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• W2116522625 endingPage "146" @default.
• W2116522625 startingPage "133" @default.
• W2116522625 abstract "Maximum a posteriori Bayesian (MAPB) pharmacokinetic parameter estimation is an accurate and flexible method of estimating individual pharmacokinetic parameters using individual blood concentrations and prior information. In the past decade, many studies have developed optimal sampling strategies to estimate pharmacokinetic parameters as accurately as possible using either multiple regression analysis or MAPB estimation. This has been done for many drugs, especially immunosuppressants and anticancer agents. Methods of development for optimal sampling strategies (OSS) are diverse and heterogeneous. This review provides a comprehensive overview of OSS development methodology using MAPB pharmacokinetic parameter estimation, determines the transferability of published OSSs, and compares sampling strategies determined by MAPB estimation and multiple regression analysis. OSS development has the following components: 1) prior distributions; 2) reference value determination; 3) optimal sampling time identification; and 4) validation of the OSS. Published OSSs often lack all data necessary for the OSS to be clinically transferable. MAPB estimation is similar to multiple regression analysis in terms of predictive performance but superior in flexibility." @default.
• W2116522625 created "2016-06-24" @default.
• W2116522625 creator A5019637847 @default.
• W2116522625 creator A5020433879 @default.
• W2116522625 creator A5020833521 @default.
• W2116522625 creator A5040069163 @default.
• W2116522625 creator A5057349563 @default.
• W2116522625 date "2011-04-01" @default.
• W2116522625 modified "2023-10-07" @default.
• W2116522625 title "Optimal Sampling Strategy Development Methodology Using Maximum A Posteriori Bayesian Estimation" @default.
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