PURPOSE: The purpose of this study were to evaluate the use of individual compartmental and population compartmental methods for bioequivalence determination, and to determine their utility as adjuncts to the current methods used for bioequivalence assessment. METHODS: Data from three bioequivalence studies of chlorthalidone were analyzed with PCNONLIN using individual compartmental modeling and NONMEM for population analyses. These results were compared with results obtained from the traditional noncompartmental or SHAM (slopes, heights, areas, and moments) approach for bioequivalence assessment and the 90% confidence interval procedure. RESULTS: Individual compartmental modeling and population compartmental modeling techniques performed well on this routine set of bioequivalence data which displayed simple pharmacokinetic properties. A direct assessment of the analysis methods was made by comparing the final estimates and 90% confidence intervals for the test to reference ratios (T/R) of AUC and CMAX. The final estimates and 90% confidence intervals for AUC T/R and CMAX T/R were similar and suggest consistency of results, independent of the method used. CONCLUSIONS: These results demonstrate the utility of modeling techniques as adjuncts to the traditional noncompartmental approach for bioequivalence determination.
PURPOSE: The purpose of this study were to evaluate the use of individual compartmental and population compartmental methods for bioequivalence determination, and to determine their utility as adjuncts to the current methods used for bioequivalence assessment. METHODS: Data from three bioequivalence studies of chlorthalidone were analyzed with PCNONLIN using individual compartmental modeling and NONMEM for population analyses. These results were compared with results obtained from the traditional noncompartmental or SHAM (slopes, heights, areas, and moments) approach for bioequivalence assessment and the 90% confidence interval procedure. RESULTS: Individual compartmental modeling and population compartmental modeling techniques performed well on this routine set of bioequivalence data which displayed simple pharmacokinetic properties. A direct assessment of the analysis methods was made by comparing the final estimates and 90% confidence intervals for the test to reference ratios (T/R) of AUC and CMAX. The final estimates and 90% confidence intervals for AUC T/R and CMAX T/R were similar and suggest consistency of results, independent of the method used. CONCLUSIONS: These results demonstrate the utility of modeling techniques as adjuncts to the traditional noncompartmental approach for bioequivalence determination.
Authors: G A Maier; G F Lockwood; J A Oppermann; G Wei; P Bauer; J Fedler-Kelly; T Grasela Journal: Eur J Drug Metab Pharmacokinet Date: 1999 Jul-Sep Impact factor: 2.441
Authors: A Dubois; S Gsteiger; S Balser; E Pigeolet; J L Steimer; G Pillai; F Mentré Journal: Clin Pharmacol Ther Date: 2011-12-28 Impact factor: 6.875
Authors: Alexander K Berg; Sumithra J Mandrekar; Katie L Allen Ziegler; Elsa C Carlson; Eva Szabo; Mathew M Ames; Daniel Boring; Paul J Limburg; Joel M Reid Journal: J Clin Pharmacol Date: 2013-02-22 Impact factor: 3.126