Abstract: The interplay between the environmental exposome and the cancer genome remains a critical "blind spot" in precision oncology. While somatic mutational signatures genomic fossils imprinted by exposures such as ultraviolet radiation, tobacco smoke, and industrial pollutants are well characterized for their etiological significance, their functional impact on therapeutic efficacy remains largely unexplored. We hypothesized that these environmental "genomic scars" induce distinct pharmacogenomic vulnerabilities (collateral sensitivity) and resistance mechanisms (collateral resistance) that vary by geographical exposure patterns. Here, we present the first global "Geo-Pharmacogenomic" atlas, integrating 41 COSMIC mutational signatures with drug response profiles from 1,001 cancer cell lines across four large-scale pharmacogenomic screens (GDSC1, GDSC2, CTRP, CCLE). By harmonizing disparate drug sensitivity metrics and applying rigorous statistical controls for tissue lineage, we identified and validated 608 significant signature-drug interactions (P < 0.01). We demonstrate that UV-associated signature SBS7a is a broad-spectrum driver of therapeutic resistance, conferring intrinsic insensitivity to BRAF inhibitors (PLX-4720, P < 10^-4) and Notch inhibitors globally. Conversely, we uncover a novel synthetic lethal vulnerability wherein pollution-driven oxidative stress (SBS18) sensitizes tumors to p38 MAPK inhibition (VX-702, r = -0.45, P < 10^-9). Synthesizing these findings with satellite-derived atmospheric data (World Bank/NASA AOD), we constructed a Kriging-interpolated risk surface spanning 122 nations. This analysis predicts distinct "Resistance Landscapes with high-intensity drug resistance predicted in pollution-dense megacities (e.g., Beijing, New Delhi) challenging the paradigm of uniform drug efficacy. Our results establish environmental history as a functional biomarker, necessitating a paradigm shift towards geographically stratified precision medicine.

Abstract: Selected organic sunscreens from different chemical families were investigated in the context of their ability to inhibit butyrylcholinesterase using novel Multiple Linear Regression, Artificial Neural Network and Support Vector Regression models based on a set of six independent variables commonly associated with compounds’ absorption and distribution properties. It was established that the descriptors that have a particularly strong, positive influence on the ability of compounds to inhibit BChE expressed as pIC₅₀ are the count of rotatable bonds (nRot) and lipophilicity (log D); pIC₅₀ is negatively correlated with flexibility (Flex), fraction of sp3 carbon atoms (F_sp3), caco-2 permeability (caco2) and plasma protein binding ability (PPB). The sunscreens that are likely to be particularly strong BChE inhibitors are Ethylhexyl Triazone (ET), Diethylhexyl Butamido Triazone (DOBT), Octocrylene (OCR) and Diethylamino Hydroxybenzoyl Hexyl Benzoate (DHHB), although in must be stressed that ET and DOBT are outside the chemical space of the reference compounds.

Abstract: Objective: The purpose of this preliminary study was to evaluate the use of the Zipf-Mandelbrot (ZM) law to mathematically model the percentage occurrence of adverse drug reactions (ADRs), as a function of rank, reported to the US FDA Adverse Event Monitoring System (AMES). Methods: Six commonly used hospital-based medications were examined. Nonlinear curve fitting of the two ZM coefficients was utilized to model the percentage occurrence of ADRs in a hierarchical or rank order for each drug examined. Results: The reported complications and their associated occurrence rates for all six medications were accurately modelled using the ZM law. Those medications which have a greater percentage of reported ADRs within their first ten ranks have a greater negative slope. Furthermore, a natural logarithmic transformation of both the reported FDA data and the predicted values utilizing the ZM law demonstrated a consistent statistically significant near-linear correlation. The ratio of the coefficients of the ZM law, a∙b^(-1), was also found to be a potentially useful index which allows for describing and comparing the overall shape of the medication-specific distributions. Conclusions: Based upon this preliminary examination, the ZM law appears to be applicable to the mathematical modeling of US FDA reported ADRs. Additional research to assess and utilize this law for the analysis, economic management, and possible improvement in patient outcome may be warranted.

