The Impact of Smoking, Sex, Infection, and Comedication Administration on Oral Olanzapine: A Population Pharmacokinetic Model in Chinese Psychiatric Patients.

BACKGROUND AND OBJECTIVE: Prior olanzapine population pharmacokinetic (PPK) models have focused on the effects of sex and smoking on olanzapine clearance. This PPK model in Chinese adult psychiatric patients also investigated the influence of comedications and co-occurrence of infections on olanzapine clearance, and explored how to personalize oral olanzapine dosage in the clinical setting. METHODS: A total of 1546 serum concentrations from 354 patients were collected in this study. A one-compartment model with first-order absorption was employed to develop the PPK model using a nonlinear mixed-effects modeling approach. Covariates included demographic parameters, co-occurrence of infection and concomitant medications (including dangguilonghui tablets, a Chinese herbal medicine for constipation). Bootstrap validation (1000 runs) and external validation of 50 patients were employed to evaluate the final model. Simulations were performed to explore the personalization of olanzapine dosing after stratification by sex, smoking, and comedication with valproate. RESULTS: Typical estimates for the absorption rate constant (Ka), apparent clearance (CL/F), and apparent distribution volume (V/F) were 0.30 h-1, 12.88 L/h, and 754.41 L, respectively. Olanzapine clearance was increased by the following variables: 1.23-fold by male sex, 1.23-fold by smoking, 1.23-fold by comedication with valproate, 1.16-fold by sertraline, and 2.01-fold by dangguilonghui tablets. Olanzapine clearance was decreased by the following variables: 0.75-fold by co-occurrence of infection, 0.70-fold by fluvoxamine, and 0.78-fold by perphenazine. The model evaluation indicated that the final model's performance was good, stable, and precise. CONCLUSION: This study contributes to the personalization of oral olanzapine dosing, but further studies should be performed to verify the effects of infection and comedications, including valproate and dangguilonghui.

This study included a total of 1546 serum olanzapine concentrations from 354 Chinese adult psychiatric patients that were analyzed by a complex mathematical model. The goal was to explore how oral olanzapine is eliminated from the body in Chinese psychiatric patients and how to personalize its dosing. Prior studies using similar complex mathematical models only studied the effects of sex and smoking on olanzapine elimination. This study also investigated the influence of co-occurrence of infection and comedications, including dangguilonghui tablets. This is a Chinese herbal medicine used to treat constipation, including constipation secondary to olanzapine treatment. Olanzapine elimination was increased by the following variables: 1.23-fold by male sex, 1.23-fold by smoking, 1.23-fold by comedication with valproate, 1.16-fold by sertraline, and 2.01-fold by dangguilonghui tablets. Olanzapine elimination was decreased by the following variables: 0.75-fold by co-occurrence of infection, 0.70-fold by fluvoxamine, and 0.78-fold by perphenazine. This study contributes to the improvement of oral olanzapine dosing personalization, but further studies are needed to verify the effects of infection and comedications, including valproate and dangguilonghui.

Identification of Potent Chloride Intracellular Channel Protein 1 Inhibitors from Traditional Chinese Medicine through Structure-Based Virtual Screening and Molecular Dynamics Analysis.

Chloride intracellular channel 1 (CLIC1) is involved in the development of most aggressive human tumors, including gastric, colon, lung, liver, and glioblastoma cancers. It has become an attractive new therapeutic target for several types of cancer. In this work, we aim to identify natural products as potent CLIC1 inhibitors from Traditional Chinese Medicine (TCM) database using structure-based virtual screening and molecular dynamics (MD) simulation. First, structure-based docking was employed to screen the refined TCM database and the top 500 TCM compounds were obtained and reranked by X-Score. Then, 30 potent hits were achieved from the top 500 TCM compounds using cluster and ligand-protein interaction analysis. Finally, MD simulation was employed to validate the stability of interactions between each hit and CLIC1 protein from docking simulation, and Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) analysis was used to refine the virtual hits. Six TCM compounds with top MM-GBSA scores and ideal-binding models were confirmed as the final hits. Our study provides information about the interaction between TCM compounds and CLIC1 protein, which may be helpful for further experimental investigations. In addition, the top 6 natural products structural scaffolds could serve as building blocks in designing drug-like molecules for CLIC1 inhibition.