Current Drug Metabolism - Volume 26, Issue 9, 2025

Polypharmacy is frequently practiced in the management of schizophrenia due to its chronic nature, recurrent relapses, and associated comorbidities. While combining psychotropic medications may benefit patients with treatment-resistant symptoms, it poses risks such as drug–drug interactions (DDIs), adverse effects, and reduced medication adherence. The absence of uniform prescribing standards further complicates clinical decision-making.

This narrative review was conducted using a scoping methodology. Databases including PubMed, Scopus, and Web of Science were searched for English-language publications from 2000 to 2024. Search terms included “schizophrenia,” “polypharmacy,” “drug–drug interactions,” “clinical outcomes,” and “pharmacogenetics.” Eligible sources included clinical trials, observational studies, systematic reviews, and treatment guidelines. Exclusion criteria were non-English articles, gray literature, and individual case reports.

Polypharmacy is reported in 30–60% of individuals with schizophrenia, especially in institutionalized or treatment-resistant populations. Treatment regimens often involve multiple antipsychotics along with adjunctive antidepressants or mood stabilizers. This approach is associated with increased risks of metabolic syndrome, cardiovascular events (e.g., QT prolongation), extrapyramidal symptoms, and decreased adherence. Interindividual variability in pharmacogenetics further affects drug efficacy and safety. Innovative approaches like genotype-guided therapy and computerized clinical decision-support systems are promising but not yet widely implemented.

Although polypharmacy may offer symptomatic relief in specific scenarios, it requires careful management due to its potential to cause harm. Rational prescribing, close monitoring, and attention to individual patient factors such as pharmacogenetic profiles are essential to optimize therapy.

Ensuring a balance between therapeutic benefit and adverse effects is crucial when employing polypharmacy in schizophrenia treatment. Integrating personalized medicine strategies, regular monitoring, and deprescribing practices when feasible can enhance clinical outcomes and patient safety.

This research aimed to establish a population pharmacokinetic (PPK) model for busulfan (Bu) in Chinese pediatric patients with thalassemia major. We analyzed pharmacokinetic (PK) parameter variability and explored potential covariates affecting Bu disposition using patient data. These findings are intended to support the optimization and personalization of Bu dosage regimens for children with thalassemia major.

Concentration-time samples were collected retrospectively from 62 pediatric patients with thalassemia major. These patients had previously received intravenous Bu as a preparatory regimen for allogeneic hematopoietic stem cell transplantation (allo-HSCT). A PPK model of Bu was developed through nonlinear mixed-effects modeling. This modeling process, conducted using NONMEM software, concurrently involved data analysis and examination of the effect of covariates on Bu pharmacokinetics. For validation purposes, the resulting model was evaluated against an external dataset consisting of 20 individuals.

The pharmacokinetic results were optimally analyzed using a model that incorporated a one-compartment model with first-order elimination. Body surface area (BSA) was subsequently identified as the most significant factor influencing both Bu clearance (CL) and volume of distribution (V). Diagnostic evaluations, encompassing goodness-of-fit plots, normalized prediction distribution errors, and visual predictive checks, confirmed the satisfactory fit and predictability of the final PPK model. Moreover, prediction-based diagnostic indices (MDPE%, 15.75; MAPE%, 22.26; F20%, 45.71; and F30%, 58.57) from external validation showed that no significant bias was detected when comparing the model's predicted concentrations against the observed data.

The present study developed the first PPK model characterizing the pharmacokinetics of Bu specifically in children with thalassemia major. This study's final PPK model demonstrated that BSA was the key predictive covariate for CL and V.

As a long-acting DPP-4 inhibitor administered orally once a week, trelagliptin can address the issues of frequent medication and poor compliance associated with traditional hypoglycemic drugs.

The Hypoxia model in rats was constructed at an altitude of approximately 4300 meters. The plasma concentration of trelagliptin was determined by LC-MS/MS. The biochemical indices and the protein expression levels of P-gp and OCT2 in the kidneys of rats were determined to explain the possible reasons for the pharmacokinetic changes of trelagliptin.