Abstract: The application of computational technologies in veterinary biochemistry and toxicology is revolutionizing translational science and making it more compatible with the One Health approach. With the distinction between animal, human, and environmental health diminishing in importance, technologies like molecular modelling, systems toxicology, vetinformatics, and artificial intelligence (AI) help in making integrated and predictive decisions. This brief review aims to highlight advancements in computational veterinary biochemistry and toxicology with special emphasis on its importance for One Health, food safety, and antimicrobial resistance (AMR). Advances in predictive toxicology, multi-omics, and AI offer new and innovative solutions for the early detection of biochemical disorders, simulation of toxicant exposure, and prediction of AMR in different species. These advancements highlight the importance of making connections between laboratory science and policy-making for animal health with the help of a multidisciplinary computational approach for global food security and AMR in a data-driven world.

Abstract: Dimethyl fumarate (DMF), a fumaric acid ester, is approved for psoriasis and multiple sclerosis due to its antioxidant and anti-inflammatory properties mediated via Nrf2 activation. Nrf2 regulates genes that protect cells from oxidative stress, a key factor in neurodegenerative diseases such as Alzheimer's disease (AD), which is characterized by amyloid-β and tau accumulation and lipid peroxidation. This systematic review aimed to evaluate preclinical evidence for DMF as a potential therapeutic agent in AD models through Nrf2 activation. A comprehensive literature search identified in vitro, in vivo, and combined preclinical studies assessing DMF in AD models. Studies were screened using predefined inclusion and exclusion criteria, with quality assessment and flow chart analysis applied. Eighteen studies were ultimately included in the analysis. Results consistently demonstrated that DMF activates the Nrf2 pathway, enhancing antioxidant and anti-inflammatory gene expression. DMF treatment reduced amyloid-β and tau protein levels, mitigated oxidative stress, and improved cognitive performance in animal models. In conclusion, preclinical evidence suggests DMF is a promising candidate for AD treatment by targeting oxidative stress and neuroinflammation via Nrf2 activation. Further preclinical studies, particularly on ferroptosis mechanisms, as well as well-designed clinical studies are warranted to clarify its full therapeutic potential.

Abstract: Research demonstrates that highly diluted solutions can modify the physicochemical and biological properties of the substance from which they are derived. This modifying effect is attributed to the mechanical vibration (such as stirring or shaking) applied during preparation process. By subjecting the initial substance and a neutral carrier directly to vibrational treatment, "vibrational iterations" had been developed that retain these modifying properties while bypassing the serial dilution process entirely. The development and application of these approaches to obtain products that modify the properties of the initial substance is hereafter defined as vibration-gradual technology. This technology has facilitated the development of therapeutics based on high dilutions of antibodies and, more recently, vibrational iterations derived from diverse complex biological structures. Evidently, vibrational iterations offer substantial potential for the treatment of various pathologies, including oncological diseases. This review outlines the research milestones leading to these developments, summarizes current experimental data, and proposes the 'supramolecular matrix' hypothesis to explain the mechanisms underlying the modifying effect.

Abstract:

Background: Cancer remains a major global health challenge, with treatment efficacy limited by drug resistance and adverse effects. Drug repurposing offers opportunities for novel anticancer strategies. This study evaluated the cytotoxic, antiproliferative, and pro-apoptotic effects of metformin and caffeine, alone and in combination, in human cancer cell lines, and their potentialinteraction mechanisms. Methods: Human cervical carcinoma (HeLa), lung adenocarcinoma (A549), and colorectal carcinoma (HT29) cell lines were treated with metformin (0.05–50 mM) and caffeine (0.5–5 mM), alone or combined, for 24 and 48 h. Cell viability and proliferation were assessed using Trypan Blue and sulforhodamine B (SRB) assays. Apoptosis was analyzed by Annexin V/propidium iodide flow cytometry, and p53 expression in HeLa cells was determined by ELISA. Statistical analysis was performed using one-way ANOVA with Tukey’s post hoc test. Results: Metformin induced dose- and time-dependent cytotoxicity in all cell lines, with the lowest IC₅₀ values in HeLa and A549 cells after 48 h (2.28 and 3.30 mM; p < 0.05). Caffeine showed moderate antiproliferative activity, with strongest effects at 2.03 mM in HeLa and 2.01 mM in HT29 cells (p < 0.05). Combined treatment demonstrated variable effects depending on the cell line and treatment duration, with limited synergistic interaction observed only under specific conditions, while predominantly antagonistic effects were detected overall. Increased apoptosis and elevated p53 expression suggest activation of tumor-suppressive pathways. Conclusions: Metformin exhibits significant anticancer activity in vitro, supporting metformin repurposing in oncology. However,the addition of caffeine does not uniformly enhance its efficacy and appears to exert context-dependent effects.Further in vivo studies are required to confirm its clinical relevance.

