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This page is an AI-assisted Turkish summary of the study presented at the 26th World Congress of Psychiatry. The study belongs to the presenting authors; please refer to the original source when citing it.

SO103

Predicting clozapine toxicity risk during ECT augmentation using an inflammation-based quantitative systems pharmacology framework

PREDICTING CLOZAPINE TOXICITY RISK DURING ECT AUGMENTATION USING AN INFLAMMATION-BASED QSP FRAMEWORK

Electroconvulsive therapy–induced cytokine surges progressively suppress CYP1A2 activity, leading to clozapine accumulation and toxicity-associated D2 receptor occupancy after the fourth session.

The study aimed to develop and validate a quantitative systems pharmacology (QSP) model to test whether electroconvulsive therapy (ECT) increases clozapine levels by triggering inflammation. The modular model, built in Python 3.8, integrated a two-compartment physiologically based pharmacokinetic structure, the ECT-induced inflammatory response, and CYP1A2 enzyme inhibition mediated by IL-6, CRP, and TNF-alpha. Parameters were derived from published clinical and population pharmacokinetic data, in vitro cytokine–CYP1A2 data, and therapeutic drug monitoring records, including cases with more than threefold increases in concentration; successful validation was defined as a prediction error within 25% of observed concentrations. A standard six-session ECT course delivered over two weeks (Monday, Wednesday, Friday) was simulated in patients at clozapine steady state, with twice-daily dosing over 336 hours and 3,000 time points. ECT produced rapid, transient increases of more than 100-fold in IL-6, a delayed but sustained approximately 15-fold elevation in CRP, and lower-amplitude peak-and-decline patterns of approximately 10-fold in TNF-alpha; CYP1A2 activity decreased progressively to approximately 30% of baseline. Dopamine D2 receptor occupancy rose from approximately 51% before ECT to more than 83% after six sessions, exceeding the toxicity-associated threshold of 80% after the fourth session. The model predicted 3.7-fold clozapine accumulation, while retrospective assessment of fit yielded results consistent with the observed two- to sixfold increases in concentration. Sensitivity analysis identified the magnitude of the IL-6 surge and the potency of CYP1A2 inhibition as the primary determinants of toxicity risk, together accounting for approximately 70% of the variance. The model is proposed as a model-based risk prediction tool to reduce the risks of delirium, seizures, myocarditis, and neutropenia during ECT augmentation through a 25% to 50% dose reduction before ECT, monitoring stratified by metabolizer status, and individualized ECT scheduling.

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