To describe the distribution kinetics of ritonavir, single and multiple compartment models with linear and nonlinear elimination were investigated. Population pharmacokinetic parameters such as clearance, volume of distribution and absorption rate constant were estimated. combination with one-compartment disposition best described the pharmacokinetics of ritonavir. Clearance, volume of distribution and absorption MG149 rate constant were 10.5 l h?1 (95% prediction interval (95% PI) 9.38C11.7), 96.6 l (95% PI 67.2C121) and 0.871 h?1 (95% PI 0.429C1.47), respectively, with 38.3%, 80.0% and 169% interindividual variability, respectively. The interoccasion variability in the apparent bioavailability was 59.1%. The concomitant use of lopinavir resulted in a 2.7-fold increase in the clearance of ritonavir (value 0.001). No patients characteristics influenced the pharmacokinetics of ritonavir. Conclusions The pharmacokinetic parameters of ritonavir were adequately described by our population pharmacokinetic model. Concomitant use of the protease inhibitor lopinavir strongly influenced the pharmacokinetics of ritonavir. The model has been validated and can be used for further investigation of the interaction between ritonavir MG149 and other protease inhibitors. value of 0.05, representing a decrease in OFV of 3.84 was considered statistically significant (chi-square distribution, degrees of freedom (d.f) = 1). Standard MG149 errors for all parameters were approximated using the COVARIANCE option of NONMEM. Individual Bayesian pharmacokinetic estimates of the pharmacokinetic parameters were obtained using the POSTHOC option . Basic pharmacokinetic model Zero-order and first-order absorption models with and without absorption lag-time were tested. To describe the distribution kinetics of ritonavir, single and multiple compartment models with linear and nonlinear elimination were investigated. Population pharmacokinetic parameters such as clearance, volume of distribution and absorption rate constant were estimated. Interindividual (IIV) and interoccasion variability (IOV) in the pharmacokinetic parameters and in the apparent bioavailability (value of 0.05 (log-likelihood ratio test). Clinical relevance was assumed when the typical value of the pharmacokinetic parameter of interest changed at least 10% in the range of the covariate observed in the population in order to prevent the detection of an irrelevant albeit significant relationship. All significant and relevant covariates were included in an intermediate model. Finally, a stepwise backward elimination procedure was carried out. A covariate was retained in the model when the influence of this parameter was statistically significant ( 0.05) and clinically relevant (10% change in pharmacokinetic parameter). Statistical refinement The validity of the interindividual and interoccasion variability model was assessed by evaluating correlations between individual random effects () and interoccasion random effects () for all of the pharmacokinetic parameters . When a substantial correlation was present, covariance between these parameters was included in the model. Model validation The bootstrap resampling technique was applied as an internal validation. Bootstrap replicates were generated by sampling randomly approximately 65% from the original data set with replacement . The final model was fitted to the replicate data sets using the bootstrap option in the software package Wings for NONMEM (by N. Holford, version 222, May 2001, Auckland, New Zealand) and parameter estimates for each of the replicate data sets were obtained. The precision of the model was evaluated by visual inspection of the distribution of the model parameters. Furthermore, the median parameter values and 95% prediction intervals of the bootstrap replicates were compared with the estimates of the original data set. Results From 186 outpatients, 55 full pharmacokinetic profiles and 505 plasma concentrations at a single time point were ActRIB available, resulting in a database of 1228 plasma ritonavir concentrations. A total of 115 patients received 100 mg ritonavir once a day or 100 mg, 133 mg or 200 mg ritonavir twice a day as a booster. A MG149 total of 71 patients received ritonavir as an antiviral drug in a dosage of MG149 300 mg, 400 mg, 500 mg,.