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

SCHIZOPHRENIA RESEARCH

卷:146

Article

Reddy, Venkatesh Pilla¹  Kozielska, Magdalena¹  Suleiman, Ahmed Abbas¹  Johnson, Martin¹  Vermeulen, An²  Liu, Jing³  de Greef, Rik⁴  Groothuis, Geny M. M.¹  Danhof, Meindert⁵  Proost, Johannes H.¹ 

[1] Univ Groningen, Div Pharmacokinet Toxicol & Targeting, Univ Ctr Pharm, NL-9713 AV Groningen, Netherlands

[2] Janssen Res & Dev, Adv PKPD Modeling & Simulat, Beerse, Belgium

[3] Pfizer Global Res & Dev, Clin Pharmacol, Groton, CT 06340 USA

[4] Merck Sharp & Dohme Ltd, Merck Res Labs, Pharmacokinet Pharmacodynam & Drug Metab, Clin PK PD, Oss, Netherlands

[5] Leiden Amsterdam Ctr Drug Res, Div Pharmacol, Leiden, Netherlands

关键词: Antipsychotic drugs;    Population pharmacokinetics-pharmacodynamics;    PANSS total;    Placebo effect;    Dropout model;    Clinical utility;   

DOI  :  10.1016/j.schres.2013.02.011

来源: Elsevier

【 摘 要 】

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 E-max 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 (E-max) 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. (C) 2013 Elsevier B.V. All rights reserved.

【 授权许可】

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