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Population pharmacokinetic model of valproate and prediction of valproate serum concentrations in children with epilepsy

查看全文 作　　者：De-chunJIANG [1]LiWANG 高影响力作者 机构地区：[1]DepartmentofPediatrics,PekingUniversityFirstHospital,TherapeuticDrugMonitoringandClinicalToxicology,CenterofPekingUniversity,Beijing100034,China高影响力机构 出　　处：《Acta Pharmacologica Sinica》索引2004年第25卷第12期,共8页高影响力期刊 基　　金：Project supported by the National Natural Science Foundation of China (No 30170994). 摘　　要：AIM: Using sparse data of valproate (VPA) serum concentrations to build a population pharmacokinetic (PPK) model of VPA in Chinese children with epilepsy and to predict serum concentrations for new patients using a Bayesian approach. METHODS: Two hundred epileptic children, whose VPA serum concentrations were collected, were divided randomly into two groups (A and B, n=100 each). The PPK parameter values of group A were calculated to establish a PPK Model by using the NPEM Program of USC*PACK software. Based on it, VPA serum concentrations of group B were predicted with the Bayesian Fitting Program of the USC*PACK software. To assess the accuracy and precision of prediction, a paired-comparisons t-test was run between predicted and ob- served concentrations, and then the mean prediction error (MPE), mean square prediction error (MSPE), root mean square prediction error (RMSPE), and coincidence rates for different percentages of prediction error were all calculated. RESULTS: Optimum PPK parameters were: Ka, 2.522±2.743 h-1; Vs, 0.329±0.496 L/kg; and Kel, 0.0438±0.0384 h-1. For group B, there was no significant difference between predicted and observed concentrations. MPE was -0.43 mg/L, MSPE was 115.40 (mg/L)2, and RMSPE was 5.47 mg/L. The coincidence rates for percent- ages of prediction error, which were less than 5 %, 10 %, 15 %, 20 %, 25 %, and 30 %, were 62 %, 74 %, 82 %, 85 %, 89 %, and 93 %, respectively. CONCLUSION: A PPK model of VPA in epileptic children was successfully established. Based on it, VPA serum concentrations can be predicted accurately with a Bayesian approach. 关 键 词：人体模型 药物动力学 2-丙基戊酸钠 免疫血清 癫痫 贝斯定理 USC*PACK软件 VPA
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