Abstract: Highly pathogenic avian influenza (HPAI) H5N1 clade 2.3.4.4b continues to circulate extensively among wild birds, poultry, and mammals, presenting ongoing risks at the intersection of human, animal, and environmental health. Antiviral approaches tailored for poultry farming or farm settings are still largely under investigation. The influenza A polymerase acidic (PA) endonuclease, which plays a key role in cap-snatching during viral transcription, is a conserved antiviral target across different host species. This research introduces a computational workflow to detect PA endonuclease inhibitors suitable for veterinary and environmental use. Homology modelling of recent H5N1 clade 2.3.4.4b PA sequences (2021–2025) was performed based on the crystallographic structure 6FS8. A curated ligand library, including reference inhibitors, hydrophilic metal-binding scaffolds, and repurposed antivirals, was screened via cross-host molecular docking against poultry- and mammalian-specific PA models. Docking results highlighted baloxavir and entecavir as top candidates due to their strong and consistent binding profiles across multiple targets. Entecavir showed particularly promising binding affinity in the poultry PA model (−100.6), similar to the reference inhibitor baloxavir (−97.5 to −97.7). A 170 ns molecular dynamics simulation of the poultry PA–entecavir complex indicated stable structural behavior, with RMSD below 1.1 Å, and MM/PBSA calculations gave a binding free energy of ΔG = −85.1 ± 0.8 kJ/mol. Physicochemical analysis revealed entecavir's high polarity and predicted water solubility, suggesting its suitability for water-based or environmental delivery within poultry facilities. Overall, this study introduces a One Health–focused computational framework that integrates cross-host structural modeling, docking, molecular dynamics, and agrochemical suitability filtering to identify promising antiviral candidates for poultry outbreak control. The results point to entecavir as a promising candidate for further evaluation in veterinary antiviral studies.

Abstract: Antimicrobial resistance is one of the most important global public health challenges, particularly in low and middle-income countries where antimicrobial consumption remains high. In Brazil, several regulatory measures have been implemented over the last decade to improve control over antimicrobial use, including restrictions on over-the-counter sales and strengthened monitoring of antimicrobial dispensing. This article provides an overview of antimicrobial use, regulatory measures, and resistance-related challenges in Brazil. Evidence from epidemiological studies, antimicrobial dispensing records, national monitoring initiatives coordinated by the Brazilian Health Regulatory Agency (ANVISA), the National System for Controlled Product Management (SNGPC), and antimicrobial resistance surveillance efforts, including GLASS/BR-GLASS and national reports on healthcare-associated infections and resistance, was considered to identify trends in antimicrobial consumption, regional variation, and the influence of public health policies. Available data indicate that antibiotics such as amoxicillin, azithromycin, and cephalosporins remain among the most commonly dispensed antimicrobials in community settings. Regulatory measures have strengthened prescription requirements, improved oversight of antimicrobial dispensing, and reduced unrestricted non-prescription sales, although their broader impact on inappropriate clinical use and resistance trends remains heterogeneous across settings. Hospital settings continue to show high rates of broad-spectrum antimicrobial use, especially in intensive care units. The COVID-19 pandemic also influenced antimicrobial use patterns, particularly by increasing the consumption of macrolides despite limited evidence of bacterial coinfection. Continued efforts involving prescriber education, antimicrobial stewardship programs, microbiological diagnostics, and integrated surveillance are essential to support more rational antimicrobial use and help address antimicrobial resistance in Brazil.

