometricians have to then conduct MBDD in close collaboration with pharmacometricians and other clinical development staff, especially with biostatisticians who also are experts in the quantitative data analysis.