Random sparse sampling strategy using stochastic simulation and estimation for a population pharmacokinetic study

• DOI: 10.1016/j.jsps.2013.01.010
• Publication Date: 2013-02-10T04:02:45Z
• Authors: Xiao-hui Huang; Kun Wang; Ji-han Huang; Ling Xu; Lu-jin Li; Yu-cheng Sheng; Qing-shan Zheng
• Keywords: Stochastic simulation; Stochastic modelling

The purpose of this study was to use the stochastic simulation and estimation method evaluate effects sample size number samples per individual on model development evaluation. pharmacokinetic parameters inter- intra-individual variation were obtained from a population clinical trials amlodipine. Stochastic performed efficiencies different sparse sampling scenarios estimate compartment model. Simulated data generated 1000 times three candidate models used fit sets. Fifty-five kinds investigated compared. results showed that, 60 with points 20 five are recommended, quantitative methodology is valuable for efficiently estimating can be other similar evaluation approaches.