Karatza Eleni, Ganguly Samit, Hornik Chi D, Muller William J, Al-Uzri Amira, James Laura, Balevic Stephen J, Gonzalez Daniel
Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Regeneron Pharmaceuticals, Inc., Tarrytown, NY, United States.
Front Pharmacol. 2022 Mar 17;13:817276. doi: 10.3389/fphar.2022.817276. eCollection 2022.
Risperidone is approved to treat schizophrenia in adolescents and autistic disorder and bipolar mania in children and adolescents. It is also used off-label in younger children for various psychiatric disorders. Several population pharmacokinetic models of risperidone and 9-OH-risperidone have been published. The objectives of this study were to assess whether opportunistically collected pediatric data can be used to evaluate risperidone population pharmacokinetic models externally and to identify a robust model for precision dosing in children. A total of 103 concentrations of risperidone and 112 concentrations of 9-OH-risperidone, collected from 62 pediatric patients (0.16-16.8 years of age), were used in the present study. The predictive performance of five published population pharmacokinetic models (four joint parent-metabolite models and one parent only) was assessed for accuracy and precision of the predictions using statistical criteria, goodness of fit plots, prediction-corrected visual predictive checks (pcVPCs), and normalized prediction distribution errors (NPDEs). The tested models produced similarly precise predictions (Root Mean Square Error [RMSE]) ranging from 0.021 to 0.027 nmol/ml for risperidone and 0.053-0.065 nmol/ml for 9-OH-risperidone). However, one of the models (a one-compartment mixture model with clearance estimated for three subpopulations) developed with a rich dataset presented fewer biases (Mean Percent Error [MPE, %] of 1.0% . 101.4, 146.9, 260.4, and 292.4%) for risperidone. In contrast, a model developed with fewer data and a more similar population to the one used for the external evaluation presented fewer biases for 9-OH-risperidone (MPE: 17% . 69.9, 47.8, and 82.9%). None of the models evaluated seemed to be generalizable to the population used in this analysis. All the models had a modest predictive performance, potentially suggesting that sources of inter-individual variability were not entirely captured and that opportunistic data from a highly heterogeneous population are likely not the most appropriate data to evaluate risperidone models externally.
利培酮被批准用于治疗青少年精神分裂症、儿童和青少年的孤独症谱系障碍及双相躁狂。它也被用于年龄更小儿童的多种精神疾病的非适应证治疗。已有多个利培酮和9-羟基利培酮的群体药代动力学模型发表。本研究的目的是评估机会性收集的儿科数据能否用于外部评估利培酮群体药代动力学模型,并确定一个用于儿童精准给药的稳健模型。本研究使用了从62例儿科患者(0.16 - 16.8岁)收集的总共103个利培酮浓度和112个9-羟基利培酮浓度。使用统计标准、拟合优度图、预测校正视觉预测检查(pcVPC)和标准化预测分布误差(NPDE),评估了五个已发表的群体药代动力学模型(四个联合母体-代谢物模型和一个仅母体模型)预测的准确性和精密度。测试模型产生的预测精度相似(利培酮的均方根误差[RMSE]范围为0.021至0.027 nmol/ml,9-羟基利培酮为0.053 - 0.065 nmol/ml)。然而,其中一个使用丰富数据集开发的模型(一个三室混合模型,为三个亚组估计清除率)对利培酮的偏差较小(平均百分比误差[MPE,%]为1.0% 。101.4、146.9、260.4和292.4%)。相比之下,一个使用较少数据且群体与用于外部评估的群体更相似的模型对9-羟基利培酮的偏差较小(MPE:17% 。69.9、47.8和82.9%)。评估的模型似乎都不能推广到本分析中使用的群体。所有模型的预测性能都一般,这可能表明个体间变异性的来源没有被完全捕捉到,并表明来自高度异质性群体的机会性数据可能不是用于外部评估利培酮模型的最合适数据。