The unique challenges in pediatric drug development require efficient and innovative tools. Model‐informed drug development (MIDD) offers many powerful tools that have been frequently applied in pediatric drug development. MIDD refers to the application of quantitative models to integrate and leverage existing knowledge to bridge knowledge gaps and facilitate development and decision‐making processes. This article discusses the current practices and visions of applying MIDD in pediatric drug development, regulatory evaluation, and labeling, with detailed examples. The application of MIDD in pediatric drug development can be broadly classified into 3 categories: leveraging knowledge for bridging the gap, dose selection and optimization, and informing clinical trial design. In particular, MIDD can provide evidence for the assumption of exposure‐response similarity in bridging existing knowledge from reference to target population, support the dose selection and optimization based on the “exposure‐matching” principle in the pediatric population, and increase the efficiency and success rate of pediatric trials. In addition, the role of physiologically based pharmacokinetics in drug‐drug interaction in children and adolescents and in utilizing ontogeny data to predict pharmacokinetics in neonates and infants has also been illustrated. Moving forward, MIDD should be incorporated into all pediatric drug development programs at every stage to inform clinical trial design and dose selection, with both its strengths and limitations clearly laid out. The accumulated experience and knowledge of MIDD has and will continue to drive regulatory policy development and refinement, which will ultimately improve the consistency and efficiency of pediatric drug development.

Model‐informed drug development (MIDD) has been a powerful and efficient tool applied widely in pediatric drug development due to its ability to integrate and leverage existing knowledge from different sources to narrow knowledge gaps. The dose selection is the most common MIDD application in regulatory submission related to pediatric drug development. This article aims to give an overview of the 3 broad categories of use of MIDD in pediatric dose selection: leveraging from adults to pediatric patients, leveraging from animals to pediatric patients, and integrating mechanism in infants and neonates. Population pharmacokinetic analyses with allometric scaling can reasonably predict the clearance in pediatric patients aged >5 years. A mechanistic‐based approach, such as physiologically based pharmacokinetic accounting for ontogeny, or an allometric model with age‐dependent exponent, can be applied to select the dose in pediatric patients aged ≤2 years. The exposure‐response relationship from adults or from other drugs in the same class may be useful in aiding the pediatric dose selection and benefit‐risk assessment. Increasing application and understanding of use of MIDD have contributed greatly to several policy developments in the pediatric field. With the increasing efforts of MIDD under the Prescription Drug User Fee Act VI, bigger impacts of MIDD approaches in pediatric dose selection can be expected. Due to the complexity of model‐based analyses, early engagement between drug developers and regulatory agencies to discuss MIDD issues is highly encouraged, as it is expected to increase the efficiency and reduce the uncertainty.

Pharmacokinetics and pharmacodynamics can provide a useful modeling framework for predicting drug activity and can serve as a basis for dose optimization. Determining a suitable biomarker or surrogate measure of drug effect for pharmacodynamic models can be challenging. The electroencephalograph is a widely-available and non-invasive tool for recording brain-wave activity simultaneously from multiple brain regions. Certain drug classes (such as drugs that act on the central nervous system) also generate a reproducible electroencephalogram (EEG) effect. Characterization of such a drug-induced EEG effect can produce pharmacokinetic/pharmacodynamic models useful for titrating drug levels and expediting development of chemically-similar drug analogs. This paper reviews the relevant concepts involved in pharmacokinetic/pharmacodynamic modeling using EEG-based pharmacodynamic measures. In addition, examples of such models for various drugs are organized by drug activity as well as chemical structure and presented.

Study HighlightsWHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC? Based on nonclinical and clinical evidence, the pathophysiology of partial onset seizures (POS) is similar in pediatric patients ≥ 1 month of age and adults. WHAT QUESTION DID THIS STUDY ADDRESS?  This analysis addresses whether drugs indicated for the treatment of POS in adults and pediatric patients exhibit similar exposure-response relationships for efficacy. Such information can provide support for extrapolation of efficacy from adult to pediatric populations. WHAT DID THIS STUDY ADD TO OUR KNOWLEDGE? Data from eight drugs approved in adult and pediatric patients were used to demonstrate that the relationship between drug exposure and reduction in seizure frequency is similar in the two populations. HOW MIGHT THIS CHANGE CLINICAL PHARMA-COLOGY OR TRANSLATIONAL SCIENCE? As a result of this work, the US Food and Drug Administration (FDA) has concluded that the efficacy of drugs approved for the treatment of POS can be extrapolated from adults to pediatric patients 1 month of age and older, thus obviating the need for a controlled efficacy trial in the pediatric population.