Bayesian inference in pharmacokinetics/pharmacodynamics using regenerative methods

被引:0
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作者
Kang, Dongwoo [1 ]
D'argenio, David Z. [1 ]
机构
[1] Univ of Southern California, Los Angeles, United States
关键词
Algorithms - Computer simulation - Drug products - Markov processes - Mathematical models - Monte Carlo methods - Parameter estimation;
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摘要
To obtain independent and identically distributed subchains that allow application of regenerative simulation analysis method, a splitting technique was applied for Independence Metropolis-Hastings (IMH) chains and a hybrid sampler, Rejection Independence Metropolis-Hastings (RIMH) algorithm, in pharmacokinetic/pharmacodynamic parameter estimation. The confidence intervals associated with posterior quantities were evaluated using an extensive coverage study with a model for the anticancer drug Teniposide. For this example, both methods demonstrated coverage of 95% confidence intervals for posterior means and selected quantiles of model parameters and predicted drug concentrations close to their nominal values.
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