MIDD

MIDD stands for Model-Informed Drug Development, an approach in pharmaceutical development that uses mathematical models and simulation to inform decisions across the drug lifecycle, from preclinical studies to post-approval labeling. The goal is to integrate diverse data streams to predict drug exposure, efficacy, and safety in different populations and to support dose selection, study design, and regulatory decisions.

Core components include pharmacokinetic/pharmacodynamic (PK/PD) modeling, population PK/PD analyses, exposure–response modeling, physiologically based pharmacokinetic (PBPK) modeling, and quantitative systems pharmacology (QSP). Analyses are conducted with tools such as nonlinear mixed-effects modeling (NONMEM), Monolix, Phoenix NLME, and Bayesian methods, often in conjunction with clinical trial simulations.

Applications include selecting initial and optimal doses, extrapolating data between populations (e.g., pediatric extrapolation), bridging sparse or early-phase data, dose-ranging decisions, and designing pivotal trials. MIDD also supports risk assessment and labeling decisions by characterizing dose–response, exposure margins, and simulation-based scenarios.

Regulatory context: regulatory agencies, including the FDA and EMA, have encouraged the use of model-informed approaches and have issued guidelines and regulatory frameworks that recognize MIDD as a valuable tool in decision making during development and review.

Challenges exist: robust models require high-quality data, careful specification of assumptions, validation, and clear communication of uncertainty. Successful MIDD depends on cross-disciplinary collaboration among clinicians, statisticians, pharmacologists, and regulatory scientists.

See also: pharmacometrics, PBPK, quantitative pharmacology.