Abstract:

Drug-induced toxicity remains a principal driver of attrition in pharmaceutical development, yet conventional screening paradigms typically address individual toxicity endpoints in isolation. Here, we introduce MultiEndpointTox, a chemoinformatics platform that simultaneously predicts seven critical drug toxicity endpoints—hERG cardiotoxicity, hepatotoxicity (DILI), nephrotoxicity (DIKI), Ames mutagenicity, skin sensitization, cytotoxicity, and reproductive toxicity (exploratory)—from molecular structures using curated datasets totaling over 18,000 compounds. The platform employs optimized classical machine learning models with systematic benchmarking of 2D topological descriptors (2240 features), enhanced multi-conformer 3D descriptors (1975 features from 5-conformer ensembles incorporating AUTOCORR3D, RDF, WHIM, and pharmacophore fingerprints), and hybrid representations. Under the tested conditions, 2D descriptors achieved the highest classification performance (AUC-ROC 0.859 ± 0.02), while enhanced 3D descriptors substantially narrowed the previously reported gap (AUC-ROC 0.833 ± 0.03 versus 0.69–0.73 for basic 14-feature 3D). Scaffold-based splitting provided rigorous generalization assessment, with an average performance reduction of approximately 8%. A multi-task learning framework via stacked generalization demonstrated cross-endpoint information sharing improves performance for 5 of 6 endpoints (average +2.1% AUC). The platform integrates leverage-based applicability domain assessment (31–100% coverage), SHAP-based feature importance analysis, and a confidence-weighted multi-endpoint risk scoring system validated on known drugs (AUC = 0.83, p = 4.06 × 10⁻¹⁴, Cliff’s δ = 0.66), with sensitivity analysis confirming robustness across five weight configurations (AUC range 0.72–0.98). External validation on independent benchmark datasets revealed the challenge of cross-dataset domain shift in computational toxicology. MultiEndpointTox is deployed as a production-ready REST API and publicly available at https://github.com/sharhabileltahir/MultiEndpointTox.

Abstract: Precise quantitative determination of Vascular Endothelial Growth Factor (VEGF) in human plasma is critical for pharmacodynamic (PD) evaluation of anti-VEGF therapeutics. In this study, we developed and optimized two immunoassay platforms, including the enzyme-linked immunosorbent assay (ELISA) and the Meso Scale Discovery (MSD), for estimating VEGF. A direct sandwich ELISA was validated to quantify pharmacodynamic biomarker VEGF in human plasma using the Human VEGF Quantikine Kit, demonstrating a quantification range of 62.5–2000.0 pg/mL and a sensitivity of 47.5 pg/mL. In parallel, a sandwich electrochemiluminescence (ECL) assay was developed using the V-PLEX Plus Human VEGF Kit on the MSD platform, achieving a lower quantification range of 7.7–562.0 pg/mL. Comparative analysis revealed that MSD ECL detection with Sulfo Tag labeling outperformed traditional colorimetric ELISA in terms of signal amplification and dynamic range, making it a valuable tool for PD biomarker analysis. Findings underscore the importance of early platform selection to ensure robust, fit-for-purpose biomarker quantification for clinical pharmacology studies and regulatory submissions.

