pharmacometrics

Pharmacometrics is a discipline that uses mathematical and statistical approaches to characterize and predict the pharmacokinetics (how the body processes a drug) and pharmacodynamics (how a drug affects the body) of medicines. It integrates data from preclinical studies and clinical trials to quantify dose-exposure and exposure-response relationships, assess variability among individuals, and inform decision making in drug development and clinical practice. The field encompasses population PK/PD modeling, exposure-response analysis, and more mechanistic frameworks such as physiologically based pharmacokinetic modeling.

Key methods include nonlinear mixed-effects modeling for population-level inference, model development and validation, and model-informed drug development (MIDD). Modeling and simulation enable prediction of drug behavior under different dosing regimens, populations, and scenarios, including pediatrics, elderly, organ impairment, and drug interactions. PBPK models connect drug properties to physiology to extrapolate across species or to different life stages.

Applications span early discovery to regulatory submission: optimizing dose selection, supporting labeling decisions, translating findings across species and populations, and characterizing risks. Regulatory agencies increasingly accept pharmacometric analyses to support risk assessment and dose recommendations within submissions.

Common tools include NONMEM, Monolix, Phoenix NLME, and open-source platforms such as R-based packages; PBPK tools like Simcyp or PK-Sim. Validation relies on goodness-of-fit, visual predictive checks, external validation, and robust uncertainty assessment. Challenges include data quality, model identifiability, and ensuring reproducibility. The field is supported by professional societies and ongoing methodological research.