This systematic review aimed to identify, evaluate, and critically an-alyze pharmacokinetic models of vancomycin in adult populations published in PubMed and EMBASE between 2020 and 2024. Twenty-two studies were included, describing 24 models character-ized by substantial heterogeneity in terms of study populations, methodological design, and covariate selection. Most models were developed in Asia and focused on hospitalized patients, particularly those in intensive care units (ICUs). Data from 2150 patients were analyzed, with an average of 93 patients per model. The models demonstrated high variability in pharmacokinetic parameters, such as vancomycin clearance (Cl) and volume of distribution (Vd), influenced by factors, such as renal function, weight, age, and comorbidities. The meta-analysis conducted on clearance and interindividual variability in clearance (IIV Cl) revealed high heterogeneity among the ana-lyzed studies. The average vancomycin clearance was 4.23 L/h, with higher values observed in neurosurgical, oncohematologic patients, and those with increased renal function. The vol-ume of distribution showed greater variability in obese patients and those undergoing continu-ous renal replacement therapy. Creatinine clearance (ClCr) was identified as a significant co-variate in 66% of the models, while weight was significant in 33%. Other important covariates included age, sex, serum creatinine, serum urea, and the hospital admission unit. The meta-analysis of Cl and IIV Cl showed high heterogeneity among the studies, with I² values of 0.83 for Cl and 0.98 for IIV Cl, indicating substantial variability. The limitations of this study included the diversity of the analyzed populations, which made it challenging to assess the model's suitability. While the models showed advances in precision, challenges, such as the lack of external validation and discrepancies in dosing recommendations, remain. This review paper has highlighted the need to validate models in diverse popula-tions and clinical settings to optimize personalized vancomycin therapy in adults. The findings have highlighted the importance of validating or adapting pharmacokinetic models to the spe-cific characteristics of each hospital population.

Drug-induced hepatotoxicity (DIH) poses a significant clinical challenge due to its unpredicta-ble nature and diverse manifestations. The liver, with its central role in metabolism and close association with the gastrointestinal tract, is particularly susceptible to drug-induced toxicity. DIH encompasses a spectrum of liver injuries, including hepatocellular, cholestatic, and mixed patterns, which may increase the risk of other liver diseases. This review examines diverse examples and molecular mechanisms under-lying DIH, highlighting the influence of genetic predisposition, drug interactions, and pre-existing liver conditions. Given the complexity and variability of hepatotoxic responses to numerous medications, un-derstanding these mechanisms is crucial for improving the diagnosis and management of DIH.

<p>Introduction: The currently available therapies for acute lung injury (ALI), including gluco-corticoids, protease inhibitors, and heparin, have limited clinical efficacy and are often associated with significant side effects. Cepharanthine (CEP) has demonstrated effectiveness in treating pulmonary dis-eases, but its clinical application is restricted by low solubility and poor bioavailability. This study aimed to develop mannosylated cepharanthine-loaded polymeric micelles (MA-CEP-PMs) to improve CEP bio-availability and enhance lung-targeted delivery for the treatment of ALI. </p><p> Methods: The pharmacokinetics of MA-CEP-PMs in rats were assessed using Ultra-Performance Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry (UPLC-Q-TOF-MS). Lung-targeting ability was evaluated through tissue distribution studies and near-infrared imaging. In a rat model of ALI induced by lipopolysaccharide (LPS), anti-ALI effects were assessed via general physiological indicators, Enzyme-Linked Immunosorbent Assay (ELISA), and Western blot analysis. Hematoxylin-eosin (HE) staining was used to examine hepatotoxicity and nephrotoxicity of MA-CEP-PMs in normal rats. Cyto-toxicity of the mannosylated polyethylene glycol-poly(lactic-co-glycolic acid) copolymer (MA-PEG-PLGA) on NR8383 cells was evaluated using the Cell Counting Kit-8 (CCK-8) assay. Cellular uptake experiments were performed to determine the targeting ability of MA-PEG-PLGA in NR8383 cells, and the effects of MA-CEP-PMs on inflammatory cytokines were analyzed using ELISA.</p><p> Results: MA-CEP-PMs significantly increased the AUC and exhibited better lung targeting ability com-pared to the unmodified micelles (P < 0.01). In the ALI model, MA-CEP-PMs improved the thymus and spleen indices, decreased the lung wet-to-dry weight ratio (P < 0.05), alleviated model animal damage, and inhibited inflammatory factor and nuclear factor-κB (NF-κB)-related protein levels (P < 0.05). MA-CEP-PMs exhibited no significant hepatotoxicity or nephrotoxicity. MA-PEG-PLGA exhibited low tox-icity against NR8383 cells and greater cell uptake, indicating stronger targeting of the lung. MA-CEP-PMs also exhibited more potent anti-inflammatory effects.</p><p> Discussion: This study focused on the short-term therapeutic effects of ALI, whereas the clinical man-agement of lung injury often requires long-term intervention. Future research should therefore assess the long-term efficacy of this delivery system in chronic lung injury, along with determining its safety profile and potential impacts on extra-pulmonary organs. While the involvement of the NF-κB pathway in the anti-inflammatory effects has been confirmed, it remains to be deciphered whether mannose modification synergistically regulates other signaling pathways and what the specific intracellular targets of CEP are, which would require further exploration through detailed molecular biology experiments.</p><p> Conclusion: The MA-CEP-PMs significantly improved CEP bioavailability and increased lung targeting. They exhibited good safety and had a significant effect on ALI management.</p>.

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.

Systemic Lupus Erythematosus (SLE) is a multifactorial autoimmune disorder in-fluenced by genetic predisposition, immune dysregulation, environmental triggers, and epi-genetic modifications. Despite advances in treatment, many patients experience recurrent symptoms and adverse effects. Recent large-scale studies have revealed significant alterations in proteins, glycopeptides, and metabolites in SLE, deepening our understanding of its path-ogenesis. Emerging omics technologies, such as proteomics, glycomics, and metabolomics, enable the high-throughput identification of disease-related biomarkers. However, biological processes are typically driven by the interplay among multiple molecular layers. Therefore, integrative multi-omics approaches have become essential for uncovering potential bi-omarkers and risk factors. This review summarizes the classification of SLE biomarkers and recent advances in diagnostic applications across proteomics, glycomics, and metabolomics, aiming to support the development of more precise diagnostic strategies for SLE.

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. 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. 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. 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.

<p> 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. </p><p> 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. </p><p> 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. </p><p> 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.

<p> 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. </p><p> 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. </p><p> 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. </p><p> 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.

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.