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Pharmacokinetic-pharmacodynamic modeling of antipsychotic drugs in patients with schizophrenia Part I: The use of PANSS total score and clinical utility

机译:抗精神病药在精神分裂症患者中的药代动力学药效学模型第I部分:PANSS总分的使用和临床应用

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Background: To develop a pharmacokinetic-pharmacodynamic (PK-PD) model using individual-level data of Positive and Negative Syndrome Scale (PANSS) total score to characterize the antipsychotic drug effect taking into account the placebo effect and dropout rate. In addition, a clinical utility (CU) criterion that describes the usefulness of a drug therapy was calculated using the efficacy of the drug and dropout rates. Methods: Data from 12 clinical trials in schizophrenia patients was used to quantify the effects of the antipsychotic drugs (APs), namely, haloperidol, risperidone, olanzapine, ziprasidone and paliperidone. Compartmental PK models were used to describe the time course of plasma drug concentrations. The combination of an Emax and the Weibull model was used to describe the drug and placebo effects. The steady-state drug concentrations were assumed to be the drivers of the exposure-response relationship. An exponential model was utilized to identify the predictors of probability of dropout. Simulations were performed to check the predictability of the model, and to calculate the CU of the drugs based on PANSS scores and dropout rates. Results: The maximal drug effect (Emax) was highest for olanzapine whilst it was lowest for ziprasidone. Higher observed PANSS scores resulted in a greater likelihood of dropout. Taking into account the efficacy and the drop-out rate, all APs possessed a comparable CU at the therapeutic doses. The resulting PK-PD model parameters were used to compute the effective concentration and dose required to produce a clinically meaningful 30% drop in PANSS score from the baseline. Conclusions: The developed PK-PD model and the associated CU score allow the evaluation of the time course of the PANSS scores of the different APs and a proper comparison of their clinically relevant treatments effects.
机译:背景:使用阳性和阴性综合征量表(PANSS)总分的个人水平数据开发药代动力学-药效学(PK-PD)模型,以考虑安慰剂作用和辍学率来表征抗精神病药物作用。另外,使用药物的疗效和辍学率计算出描述药物疗法有用性的临床效用(CU)标准。方法:使用来自精神分裂症患者的12项临床试验的数据来量化氟哌啶醇,利培酮,奥氮平,齐拉西酮和帕潘立酮等抗精神病药(AP)的作用。隔室PK模型用于描述血浆药物浓度的时间过程。 Emax和Weibull模型的组合用于描述药物和安慰剂的作用。假定稳态药物浓度是暴露-反应关系的驱动因素。使用指数模型来识别辍学概率的预测因子。进行仿真以检查模型的可预测性,并根据PANSS得分和辍学率计算药物的CU。结果:奥氮平的最大药物作用(Emax)最高,而齐拉西酮的最低。观察到的PANSS分数越高,辍学的可能性越大。考虑到疗效和退出率,所有AP在治疗剂量下均具有可比的CU。所得的PK-PD模型参数用于计算使PANSS得分从基线下降具有临床意义的30%所需的有效浓度和剂量。结论:发达的PK-PD模型和相关的CU评分可以评估不同AP的PANSS评分的时程,并可以适当比较其临床相关治疗效果。

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