Abstract: Background: Guillain–Barré syndrome (GBS) is an autoimmune peripheral neuropathy that can lead to paralysis and respiratory failure. In addition to infections, several drugs have been identified as potential triggers of GBS. This study investigated drugs potentially associated with GBS and evaluated its onset timing using a spontaneous adverse event reporting database. Methods: The Japan Adverse Drug Event Report (JADER) database was analyzed to assess more than 4000 drugs for possible associations with GBS. Signal detection was performed using reporting odds ratios, Fisher’s exact test, and total report counts. For vaccines and immune checkpoint inhibitors, onset patterns were assessed using Weibull distribution analysis. Results: Signals suggestive of possible associations with GBS were identified for 45 drugs, including vaccines, immune checkpoint inhibitors, tumor necrosis factor-α inhibitors, non-immune checkpoint inhibitor anticancer drugs, antifungal drugs, and interferons. Vaccine-associated GBS frequently occurred within 1–3 weeks after coronavirus disease 2019, influenza, and pneumococcal vaccination and within 1–3 months after bivalent human papillomavirus vaccination, with the risk decreasing thereafter. Conversely, GBS associated with immune checkpoint inhibitors developed 1–3 months after nivolumab, ipilimumab, and pembrolizumab administration, whereas atezolizumab was linked to a peak onset within 1–3 weeks. Unlike vaccine-associated cases, no clear decline in risk over time was observed. Conclusions: Drugs that modulate immune function, including vaccines and immune checkpoint inhibitors, might be associated with GBS development. Vaccine-associated cases exhibit an early-onset pattern, whereas immune checkpoint inhibitor-associated GBS might occur irrespective of treatment duration. These findings support pharmacovigilance and adverse event monitoring.

Abstract:

Poly(lactic acid) (PLA) devices can be functionalized with plant derived bioactives to introduce antioxidant activity while maintaining manufacturability and cytocompatibility. Here, a polyphenol rich mango leaf extract (MLE) was obtained by enhanced solvent extraction and incorporated into PLA using supercritical carbon dioxide assisted impregnation. Two manufacturing sequences were compared: impregnation after three dimensional (3D) printing of discs and impregnation of filaments prior to printing. Extract yield and radical scavenging capacity were quantified, and impregnation efficiency was assessed as a function of pressure and temperature. Biological performance was evaluated using adipose tissue derived endothelial colony forming cells (ECFCs) and adipose tissue derived mesenchymal stromal cells (MSCs), cultured separately and in co culture on functionalized substrates. Impregnation after printing provided higher and more reproducible loading while preserving disc geometry, whereas impregnation before printing promoted swelling and printing associated deformation that compromised structural fidelity. Cell based analyses supported improved adhesion, spatial distribution and proliferative status on discs produced by impregnation after printing under low temperature and high pressure conditions, without evidence of selective loss of either population in co culture by flow cytometry. These results support post print supercritical impregnation as a robust route to generate antioxidant, cell supportive PLA scaffolds from agricultural by products with potential relevance for vascular oriented biomedical applications.

Abstract: The active constituents of essential plant oils (EOAIs), monoterpenoid carvacrol and monoterpene p-cymene, are widely distributed in many aromatic plants and their products. They differ in that carvacrol has a phenolic functional group. The numerous pharmacological effects of these two EOAIs are well known. In different doses/concentrations, they exhibit analgesic, neuroprotective, vasorelaxant, antiinflammatory, antiviral, antibacterial and antiparasitic effects. The acute toxicity of carvacrol and p-cymene in rats and the free-living nematode Caenorhabditis elegans was investigated. Furthermore, the impact of subacute administration of these two ter-penes on general health, CNS integration, i.e. motor coordination and balance of rats, as well as their effects on the movement of adult C. elegans, was also examined. The aim was to compare the effects and describe in more detail the selective toxicity of carvacrol and p-cymene. The calculated LD50 value of carvacrol was 790.15±1.15 mg/kg, while the LD50 value of p-cymene is above 3000 mg/kg. Tested doses of carvacrol and p-cymene administered for 28 days (50, 100, and 200 mg/kg) did not exert any effect on the CNS of rats or cause any clinical disorders. LC50 value of carvacrol for adult C. elegans was 184.13±1.51 micM and for p-cymene 1268±1.65 micM. In subacute testing, carvacrol showed negative effects on C. elegans reproduction, distance traveled, movement speed and rotational index at lower concentrations than p-cymene, indicating higher toxicity. On the other hand, although less toxic to C. elegans, p-cymene exhibited a specific effect on worm motility, with more rolling which should be further investigated, and can be a consequence of cuticle damage or loss of orientation.

