J Kharidia1, A J Jackson, L A Ouderkirk. 1. Division of Bioequivalence, Office of Generic Drugs, Center for Drug Evaluation and Research, Food and Drug Administration, Rockville, Maryland 20857, USA.
Abstract
PURPOSE: To compare the applicability and accuracy of truncated area (AUCt; where t represents truncated time) versus area to the last quantifiable time point [AUC(O-T)] for assessing bioequivalence. Drugs with either very low or very high intra-subject variability in clearance (CL) were selected for study. Clearance variability was defined by the number of subjects with a quantifiable plasma value (Cp) at each collection time from 24 hrs to last collection time (T). METHODS: Data for amiodarone and danazol, drugs with different distributions of subject CL were examined. For amiodarone, the number of subject samples observed (test + reference) at the time of the last quantifiable concentrations was 60 at 240 hrs(T), 16 at 144 hrs and 4 at 96 hrs: while danazol had 4 at 96 hr(T), 3 at 72 hrs, 16 at 60 hrs, 7 at 48 hrs, 14 at 36 hrs, 11 at 24 hrs, 13 and 2 at 16 and 12 hrs, respectively. Simulations (Scenarios A and B) were performed to obtain populations (N = 24) with CL patterns similar to those of amiodarone and danazol. For scenario A (CL pattern similar to amiodarone), log-normally distributed CL values (28.8 L/HR) with intra-subject coefficient of variation (CV) of 25%, 40% and 60% gave the desired CL pattern. Scenario B (CL pattern similar to danazol) required that a subpopulation with an increase in CL of 40% from baseline (i.e., 40.32 L/HR) in 5%, 10% and 20% of the population represent the desired distribution. Power was evaluated by the percentage of times the simulated trials were declared bioequivalent (i.e., the number of times the test vs. reference 90% CI was within 80-125%), while accuracy was determined when the true difference in fraction absorbed (i.e., 1.25) was within the CI. Each simulation was repeated 300 times. RESULTS: The simulation results for Scenario A indicated that the statistical results using truncated area (AUCt) had power and accuracy equivalent to that obtained using the AUC(O-T) metric. However, results for Scenario B indicated that AUCt had less power and accuracy than that obtained using AUC(0-T). The confidence interval (CI) for amiodarone was the same whether AUC (0-T) or AUCt was used as the metric for extent, while for danazol, the AUC(0-T) and AUCt differed in the lower limit by 7%. CONCLUSIONS: The truncated area, AUCt, has the greatest power and accuracy when the population clearance is such that most subjects have measurable plasma concentrations at last collection time(T), resulting in a proportional loss of data from each subject.
RCT Entities:
PURPOSE: To compare the applicability and accuracy of truncated area (AUCt; where t represents truncated time) versus area to the last quantifiable time point [AUC(O-T)] for assessing bioequivalence. Drugs with either very low or very high intra-subject variability in clearance (CL) were selected for study. Clearance variability was defined by the number of subjects with a quantifiable plasma value (Cp) at each collection time from 24 hrs to last collection time (T). METHODS: Data for amiodarone and danazol, drugs with different distributions of subject CL were examined. For amiodarone, the number of subject samples observed (test + reference) at the time of the last quantifiable concentrations was 60 at 240 hrs(T), 16 at 144 hrs and 4 at 96 hrs: while danazol had 4 at 96 hr(T), 3 at 72 hrs, 16 at 60 hrs, 7 at 48 hrs, 14 at 36 hrs, 11 at 24 hrs, 13 and 2 at 16 and 12 hrs, respectively. Simulations (Scenarios A and B) were performed to obtain populations (N = 24) with CL patterns similar to those of amiodarone and danazol. For scenario A (CL pattern similar to amiodarone), log-normally distributed CL values (28.8 L/HR) with intra-subject coefficient of variation (CV) of 25%, 40% and 60% gave the desired CL pattern. Scenario B (CL pattern similar to danazol) required that a subpopulation with an increase in CL of 40% from baseline (i.e., 40.32 L/HR) in 5%, 10% and 20% of the population represent the desired distribution. Power was evaluated by the percentage of times the simulated trials were declared bioequivalent (i.e., the number of times the test vs. reference 90% CI was within 80-125%), while accuracy was determined when the true difference in fraction absorbed (i.e., 1.25) was within the CI. Each simulation was repeated 300 times. RESULTS: The simulation results for Scenario A indicated that the statistical results using truncated area (AUCt) had power and accuracy equivalent to that obtained using the AUC(O-T) metric. However, results for Scenario B indicated that AUCt had less power and accuracy than that obtained using AUC(0-T). The confidence interval (CI) for amiodarone was the same whether AUC (0-T) or AUCt was used as the metric for extent, while for danazol, the AUC(0-T) and AUCt differed in the lower limit by 7%. CONCLUSIONS: The truncated area, AUCt, has the greatest power and accuracy when the population clearance is such that most subjects have measurable plasma concentrations at last collection time(T), resulting in a proportional loss of data from each subject.