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摘要
The aim of this work is to reduce the cost of required sampling for the estimation of the area under the gliclazide plasma concentration versus time curve within 60 h (AUC(0-60t) ). The limited sampling strategy (LSS) models were established and validated by the multiple regression model within 4 or fewer gliclazide concentration values. Absolute prediction error (APE), root of mean square error (RMSE) and visual prediction check were used as criterion. The results of Jack-Knife validation showed that 10 (25.0 %) of the 40 LSS based on the regression analysis were not within an APE of 15 % using one concentration-time point. 90.2, 91.5 and 92.4 % of the 40 LSS models were capable of prediction using 2, 3 and 4 points, respectively. Limited sampling strategies were developed and validated for estimating AUC(0-60t) of gliclazide. This study indicates that the implementation of an 80 mg dosage regimen enabled accurate predictions of AUC(0-60t) by the LSS model. This study shows that 12, 6, 4, 2 h after administration are the key sampling times. The combination of (12, 2 h), (12, 8, 2 h) or (12, 8, 4, 2 h) can be chosen as sampling hours for predicting AUC(0-60t) in practical application according to requirement.
