Purpose of review: Studies from the anesthesiology literature published in the last 2 years were selected to illustrate the most important developments in the field of pharmacokinetic–pharmacodynamic modeling.
Recent findings: The pharmacokinetic models focused on incorporating covariate, especially age for pediatric–geriatric use, and altered physiological states. The pharmacodynamic models studied the effect of rate of anesthetic administration, age, experimental conditions, and delay within the monitor on estimation of drug concentration in the biophase. Models for the surrogate measure of the components of general anesthesia, hypnosis (bispectral index scale, entropy), immobility (limb tetanic stimulus-induced withdrawal reflex) and antinociception (surgical stress index, skin conductance algesimeter) were developed and validated. Response surface models were used to study drug interactions for important end-points during surgery and also to optimize dosing of anesthetic agents to maximize the desired/undesired effect ratio. The models for target-controlled infusions were improved by incorporating more covariates, and the closed-loop system was refined by using adaptive controllers that individualize the pharmacokinetic/pharmacodynamic parameters to the particular patient by using Bayesian, Kalman filters, fuzzy logic or neural networks.
Summary: Progress was made by improving population pharmacokinetic/pharmacodynamic models, developing new indexes to measure drug effect and using them in an adaptive delivery system to the individual patient.