Abstract: Gadolinium nanoparticles (GdNPs) have gained increasing attention as multifunctional metal-based nanoplatforms that extend far beyond their traditional use as magnetic reso-nance imaging (MRI) contrast agents. Their specific magnetic properties, tunable physicochemical features, and tunable biocompatibilities with biocompatible coatings give them great potential as drug delivery and theranostic applica-tions. They offer better stability, less systemic toxicity, and more surface modification options compared to molecular gadolinium chelates. Thermal decomposition, hydrothermal synthesis, polyol-based processes, and green methodologies, along with functionalization products that employ polymers, peptides, or targeting ligands, have significantly enhanced colloidal stability as well as biodistribution and selective accumulation at disease sites. Func-tionalized GdNPs exhibit outstanding properties not only as drug carriers for their specific indications but also as agents for multiple imaging modalities with superior therapeutic efficacy through radiosensitization and magneti-cally assisted delivery. Conjugation with ligands consisting of RGD peptides, hyaluronic acid, or folic acid allows receptor-mediated targeting and en-hances the uptake into cellular tissue in tumors. It is also important to men-tion that GdNP-based formulations have been proved to exert synergistic ef-fects when administered in combination with chemotherapeutic agents like doxorubicin, paclitaxel, and cisplatin. Although GdNPs have shown inter-esting preclinical findings, clinical translation of the products is limited due to scale-up limitations, long-term safety challenges, pharmacokinetics, and regulatory problems. This review presents synthetic strategies for the use of GdNPs, their main physicochemical and magnetic properties, ligand engi-neering for targeted delivery, and underlying biological mechanisms of their theranostic performance.

Abstract: Background: Polysaccharide-based dynamic hydrogels are promising for wound management due to their biocompatibility, injectability, and tunable biofunctionality. The integration of therapeutic gasotransmitter donors offers a strategy to modulate the wound microenvironment. Objectives: This study aimed to develop an injectable, self-healing carbohydrate hydrogel capable of sustained hydrogen sulfide (H₂S) release for burn wound therapy, and to evaluate its physicochemical properties, in vivo efficacy, and mechanism of action. Methods: A dynamic hydrogel (ACMOD) was fabricated via Schiff-base crosslinking between oxidized dextran (OD) and carboxymethyl chitosan (CMCS), incorporating the H₂S donor ADT-OH. Rheological and recovery tests characterized its mechanical and self-healing properties. Efficacy and mechanisms were assessed in a rat full-thickness burn model, analyzing wound closure, histology, oxidative stress, macrophage polarization, angiogenesis, and collagen deposition. Results: ACMOD exhibited shear-thinning, rapid self-healing, and strong tissue adherence. Sustained H₂S release from ACMOD significantly accelerated wound closure and improved tissue regeneration compared to controls. Mechanistically, H₂S attenuated oxidative stress, promoted a pro-regenerative M2 macrophage phenotype, enhanced angiogenesis via VEGF upregulation, and fostered organized collagen deposition and extracellular matrix remodeling. Conclusions: This work demonstrates a versatile, carbohydrate-based dynamic hydrogel platform that synergizes polymer network dynamics with bioactive H₂S delivery to effectively promote burn wound healing. The findings underscore the potential of polysaccharide hydrogels with integrated gasotransmitter release for regenerative therapy and biomaterials applications.

Abstract: Glaucoma treatment is undergoing a significant transformation. Traditionally, the therapy path followed a rigid progression from topical eye drops to invasive surgery. However, this 'step-ladder' approach often imposes a heavy physical and psychological burden on the patient. This review explores the emergence of next-generation pharmaceuticals and sustained-release systems as realistic alternatives to surgical intervention. The analysis focuses on three key areas: the development of dual-action molecules that restore physiological drainage, the introduction of biodegradable implants that ensure long-term stability, and the shift toward neuroprotective strategies. These advancements suggest that the potential of medical therapy is expanding, allowing for effective pressure control with fewer complications. While surgery remains essential for advanced cases, this work highlights a future where glaucoma can be addressed as a chronic condition through molecular precision, prioritizing the patient’s quality of life and long-term visual prognosis.

