Abnormal olanzapine toxicokinetic profiles--population pharmacokinetic analysis

Restarting antidepressant and antipsychotic medication after intentional overdoses: need for evidence-based guidance

Intentional drug overdoses with antidepressant and antipsychotic medications are an increasingly common problem. Currently, there is little guidance with regard to reintroduction of these medications after intentional overdoses. We have used published toxicological and pharmacokinetic data to obtain factors which control the recovery from overdoses. From such data, we have proposed guidance regarding their reintroduction, provided there are no adverse effects or contraindications. Tentatively, we suggest that when adverse effects from the overdose are lost, treatment could recommence after a further mean half-life of elimination. Most antidepressant and antipsychotic drugs are metabolized by cytochrome P450 enzymes and, where cytochrome P450 inhibitors are co-ingested, serial plasma concentrations should optimally be obtained in order to assess a suitable time for reintroduction of the psychoactive drugs. We hope the proposals presented will stimulate research and discussion that lead to better guidance for clinicians concerning reintroduction of psychoactive medication after intentional overdose.

Prediction of olanzapine exposure in individual patients using physiologically based pharmacokinetic modelling and simulation

AIM

The aim of the present study was to predict olanzapine (OLZ) exposure in individual patients using physiologically based pharmacokinetic modelling and simulation (PBPK M&S).

METHODS

A 'bottom-up' PBPK model for OLZ was constructed in Simcyp® (V14.1) and validated against pharmacokinetic studies and data from therapeutic drug monitoring (TDM). The physiological, demographic and genetic attributes of the 'healthy volunteer population' file in Simcyp® were then individualized to create 'virtual twins' of 14 patients. The predicted systemic exposure of OLZ in virtual twins was compared with measured concentration in corresponding patients. Predicted exposures were used to calculate a hypothetical decrease in exposure variability after OLZ dose adjustment.

RESULTS

The pharmacokinetic parameters of OLZ from single-dose studies were accurately predicted in healthy Caucasians [mean-fold errors (MFEs) ranged from 0.68 to 1.14], healthy Chinese (MFEs 0.82 to 1.18) and geriatric Caucasians (MFEs 0.55 to 1.30). Cumulative frequency plots of trough OLZ concentration were comparable between the virtual population and patients in a TDM database. After creating virtual twins in Simcyp®, the R2 values for predicted vs. observed trough OLZ concentrations were 0.833 for the full cohort of 14 patients and 0.884 for the 7 patients who had additional cytochrome P450 2C8 genotyping. The variability in OLZ exposure following hypothetical dose adjustment guided by PBPK M&S was twofold lower compared with a fixed-dose regimen - coefficient of variation values were 0.18 and 0.37, respectively.

CONCLUSIONS

Olanzapine exposure in individual patients was predicted using PBPK M&S. Repurposing of available PBPK M&S platforms is an option for model-informed precision dosing and requires further study to examine clinical potential.

Population pharmacokinetics analysis of olanzapine for Chinese psychotic patients based on clinical therapeutic drug monitoring data with assistance of meta-analysis

PURPOSE

The aim of this study was to build an eligible population pharmacokinetic (PK) model for olanzapine in Chinese psychotic patients based on therapeutic drug monitoring (TDM) data, with assistance of meta-analysis, to facilitate individualized therapy.

METHODS

Population PK analysis for olanzapine was performed using NONMEM software (version 7.3.0). TDM data were collected from Guangzhou Brain Hospital (China). Because of the limitations of TDM data, model-based meta-analysis was performed to construct a structural model to assist the modeling of TDM data as prior estimates. After analyzing related covariates, a simulation was performed to predict concentrations for different types of patients under common dose regimens.

RESULTS

A two-compartment model with first-order absorption and elimination was developed for olanzapine oral tablets, based on 23 articles with 390 data points. The model was then applied to the TDM data. Gender and smoking habits were found to be significant covariates that influence the clearance of olanzapine. To achieve a blood concentration of 20 ng/mL (the lower boundary of the recommended therapeutic range), simulation results indicated that the dose regimen of olanzapine should be 5 mg BID (twice a day), ≥ 5 mg QD (every day) plus 10 mg QN (every night), or >10 mg BID for female nonsmokers, male nonsmokers and male smokers, respectively.

CONCLUSION

The population PK model, built using meta-analysis, could facilitate the modeling of TDM data collected from Chinese psychotic patients. The factors that significantly influence olanzapine disposition were determined and the final model could be used for individualized treatment.