Role of modeling and simulation in pediatric investigation plans

Ethical and practical constraints encourage the optimal use of resources in pediatric drug development. Modeling and simulation has emerged as a promising methodology acknowledged by industry, academia, and regulators. We previously proposed a paradigm in pediatric drug development, whereby modeling and simulation is used as a decision tool, for study optimization and/or as a data analysis tool. Three and a half years since the Paediatric Regulation came into force in 2007, the European Medicines Agency has gained substantial experience in the use of modeling and simulation in pediatric drug development. In this review, we present examples on how the proposed paradigm applies in real case scenarios of planned pharmaceutical developments. We also report the results of a pediatric database search to further 'validate' the paradigm. There were 47 of 210 positive pediatric investigation plan (PIP) opinions that made reference to modeling and simulation (data included all positive opinions issued up to January 2010). This reflects a major shift in regulatory thinking. The ratio of PIPs with modeling and simulation rose to two in five based on the summary reports. Population pharmacokinetic (POP-PK) and pharmacodynamics (POP-PD) and physiologically based pharmacokinetic models are widely used by industry and endorsed or even imposed by regulators as a way to circumvent some difficulties in developing medicinal products in children. The knowledge of the effects of age and size on PK is improving, and models are widely employed to make optimal use of this knowledge but less is known about the effects of size and maturation on PD, disease progression, and safety. Extrapolation of efficacy from different age groups is often used in pediatric medicinal development as another means to alleviate the burden of clinical trials in children, and this can be aided by modeling and simulation to supplement clinical data. The regulatory assessment is finally judged on clinical grounds such as feasibility, ethical issues, prioritization of studies, and unmet medical need. The regulators are eager to expand the use of modeling and simulation to elucidate safety issues, to evaluate the effects of disease (e.g., renal or hepatic dysfunction), and to qualify mechanistic models that could help shift the current medicinal development paradigm.