title: Sequential population pharmacokinetic modeling of lopinavir and ritonavir in healthy volunteers and assessment of different dosing strategies.
abstract: Nonlinear mixed-effects modeling was applied to explore the relationship between lopinavir and ritonavir concentrations over 72 h following drug cessation and also to assess other lopinavir and ritonavir dosing strategies compared to the standard 400-mg-100-mg twice-daily dose. Data from 16 healthy volunteers were included. Possible covariates influencing lopinavir and ritonavir pharmacokinetics were also assessed. Data were modeled first separately and then together by using individually predicted ritonavir pharmacokinetic parameters in the final lopinavir model. The model was evaluated by means of a visual predictive check and external validation. A maximum-effect model in which ritonavir inhibited the elimination of lopinavir best described the relationship between ritonavir concentrations and lopinavir clearance (CL/F). A ritonavir concentration of 0.06 mg/liter was associated with a 50% maximum inhibition of the lopinavir CL/F. The population prediction of the lopinavir CL/F in the absence of ritonavir was 21.6 liters/h (relative standard error, 14.0%), and the apparent volume of distribution and absorption rate constant were 55.3 liters (relative standard error, 10.2%) and 0.57 h(-1) (relative standard error, 0.39%), respectively. Overall, 92% and 94% of the observed concentrations were encompassed by the 95% prediction intervals for lopinavir and ritonavir, respectively, which is indicative of an adequate model. Predictions of concentrations from an external data set (HIV infected) (n = 12) satisfied predictive performance criteria. Simulated lopinavir exposures at lopinavir-ritonavir doses of 200 mg-150 mg and 200 mg-50 mg twice daily were 38% and 65% lower, respectively, than that of the standard dose. The model allows a better understanding of the interaction between lopinavir and ritonavir and may allow a better prediction of lopinavir concentrations and assessments of different dosing strategies.
authors.affiliation: Department of Pharmacology, University of Liverpool, Pharmacology Research Laboratories, Block H, First Floor, 70 Pembroke Place, Liverpool L693GF, United Kingdom. laurad@liv.ac.uk
authors.forename: Laura
authors.initials: L
authors.lastname: Dickinson
authors.forename: Marta
authors.initials: M
authors.lastname: Boffito
authors.forename: David
authors.initials: D
authors.lastname: Back
authors.forename: Laura
authors.initials: L
authors.lastname: Else
authors.forename: Nils
authors.initials: N
authors.lastname: von Hentig
authors.forename: Geraint
authors.initials: G
authors.lastname: Davies
authors.forename: Saye
authors.initials: S
authors.lastname: Khoo
authors.forename: Anton
authors.initials: A
authors.lastname: Pozniak
authors.forename: Graeme
authors.initials: G
authors.lastname: Moyle
authors.forename: Leon
authors.initials: L
authors.lastname: Aarons
mesh_terms: D000328:Adult; D019380:Anti-HIV Agents / Q000493:pharmacokinetics*; D019540:Area Under Curve; D015992:Body Mass Index; D005260:Female; D006801:Humans; D061466:Lopinavir; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D011744:Pyrimidinones / Q000008:administration & dosage / Q000493:pharmacokinetics*; D019438:Ritonavir / Q000008:administration & dosage / Q000493:pharmacokinetics*
chemical_list: D019380:Anti-HIV Agents; D011744:Pyrimidinones; D061466:Lopinavir; D019438:Ritonavir