Histogram Analysis of Pharmacokinetic Parameters by Bootstrap Resampling from One-point Sampling Data in Animal Experiments

A bootstrap method is proposed for assessing statistical histograms of pharmacokinetic parameters (AUC, MRT, CL and Vss) from one-point sampling data in animal experiments. A computer program, MOMENT(BS), written in Visual Basic on Microsoft Excel, was developed for the bootstrap calculation and the construction of histograms. MOMENT(BS) was applied to one-point sampling data of the blood concentration of three physiologically active proteins (111In labeled Hsp70, Suc20-BSA and Suc40-BSA) administered in different doses to mice. The histograms of AUC, MRT, CL and Vss were close to a normal (Gaussian) distribution with the bootstrap resampling number (200), or more, considering the skewness and kurtosis of the histograms. A good agreement of means and SD was obtained between the bootstrap and Bailer’s approaches. The hypothesis test based on the normal distribution clearly demonstrated that the disposition of 111In-Hsp70 and Suc20-BSA was almost independent of dose, whereas that of 111In-Suc40-BSA was definitely dose-dependent. In conclusion, the bootstrap method was found to be an efficient method for assessing the histogram of pharmacokinetic parameters of blood or tissue disposition data by one-point sampling.