Current drug metabolism最新文献

Traditional treatment methods for the management of diabetes, such as oral hypoglycemic med-ications and insulin injections, include drawbacks like systemic adverse effects, inconsistent medication levels, and low compliance. To avoid difficulties, glycemic levels in diabetic patients, a long-term meta-bolic condition, must be precisely and consistently controlled. Smart therapeutic systems allow for precise, on-demand medication release in response to local physiological or environmental cues, such as glucose levels, pH, temperature, or enzyme activity. They provide a possible substitute for conventional diabetic therapies. As these systems only administer medications when and where needed, they reduce side effects while simultaneously increasing therapeutic efficacy and patient compliance. These systems are designed to respond to signals from external sources (such as light, ultrasound, or magnetic fields) or stimuli like temperature, pH, glucose levels, and enzymes. As they use glucose-sensitive substances like phenyl-boronic acid, glucose oxidase, or polymers to precisely release insulin in hyperglycemic circumstances, glucose-responsive delivery methods are essential for diabetes. This review discusses a stimuli-responsive drug delivery system designed for diabetes treatment, with a focus on the developments in biomaterials, nanotechnology, and engineering that improve its effectiveness and biocompatibility. Along with the pos-sibility of combining a stimuli-responsive drug delivery system with wearable technology for continuous glucose monitoring and intelligent insulin delivery, issues, such as manufacturing complexity, stability, and patient safety, are also addressed. The stimuli-responsive drug delivery system has the potential to revolutionize diabetes management by bridging the gap between physiological needs and therapeutic de-livery, providing better glucose control, fewer side effects, and an enhanced standard of living for patients.

Objective: The objective of this study was to investigate the mechanism of anti-cerebral ischemia-reperfusion injury (anti-CIRI) of Ai pian by using the network pharmacology approach combined with serum metabolomics technique based on UPLC-MS.

Methods: The cerebral ischemia-reperfusion injury (CIRI) model was established by middle cerebral artery occlusion (MCAO). The therapeutic effect of Ai pian on CIRI rats was evaluated by behavioral test, 2,3,5-triphenyltetrazolium chloride (TTC) staining, Nissl staining, and hematoxylin-eosin (HE) staining. The active compound-potential target-disease network for Ai Pian in the treatment of CIRI was established using network pharmacology methods. Rat serum was detected by the metabolomics technique based on UPLC-MS. A Western blot was used to validate common targets of the network pharmacology approach combined with serum metabolomics.

Results: The process of treating CIRI with Ai Pian involved regulating enzyme, nuclear receptor, and transcription factor activity, managing the inflammatory response, and participating in biofilm composition. Twenty endogenous potential biomarkers were screened and submitted to MetaboAnalyst 6.0 for pathway and enrichment analysis. Four metabolic pathways were identified: butanoate metabolism, fructose and mannose metabolism, alanine, aspartate, and glutamate metabolism, and pyrimidine metabolism. Fructose and mannose metabolism and pyrimidine metabolism were two key pathways. Western blot analysis suggested that DHODH, TYMS, and AKR1B1 may be targets through which therapeutic effects are exerted.

Conclusion: This research contributed to the development of Ai pian as an adjunctive drug for treating CIRI and provided a basis for further research on CIRI.

Objectives: 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. Revealing the pharmacokinetic changes of trelagliptin is particularly important for populations in high-altitude hypoxic environments.

Methods: 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 pro-tein 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.

Results: 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 de-creased. Additionally, the biochemical indexes and protein expression of P-gp and OCT2 were signifi-cantly altered.

Conclusion: The study demonstrated that high-altitude hypoxia significantly altered trelagliptin's phar-macokinetics, slowing clearance, prolonging elimination half-life and residence time, and increasing bio-availability. These changes suggested that the optimal therapeutic dosage of trelagliptin should be reas-sessed under hypoxic exposure.

Purpose: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

Introduction: Avacopan (Tavneos®) is approved as an oral adjunctive treatment at a dose of 30 mg twice daily with food for adult patients with severe active Granulomatosis with Polyangiitis (GPA) and Microscopic Polyangiitis (MPA) in combination with standard therapy including glucocorticoids.

Methods: 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.

Results: 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.

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

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

Introduction: 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.

Methods: 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.

Results: 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.

Discussion: 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.

Conclusion: 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.

Introduction: 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 inte-grated 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 mecha-nisms remain to be fully clarified.

Materials and methods: 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.

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

Discussion: 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 re-activate 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.

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

Rare diseases present unique challenges in drug discovery and development, primarily due to small patient populations, limited clinical data, and significant variability in disease mechanisms. The primary objective of this review is to examine the integration of pharmacokinetics (PK) and drug metabolism data into data-driven drug discovery approaches, particularly in the context of rare diseases. By incorporating advanced computational techniques such as Machine Learning (ML) and Artificial Intelligence (AI), researchers can better predict PK parameters, optimize drug candidates, and identify personalized therapeutic strategies. AI integration with genomic and proteomic data reveals previously unidentifiable pathways, fostering collaboration among researchers, clinicians, and pharmaceutical companies. This interdisciplinary approach reduces development timelines and costs while enhancing the precision and effectiveness of therapies for patients with rare diseases. This review highlights the critical role of absorption, distribution, metabolism, and excretion (ADME) in understanding drug behavior in genetically diverse populations, thereby enabling the development of tailored treatments for patients with rare diseases. Additionally, it evaluates the opportunities and limitations of integrating PK/PD (pharmacodynamics) models with multi-omics data to improve drug discovery efficiency. Key examples of enzyme-drug interactions, metabolic pathway analysis, and AIbased PK simulations are discussed to illustrate advancements in predictive accuracy and drug safety. This review concludes by emphasizing the transformative potential of integrating PK and metabolism studies into the broader framework of data-driven drug discovery, ultimately accelerating therapeutic innovation and addressing unmet medical needs in rare diseases.

Licochalcone A (LCA) is an important secondary metabolite in licorice that has attracted extensive attention due to its unique species-specific distribution characteristics and various pharmacodynamic activities, particularly its anti-inflammatory and anti-cancer effects. LCA was originally considered exclusive to Glycyrrhiza inflata Batal. However, further analyses have shown its distribution in different licorice species, extending its known distribution among licorice species and suggesting a broader role in secondary metabolism. Nevertheless, the complex chemical synthesis of LCA presents challenges in regioselectivity control. The oral bioavailability of LCA is limited due to the intestinal first-pass effect, and its metabolic mechanism has not yet been fully elucidated. These issues restrict the therapeutic effects and practical applications of LCA in vivo. In recent years, advancements in optimizing synthetic pathways and developing new delivery systems have significantly improved the efficacy of LCA while also achieving notable breakthroughs in its safety. This review examines the distribution patterns, synthesis methods, in vivo metabolic processes, pharmacological activities, and current application status of LCA, while also exploring future research directions. However, its metabolic mechanisms and prospects for clinical application still require further investigation in the future. A multisource database search related literature employed "Licochalcone A"as the anchor term, synergized with species taxonomy (Glycyrrhiza), biogeographic patterns, and phytochemical dynamics (biosynthesis/metabolism).