Application of Physiologically Based Pharmacokinetic Modeling to Predict the Effect of Renal Impairment on the Pharmacokinetics of Olanzapine and Samidorphan Given in Combination
2020
A combination of the antipsychotic olanzapine and opioid receptor antagonist samidorphan (OLZ/SAM) is in development for the treatment of patients with schizophrenia or bipolar I disorder. The effect of severe renal impairment on the pharmacokinetics of olanzapine and samidorphan after a single oral dose of OLZ/SAM was evaluated in a clinical study. Complementary to the clinical findings, physiologically based pharmacokinetic modeling was used to assess the effects of varying degrees of renal impairment on the pharmacokinetics of olanzapine and samidorphan. A physiologically based pharmacokinetic model for OLZ/SAM was developed and validated by comparing model-simulated data with observed clinical data. The model was applied to predict changes in olanzapine and samidorphan pharmacokinetics after administration of OLZ/SAM in subjects with mild, moderate, and severe renal impairment relative to age-matched controls with normal renal function. The model predicted 1.5- and 2.2-fold increases in olanzapine and samidorphan area under the plasma concentration–time curve (AUC), respectively, after a single dose of OLZ/SAM in subjects with severe renal impairment vs controls, which was consistent with results from the clinical study. Application of the model prediction indicated increases in steady-state olanzapine AUC of 1.2-, 1.5-, and 1.6-fold, and samidorphan AUC of 1.4-, 1.8-, and 2.2-fold, in subjects with mild, moderate, and severe renal impairment, respectively, relative to healthy controls. Physiologically based pharmacokinetic modeling extended the findings from a clinical study in severe renal impairment to other untested clinical scenarios; these data could be of interest to clinicians treating patients with renal impairment.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
35
References
2
Citations
NaN
KQI