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Truncated Area Under the Curve as a Measure of Relative Extent of Bioavailability: Evaluation Using Experimental Data and Monte Carlo Simulations

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Abstract

Purpose. The use of truncated areas under the curve (AUCs) could be a significant advantage for bioequivalence studies of drugs with long half-lives. The purpose of this study was to evaluate the performance of truncated AUCs as measures of relative extent of bioavailability using a large database of experimental data and Monte Carlo simulations.

Methods. The experimental data consisted of 123 single-dose, 2-treatment, crossover studies with at least 18 subjects/study. Monte Carlo techniques were also used to simulate studies that reflected a wide variety of experimental conditions. AUCs were calculated over different time intervals and the standard two one-sided t tests procedure was used to assess bioequivalence.

Results. The experimental data showed that conclusions concerning bioequivalence were identical between AUCs truncated at four times the time of peak concentration (Tmax) and AUCs extrapolated to infinity (AUCinf) in 120/123 or 97.6% of studies. There was little change in the intra-subject CVs for AUCs truncated at 3*Tmax or later. The results of Monte Carlo simulations were generally consistent with the experimental data and showed that AUCs truncated at 72 hours (AUC0−72) performed well compared to AUCinf as measures of bioequivalence for drugs with long half-lives.

Conclusions. Based on both the experimental and simulated data, AUCs truncated after the absorption phase perform well as measures of relative extent of bioavailability. Truncated AUCs offer a particular advantage for drugs with long half-lives and these results indicate that it would be reasonable to limit the sample collection period to 72 hours in bioequivalence studies of oral formulations.

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Correspondence to Richard L. Lalonde.

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Gaudreault, J., Potvin, D., Lavigne, J. et al. Truncated Area Under the Curve as a Measure of Relative Extent of Bioavailability: Evaluation Using Experimental Data and Monte Carlo Simulations. Pharm Res 15, 1621–1629 (1998). https://doi.org/10.1023/A:1011971620661

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  • DOI: https://doi.org/10.1023/A:1011971620661

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