Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
2485130 | Journal of Pharmaceutical Sciences | 2010 | 9 Pages |
Abstract
Empirically, 3-6 samples at each sampling time point have been used for most preclinical oneâpoint sampling experiments without any theoretical justification. The purpose of the present study is to propose a practical approach to determine the minimum sample number (Nmin) based on Monte Carlo simulation and a bootstrap resampling. A computer program MOMENT(BS), in which a bootstrap resampling algorithm is used to estimate mean and standard deviations of pharmacokinetic parameters, such as area under the curve and mean residence time, was applied to estimate Nmin. A new simulation program, MONTE1, was developed to generate simulated data for bootstrap resampling using the model parameters including interâ and/or intraâindividual variations. Then, an index, S2CV calculated as the sum of the squared coefficient of variation is proposed to determine the Nmin. The proposed approach was applied to the actual data in preclinical experiments, and the usefulness of the approach was suggested. An issue that oneâpoint sampling data cannot separately assess interâ and intraâindividual variability is discussed. © 2009 WileyâLiss, Inc. and the American Pharmacists Association J Pharm Sci 99: 2176-2184, 2010
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Authors
Seiji Takemoto, Kiyoshi Yamaoka, Makiya Nishikawa, Yoshitaka Yano, Yoshinobu Takakura,