PKPDAnalysen

PKPDAnalysen (pharmacokinetic/pharmacodynamic analyses) are quantitative methods used to describe and predict how a drug's exposure relates to its therapeutic and adverse effects over time. By combining pharmacokinetics (how the body processes a drug) with pharmacodynamics (the drug's biological effects), PKPDAnalysen support dose selection, regimen optimization, and risk assessment.

Data for PKPD analyses typically come from concentration-time profiles in biological samples and corresponding pharmacodynamic endpoints or biomarkers. Modeling approaches range from exploratory non-compartmental analysis to mechanistic compartmental models. PK describes absorption, distribution, metabolism, and excretion; PD describes drug-target interactions, often with Emax or sigmoid Emax dose–response relationships. Linking models connect exposure metrics (concentration, AUC) to effects.

Population PK/PD uses nonlinear mixed-effects modeling to quantify typical effects and variability across individuals and covariates (weight, age, organ function). Software tools include NONMEM, Monolix, Phoenix NLME, and R packages; Bayesian and frequentist methods are used, including MCMC and NLME. Validation uses diagnostic plots, visual predictive checks, bootstrap, and external data when available.

Applications include dose optimization in adults and special populations (pediatrics, renal/hepatic impairment), assessment of drug–drug interactions, therapeutic drug monitoring, and exposure–safety analyses (e.g., QT prolongation). In regulatory science, PKPD analyses are central to model-informed drug development and labeling decisions.

Limitations include model misspecification, identifiability issues, data quality, and the assumption that models generalize beyond studied populations.