Evaluation of bioequivalence of highly variable drugs using clinical trial simulations. II: Comparison of single and multiple-dose trials using AUC and Cmax.

PURPOSE: Evaluating of the effects of high intrasubject variability in clearance (CL) and volume of distribution (V), on 90% confidence intervals (CIs) for AUC (Area Under the concentration Curve) in single and multiple-dose bioequivalence studies. The main methodology was Monte Carlo simulation, and we also used deterministic simulation, and examination of clinical trials. The results are compared with those previously observed for Cmax (maximum concentration.) METHODS: The time course of drug concentration in plasma was simulated using a one-compartment model with log-normal statistical distributions of intersubject and intrasubject variabilities in the pharmacokinetic parameters. Both immediate-release and prolonged-release products were simulated using several levels of intrasubject variability in single-dose and multiple-dose studies. Simulations of 2000 clinical bioequivalence trials per condition (138 conditions) with 30 subjects in each crossover trial were carried out. Simulated data were compared with data from actual bioequivalence trials. RESULTS: The current simulations for AUC show similar probabilities of failure for single-dose and multiple-dose bioequivalence studies, even with differences in the rate of absorption or fraction absorbed. AUC values from prolonged-release scenario studies are more sensitive to changes in the first order absorption rate constant ka, and to variability in CL and V than AUC from studies of immediate-release studies. CONCLUSIONS: We showed that multiple-dose designs for highly variable drugs do not always reduce intrasubject variability in either AUC or Cmax, although the behavior of AUC differs from Cmax. Single dose AUC to the last quantifiable concentration was more reliable than either single dose AUC extrapolated to infinity, or multiple dose AUC during a steady-state interval. Multiple-dose designs may not be the best solution for assessing bioequivalence of highly variable drugs.

Evaluation of bioequivalence of highly variable drugs using Monte Carlo simulations. I. Estimation of rate of absorption for single and multiple dose trials using Cmax.

PURPOSE: A Monte Carlo simulation study was done to investigate the effects of high intrasubject variation in clearance (CL), and volume of distribution (V) on the calculation of the 90% confidence interval (CI) for Cmax for single dose and multiple dose studies. METHODS: Simulations were done for both immediate release and sustained release scenarios. The simulated data were compared with clinical data from bioequivalence studies performed on indomethacin and verapamil. RESULTS: Previous reviews and simulations have shown that the probability of failure for the Cmax for single dose studies was always greater than that for multiple dose studies. However, the results for the simulated scenarios currently investigated indicate that if intra-subject (period-to-period) variation in CL and V is high (% CV's above 25%, and 12%, respectively), multiple dose studies can exhibit a higher probability of failure for Cmax than do single dose studies. Furthermore, Cmax values from studies performed with a sustained release scenario are more sensitive to changes in Ka, CL, and V than are results of studies on immediate release products. As an example, the probability of failure for immediate release products in simulated single dose studies is about 11% and 21% when the mean difference in Ka is 10% and 20%, respectively; while, the probability of failure for multiple dose studies is about 36% regardless of the difference in Ka. The corresponding values for the probability of failure for sustained release products were 25%, 53% for single dose studies and 39% for multiple dose studies. The simulations also indicate that changes in the fraction absorbed have a greater effect on the estimation of Cmax in multiple dose regimens than in single dose studies. CONCLUSIONS: The results from these investigations indicate that multiple dose studies do not necessarily always reduce variability in Cmax.

Comparison of single and multiple dose pharmacokinetics using clinical bioequivalence data and Monte Carlo simulations.

The purpose of this study was to evaluate the relative performance and usefulness of single dose (SD) and multiple dose (MD) regimens for bioequivalence (BE) determination. Drugs such as indomethacin, procainamide, erythromycin, quinidine, nifedipine were tested for BE under SD and MD dose regimens. Drugs characterized by low accumulation indices (AI) showed virtually no change in the 90% confidence interval (CI) of AUC and CMAX upon multiple dosing. On the other hand, drugs with higher AI appeared to have smaller CI at steady-state. For example, the CI range of AUC and CMAX of quinidine (AI of 1.54) decreased from 26 to 12 and from 22 to 12, respectively, upon multiple dosing. A Monte Carlo simulation study of SD and MD bioequivalence trials was performed. The probability of failing the bioequivalence test was evaluated for several situations defined by different levels of variability and correlation in ka constants, presence or absence of inter- and/or intra-individual variability in clearance (CL) and volume of distribution (V), and different degrees of accumulation. All the possible combinations of these factors were tested with SD and MD study designs. All simulations used 1000 data sets with 30 subjects in each data set for a total of 144 unique designs (total of 144,000 simulations of bioequivalence trials). Upon multiple dosing, narrowing of CI ranges was observed for drugs simulated to have high AI high variability and a large difference in absorption constants (ka) between test and reference formulations.(ABSTRACT TRUNCATED AT 250 WORDS)