This study demonstrated that the pharmacokinetic parameters of trelagliptin were significantly changed in high-altitude hypoxic environments. Compared with the control group, the AUC, MRT, t1/2, and Vd were remarkably increased during acute and chronic hypoxia, while the CL and Ke were decreased. Additionally, the biochemical indexes and protein expression of P-gp and OCT2 were significantly altered.

The study demonstrated that high-altitude hypoxia significantly altered trelagliptin's pharmacokinetics, slowing clearance, prolonging elimination half-life and residence time, and increasing bioavailability. These changes suggested that the optimal therapeutic dosage of trelagliptin should be reassessed under hypoxic exposure.

In this pharmacokinetic (PK) study, the absorption, metabolism, and excretion of avacopan were evaluated following a single 100 mg/400 μCi oral ¹⁴C-avacopan dose solution in six healthy male participants. The mass balance recovery, plasma concentrations, and metabolite profile in plasma, urine, and feces were determined.

Fecal and renal excretion accounted for 77.2% and 9.5%, respectively, of the total administered radioactivity, with none of the mono- or bis-oxidation metabolites present at greater than 7% of the total radioactive dose. In urine, intact avacopan was present at <1% of the radioactive dose. In feces, intact avacopan was present at 8.7%, which represented 6.7% of the total radioactive dose, suggesting at least 93.3% of the radioactive dose was absorbed. The predominant component in plasma was avacopan, which accounted for 18.0% of the dose. The major circulating metabolite, M1, a monohydroxylation metabolite with similar potency in C5a receptor inhibition as avacopan, accounted for 11.9% of the total radioactivity.

The primary route of elimination of avacopan is phase I metabolism, followed by biliary excretion of the metabolites. CYP3A4 is the primary isozyme involved in the in vitro metabolism of avacopan and formation of metabolite M1.

Study results provide a definitive assessment of the absorption, elimination, and nature of metabolism of avacopan in humans.

Type 2 diabetes mellitus (T2DM), characterized by insulin resistance (IR) and hepatic ectopic lipid deposition (ELD), poses a complex metabolic challenge. This study aimed to elucidate the mechanisms of Yiqi Huazhuo Decoction (YD) through an integrated approach combining network pharmacology and metabolomics. T2DM is marked by impaired insulin signaling and disrupted hepatic lipid metabolism, resulting in a vicious cycle that accelerates disease progression. While Traditional Chinese Medicine (TCM), such as YD, demonstrates potential in modulating these dysfunctions, its underlying molecular mechanisms remain to be fully clarified.

A diabetic fat rat model was used to evaluate the efficacy of YD. UPLC-MS characterized the main metabolites found in YD. After an 8-week intervention, physiological indices and hepatic pathology were assessed. Network pharmacology identified bioactive metabolites and targets, which were validated by molecular docking. Untargeted metabolomics was employed to analyze hepatic metabolic changes.

YD improved glucose/lipid metabolism, insulin sensitivity, and hepatic function. Network pharmacology revealed that YD acts via the EGFR and PI3K-Akt/IL-17 pathways. Molecular docking confirmed luteolin-EGFR binding. Metabolomics identified 20 altered metabolites in the biosynthesis of unsaturated fatty acids. Multi-omics analysis revealed that YD regulated EGFR and hepatic metabolic networks.

The multi-metabolite, multi-target mechanism of YD distinguishes it apart from single-target drugs, such as metformin. The binding of luteolin to EGFR may potentially reactivate the PI3K-Akt signaling pathway, thereby enhancing insulin sensitivity. Regulation of metabolic pathways, including the biosynthesis of unsaturated fatty acids, contributes to the reduction of hepatic lipid deposition. These findings underscore the capacity of YD to disrupt the IR-ELD cycle in T2DM.

YD ameliorates T2DM-IR and hepatic ELD by modulating EGFR signaling and metabolic pathways, providing multi-omics evidence for its clinical application.