BACKGROUND AND OBJECTIVE: Daclatasvir is a potent, pangenotypic once-daily hepatitis C virus (HCV) NS5A inhibitor that is approved for the treatment of chronic HCV infection. The objective of this analysis was to characterize the pharmacokinetics of daclatasvir in subjects with chronic HCV infection. METHODS: A population pharmacokinetic (PPK) model was developed to evaluate effects of covariates on daclatasvir pharmacokinetics in subjects with chronic HCV infection (n = 2149 from 11 studies). All significant demographic, laboratory, prognostic and treatment covariates (p < 0.05) from univariate screening were included in the full model. The final model was reached by backward elimination (p < 0.001) and simulations were performed to further evaluate the effects of covariates on daclatasvir exposures. The plasma pharmacokinetics of daclatasvir was described by a two-compartment model with linear elimination. Absorption was modeled as a zero-order release followed by a first-order absorption into the central compartment. RESULTS: The typical value of apparent clearance (CL/F) was 5.7 L/h (1.58% relative standard error [RSE]) and of apparent volume of the central compartment (V c/F) was 58.6 L (2.00% RSE). Modest inter-individual variability was estimated for CL/F (35.1%) and V c/F (29.5%). Statistically significant covariates in the final model were sex, race, virus genotype, baseline creatinine clearance, and alanine aminotransferase (ALT) on CL/F and sex, race, and body weight on V c/F. Covariate effects demonstrated a 30% higher area under the plasma concentration-time curve at steady state (AUCss) in female subjects; effects of all other covariates were <16%. CONCLUSIONS: The model adequately described the daclatasvir pharmacokinetics and estimated relatively small covariate effects. Considering the exposure range for the therapeutic dose of daclatasvir 60 mg once daily and the favorable safety profile, the small difference in exposures due to these covariates is not considered clinically relevant.
BACKGROUND AND OBJECTIVE: Daclatasvir is a potent, pangenotypic once-daily hepatitis C virus (HCV) NS5A inhibitor that is approved for the treatment of chronic HCV infection. The objective of this analysis was to characterize the pharmacokinetics of daclatasvir in subjects with chronic HCV infection. METHODS: A population pharmacokinetic (PPK) model was developed to evaluate effects of covariates on daclatasvir pharmacokinetics in subjects with chronic HCV infection (n = 2149 from 11 studies). All significant demographic, laboratory, prognostic and treatment covariates (p < 0.05) from univariate screening were included in the full model. The final model was reached by backward elimination (p < 0.001) and simulations were performed to further evaluate the effects of covariates on daclatasvir exposures. The plasma pharmacokinetics of daclatasvir was described by a two-compartment model with linear elimination. Absorption was modeled as a zero-order release followed by a first-order absorption into the central compartment. RESULTS: The typical value of apparent clearance (CL/F) was 5.7 L/h (1.58% relative standard error [RSE]) and of apparent volume of the central compartment (V c/F) was 58.6 L (2.00% RSE). Modest inter-individual variability was estimated for CL/F (35.1%) and V c/F (29.5%). Statistically significant covariates in the final model were sex, race, virus genotype, baseline creatinine clearance, and alanine aminotransferase (ALT) on CL/F and sex, race, and body weight on V c/F. Covariate effects demonstrated a 30% higher area under the plasma concentration-time curve at steady state (AUCss) in female subjects; effects of all other covariates were <16%. CONCLUSIONS: The model adequately described the daclatasvir pharmacokinetics and estimated relatively small covariate effects. Considering the exposure range for the therapeutic dose of daclatasvir 60 mg once daily and the favorable safety profile, the small difference in exposures due to these covariates is not considered clinically relevant.
Authors: T Garimella; R Wang; W-L Luo; P Wastall; H Kandoussi; M DeMicco; R D Bruce; C Hwang; R Bertz; M Bifano Journal: Antimicrob Agents Chemother Date: 2015-06-29 Impact factor: 5.191
Authors: Richard E Nettles; Min Gao; Marc Bifano; Ellen Chung; Anna Persson; Thomas C Marbury; Ronald Goldwater; Michael P DeMicco; Maribel Rodriguez-Torres; Apinya Vutikullird; Ernesto Fuentes; Eric Lawitz; Juan Carlos Lopez-Talavera; Dennis M Grasela Journal: Hepatology Date: 2011-12 Impact factor: 17.425
Authors: Tushar Garimella; Reena Wang; Wen-Lin Luo; Carey Hwang; Diane Sherman; Hamza Kandoussi; Thomas C Marbury; Harry Alcorn; Richard Bertz; Marc Bifano Journal: Antivir Ther Date: 2015-02-05
Authors: Jane P Messina; Isla Humphreys; Abraham Flaxman; Anthony Brown; Graham S Cooke; Oliver G Pybus; Eleanor Barnes Journal: Hepatology Date: 2014-07-28 Impact factor: 17.425
Authors: Marc Bifano; Robert Adamczyk; Carey Hwang; Hamza Kandoussi; Alan Marion; Richard J Bertz Journal: Clin Drug Investig Date: 2015-05 Impact factor: 2.859
Authors: Frauke Assmus; Jean-Sélim Driouich; Rana Abdelnabi; Laura Vangeel; Franck Touret; Ayorinde Adehin; Palang Chotsiri; Maxime Cochin; Caroline S Foo; Dirk Jochmans; Seungtaek Kim; Léa Luciani; Grégory Moureau; Soonju Park; Paul-Rémi Pétit; David Shum; Thanaporn Wattanakul; Birgit Weynand; Laurent Fraisse; Jean-Robert Ioset; Charles E Mowbray; Andrew Owen; Richard M Hoglund; Joel Tarning; Xavier de Lamballerie; Antoine Nougairède; Johan Neyts; Peter Sjö; Fanny Escudié; Ivan Scandale; Eric Chatelain Journal: Microorganisms Date: 2022-08-12