Predicting clozapine dose required to achieve a therapeutic plasma concentration - A comparison of a population algorithm and three algorithms based on gene variant models.

Abstract

Clozapine is the most effective antipsychotic but requires careful titration to therapeutic blood levels. Methods to predict therapeutic doses are based on population data. We aimed to construct a model based on genetic variants which accurately predicted plasma levels for clozapine. We measured clozapine plasma levels in patients on a stable dose of clozapine who were known to be fully compliant. Measured plasma levels were adjusted for sampling time and dose. Hepatic enzyme variants were analysed and models were constructed to predict the required dose. These predictions were compared with a standard population-based algorithm. We measured plasma clozapine concentrations in 18 adherent patients on stable doses of clozapine and recorded the exact timing of sampling. For the algorithm-predicted dose, the mean difference was -49.9 mg/day ((SD 155.9), r = 0.36) from the actual dose required to give a plasma concentration of 0.35 ng/ml. The gene variant activity score predicted a dose for which the mean difference was -43.5 mg/day ((SD 140.1), r = 0.55). For the gene variant activity score with omeprazole correction predicted dose, the mean difference was -31.0 mg/day ((SD 140.8), r = 0.54), and with the gene variant CYP1A2 inducibility predicted dose the mean difference was 44.9 mg/day ((SD 160.8), r = 0.32). Our gene variant activity score with omeprazole correction gave the best estimate of the clozapine dose required to achieve a minimum therapeutic plasma concentration. The use of this model will allow safer titration of clozapine and may reduce the need for plasma-level monitoring during titration.