Modeling Approach with Therapeutic Drug Monitoring Data to Describe Time Course of Clozapine Exposure and Positive and Negative Syndrome Scale Scores

Abstract

Objective: The Positive and Negative Syndrome Scale (PANSS) is commonly used to assess the severity of the clinical symptoms of schizophrenia (SCZ). This study aimed to develop a pharmacokinetic (PK)/pharmacodynamic (PD) model based on therapeutic drug monitoring (TDM) data to characterize the relationship between clozapine exposure and the PANSS scores in patients with SCZ.

Methods: TDM data for clozapine and PANSS scores from 45 patients with SCZ were included in this modeling analysis using NONMEM. Based on published data, intensive PK sampling data collected up to 12 hours postdose from 23 patients was incorporated into the PK data set to improve the fitting of absorption and disposition. For PD model development, the PANSS score was assessed at baseline, followed by 8 and 18 weeks after the initiation of clozapine dosing. Visual predictive check plots, the precision of parameter estimates, and decreases in the minimum objective function values were used for the model evaluation.

Results: A 2-compartment model with an absorption lag and a combined error model adequately described the PK of clozapine. The implementation of disease progression with placebo and drug effects improved the model's ability to describe the time course of the PANSS scores. In the final PK/PD model, Weibull and maximum effect (E max ) models were selected as disease progression models for the placebo and drug effect models, respectively. The model evaluation results supported the adequacy of the final model.

Conclusions: A clozapine PK/PD model based on clinical settings adequately described the PANSS time course in patients with SCZ. These findings may aid the development of treatment strategies for patients with SCZ.