AI Article Synopsis

  • * Using multiple regression analysis, the study found that most LSS models (97.5% to 100%) could predict AUC(0-24 h) accurately within a 15% error margin when using 2 to 4 concentration-time points.
  • * Key time points for sampling after drug administration identified were 12, 4, 24, and 2 hours; combinations of these may be utilized for practical applications based on specific requirements for AUC estimation.

Article Abstract

This study aims to save cost of sampling for estimating the area under the amlodipine plasma concentration versus time curve in 24 hours (AUC(0-24 h)). Limited sampling strategy (LSS) models was developed and validated by mutiple regression model within 4 or fewer amlodipine concentration values. Absolute prediction error (APE), root of mean square error (RMSE) and visual predict check were used as criterion. The results of Jackknife validation showed that fifteen (9.4%) of the 160 LSS based on regression analysis were not within an APE of 15% by using one concentration-time point. 156 (97.5%), 159 (99.4%) and 160 (100%) of the 160 LSS model were capable of predicting within an APE 15% by using 2, 3, 4 points, separately. Limited sampling strategies have been developed and validated for estimating AUC(0-24 h) of amlodipine. The present study indicated that the implemention of both 5 mg and 10 mg dosage could enable accurate predictions of AUC(0-24 h) by the same LSS model. This study shows that 12, 4, 24, 2 h after administration are key sampling time points. The combination of (12, 4), (12, 4, 24) or (12, 4, 24, 2 h) might be chosen as sampling hours for predicting AUC(0-24 h) in practical application according to requirement.

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