PKPDmallinnus

PKPDmallinnus, short for pharmacokinetic-pharmacodynamic modeling, is a framework used to describe and predict how a drug’s concentration in the body relates to its therapeutic and adverse effects. The pharmacokinetic (PK) component describes how the body handles the drug—absorption, distribution, metabolism, and excretion—often through compartmental models that yield concentration-time profiles and parameters such as clearance and volume of distribution. The pharmacodynamic (PD) component describes the drug’s effect as a function of exposure, typically using models like linear, Emax, or sigmoidal Emax (Hill) with parameters such as EC50, Emax, and the Hill coefficient.

Linking PK and PD involves establishing an exposure–response relationship. Direct response models assume an immediate effect proportional to concentration, while indirect response or mechanistic models account for delays and the biology underlying the effect. Population PKPD extends these concepts to describe typical trajectories and between-subject variability, often incorporating covariates such as weight, age, renal or hepatic function to explain differences among individuals. Bayesian and nonlinear mixed-effects methods are commonly used for estimation.

Applications include dose regimen optimization, exposure–response simulations, and supporting dosing in special populations (pediatrics, organ impairment) or for bridging across populations. PKPD modeling informs regulatory submissions by providing mechanistic and quantitative justifications for dosing recommendations and labeling.

Model development relies on data that include concentration measurements and pharmacodynamic endpoints, analyzed with software such as NONMEM, Monolix, Stan, or R packages. Validation uses diagnostic plots, visual predictive checks, bootstrap, and external validation when possible. Limitations include potential model misspecification, identifiability challenges, sparse data, and the risks of extrapolating beyond observed conditions.