Abstract: Background: Doxorubicin causes dose-dependent cardiotoxicity linked to epigenetic dysregulation, especially DNA methylation. Metformin shows cardioprotective effects through metabolic and epigenetic mechanisms. This study examined the role of metformin in counteracting doxorubicin-induced DNA methylation changes. Methods: H9c2 cardiomyoblasts were treated with doxorubicin, with or without metformin (0.7–2.8 mM). Cell viability and IC₅₀ were determined by MTT assay. Genome-wide DNA methylation was analysed by whole-genome bisulfite sequencing, followed by PCA and differential methylation analysis with FDR correction. Results: Doxorubicin reduced cell viability (IC₅₀ = 0.164 μM). Pre-treatment with metformin increased IC₅₀ to 0.21, 0.289, and 0.51 μM (0.7, 1.4, 2.8 mM). PCA showed distinct separation among groups. Numerous differentially methylated regions (FDR < 0.05) were associated with genes involved in oxidative stress, mitochondria, apoptosis, and chromatin regulation. Conclusions: Metformin induced distinct, dosedependent genome-wide DNA methylation changes in cardiac cells, indicating a direct epigenetic effect. These findings suggest that metformin influences cardiac epigenetic regulation and may contribute to cardioprotection by modulating DNA methylation.

Abstract: Long‑acting injectables (LAIs) are widely used for chronic conditions such as schizophrenia, opioid use disorder and HIV. Their prolonged efficacy improves adherence and reduces dosing frequency. Among these systems, poly(lactide‑co‑glycolide) (PLGA)‑based formulations are commonly used to deliver drugs ranging from small molecules to peptides and proteins. In vitro release (IVR) tests play a critical role in evaluating drug product performance for both immediate release and prolonged release dosage forms. However, there is a lack of standardized compendial IVR methods for the assessment of LAIs. This lack impedes the development of new drug products in this area and also complicates their regulatory approval process. Considering the complexity of drug release mechanisms and the diversity of various formulation design approaches, it is not possible to devise a universal IVR method which would be applicable to all LAI products. The in vitro release test applied for quality control should be simple, robust, reproducible and discriminatory. On the other hand, more complex biorelevant media and methods are often used during development to better reflect the physiological conditions. This article provides a comprehensive review of compendial and non-compendial methods used for in vitro release testing of PLGA-based LAIs (microspheres and in situ forming implants), with the goal of aiding the development and standardization of future methodologies.

Abstract: Background/Objectives: Cancer therapy–induced alopecia (CTIA) profoundly affects patients’ quality of life. This study conducted a disproportionality analysis of CTIA using the FDA Adverse Event Reporting System (FAERS) database to provide an overview of drug-specific signal distributions by systematically evaluating the impact of reporter type on CTIA signal detection. Methods: FAERS data from January 2004 to September 2024 were analyzed to extract alopecia-related Preferred Terms included under the Medical Dictionary for Regulatory Activities High Level Term “Alopecias.” Reporting odds ratios (RORs) were calculated to assess disproportionality. A primary analysis including all reports and a stratified analysis restricted to reports submitted by healthcare professionals (HCPs) were performed. No individual case-level clinical review was conducted. Results: Approximately 90% of alopecia reports were associated with female patients, and approximately 40% of these reports were linked to breast cancer. In the disproportionality analysis including all reporters, the highest ROR [95% confidence interval (CI)] was observed for docetaxel [58.31 (57.46–59.17)]. In the analysis restricted to HCP reports, the highest ROR was observed for vismodegib [23.92 (21.86–26.17)], whereas that for docetaxel markedly decreased to 3.68 (3.48–3.89). For molecular targeted agents, statistically significant signals were maintained even in the HCP-restricted analysis. Conclusions: Reporter characteristics substantially influence the detection of alopecia signals, with patients amplifying signals reflecting psychological harm and HCPs amplifying signals reflecting pharmacological plausibility. These findings should be interpreted as hypothesis-generating and warrant further validation using prospective or clinical datasets.