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 V(ss)) 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 ((111)In labeled Hsp70, Suc(20)-BSA and Suc(40)-BSA) administered in different doses to mice. The histograms of AUC, MRT, CL and V(ss) 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 (111)In-Hsp70 and Suc(20)-BSA was almost independent of dose, whereas that of (111)In-Suc(40)-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.