Towards precision dosing in psychiatry: Population pharmacokinetics meta-modelling of clozapine and lithium

Abstract

Background:

Treatment optimization is mandatory in psychiatric diseases and the use of population pharmacokinetics (popPK) models through model informed precision dosing (MIPD) has the potential to improve patient medical care. In this perspective, meta-modelling methods could provide popPK models with improved predictive performances and most of covariates of interest. The aims of this study were to develop meta-models of clozapine and lithium, assess their predictability and propose optimized dosing regimens for both drugs.

Methods:

Two popPK models for each drug were retained to develop the meta-models. For clozapine, the model with the best predictive performances and gender as a covariate and one with smoking status were retained. For lithium, the model with the best predictive performances and fat-free mass as covariate and one with glomerular filtration rate were retained.

Results:

Both meta-models showed improved predictability compared to the original models. Clozapine meta-model simulations allowed us to propose dosing regimen according to gender and smoking status. Steady-state doses ranged from 375 to 725 mg/day for clozapine once daily, and from 350 to 650 mg/day for clozapine twice daily. Lithium meta-model simulations allowed us to propose dosing regimen according to weight, body mass index, gender and GFR. Our steady-state dose propositions ranged from 625 to 1125 mg/day for males, and from 375 to 750 mg/day for females.

Conclusion:

Both meta-models met the acceptability criteria for use in clinical practice on all subpopulations of interest. Those models could be used in the perspective of MIPD for clozapine and lithium.