Pharmacokinetic-pharmacodynamic modelling of antipsychotic drugs in patients with schizophrenia: Part II: The use of subscales of the PANSS score

Venkatesh Pilla Reddy, Magdalena Kozielska, Ahmed Abbas Suleiman, Martin Johnson, An Vermeulen, Jing Liu, Rik de Greef, Geny M. M. Groothuis, Meindert Danhof, Johannes H. Proost*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Background and objectives: The superiority of atypical antipsychotics (also known as second-generation antipsychotics (SGAs)) over typical antipsychotics (first generation antipsychotics (FGAs)) for negative symptom control in schizophrenic patients is widely debated. The objective of this study was to characterize the time course of the scores of the 3 subscales (positive, negative, general) of the Positive and Negative Syndrome Scale (PANSS) after treatment of patients with antipsychotics, and to compare the control of negative symptom by SGAs versus a FGA (haloperidol) using pharmacokinetic and pharmacodynamic (PKPD) modelling. In addition, to obtain insight in the relationship between the clinical efficacy and the in vitro and in vivo receptor pharmacology profiles, the D-2 and 5-HT2A receptor occupancy levels of antipsychotics were related to the effective concentrations.

Methods: The PKPD model structure developed earlier (part I) was used to quantify the drug effect using the 3 PANSS subscales. The maximum drug effect sizes (E-max) of oral SGAs (risperidone, olanzapine, ziprasidone, and paliperidone) across PANSS subscales were compared with that of haloperidol, while accounting for the placebo effect. Using the estimates of PKPD model parameters, the effective concentrations (C-eff) needed to achieve 30% reduction in the PANSS subscales were computed. Calculated effective concentrations were then correlated with receptor pharmacology profiles.

Results: Positive symptoms of schizophrenia responded well to all antipsychotics. Olanzapine showed a better effect towards negative symptoms than the other SGAs and haloperidol. Dropout modelling results showed that the probability of a patient dropping out from a trial was associated with all subscales, but was more strongly correlated with the positive subscale than with the negative or the general subscales. Our results suggest that different levels of D-2 or 5-HT2A receptor occupancy are required to achieve improvement in PANSS subscales.

Conclusions: This PKPD modelling approach can be helpful to differentiate the effect of antipsychotics across the different symptom domains of schizophrenia. Our analysis revealed that olanzapine seems to be superior in treating the negative symptoms compared to other non-clozapine SGAs. The relationship between receptor pharmacology profiles of the antipsychotics and their clinical efficacy is not yet fully understood. (C) 2013 Elsevier B.V. All rights reserved.

Original languageEnglish
Pages (from-to)153-161
Number of pages9
JournalSchizophrenia Research
Issue number1-3
Publication statusPublished - May-2013


  • Antipsychotic drugs
  • Population pharmacokinetic-pharmacodynamic modelling
  • PANSS subscales
  • Placebo effect
  • Dropout model

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