Drug toxicity prediction plays a crucial role in the drug research and development process, ensuring clinical drug safety. However, traditional methods are hampered by high cost, low throughput, and uncertainty of cross-species extrapolation, which has become a key bottleneck restricting the efficiency of new drug research and development. The breakthrough development of Artificial Intelligence (AI) technology, especially the application of deep learning and multimodal data fusion strategy, is reshaping the scientific paradigm of drug toxicology assessment. In this review, we focus on the application of AI in the field of drug toxicity prediction and systematically summarize the relevant literature and development status globally in the past years. The application of various toxicity databases in the prediction was elaborated in detail, and the research results and methods for the prediction of different toxicity endpoints were analyzed in depth, including acute toxicity, carcinogenicity, organ-specific toxicity, etc. Furthermore, this paper discusses the application progress of AI technologies (e.g., machine learning and deep learning model) in drug toxicity prediction, analyzes their advantages and challenges, and outlines the future development direction. It aims to provide a comprehensive and in-depth theoretical framework and actionable technical strategies for toxicity prediction in drug development.

Oxidative stress is a critical factor contributing to the pathogenesis of numerous diseases, including cardiovascular disorders, diabetes, and neurodegenerative conditions. In recent years, marine-derived antioxidants have emerged as promising therapeutic agents due to their unique biological activities and diverse sources. This comprehensive review explores the therapeutic potential of various marine antioxidants in mitigating oxidative stress-associated diseases. Marine organisms are rich in bioactive compounds, such as polysaccharides, polyphenols, carotenoids, peptides, and vitamins, which exhibit potent antioxidant and free radical scavenging abilities. These compounds have been shown to effectively inhibit oxidative reactions, repair oxidative damage, and enhance the body’s antioxidant defense mechanisms. For instance, marine polysaccharides and their derivatives can scavenge reactive oxygen species (ROS), protect neurons from oxidative damage, and alleviate inflammation in neurodegenerative diseases like Alzheimer’s and Parkinson’s diseases. Similarly, marine unsaturated fatty acids, such as omega-3 polyunsaturated fatty acids (PUFAs), have been found to reduce cardiovascular risks by lowering serum triglyceride levels and improving vascular endothelial function. Additionally, marine-derived superoxide dismutase (SOD) plays a crucial role in neutralizing ROS, thereby offering protection against oxidative stress in various diseases. Despite these promising findings, challenges remain in the field, including the need for improved extraction and purification technologies, more comprehensive activity evaluation systems, and further research into the safety and bioavailability of these compounds. This review provides a detailed overview of the current research status, highlighting the types, structural characteristics, antioxidant activities, and mechanisms of action of marine antioxidants. It also identifies key areas for future research and development, aiming to harness the full potential of marine-derived antioxidants in the prevention and treatment of oxidative stress-related diseases.

There have been intensive efforts to identify in vivo biomarkers that can be used to monitor drug-induced kidney damage before significant impairment occurs. Kidney injury molecule-1, neutrophil gelatinase-associated lipocalin, clusterin, β2-microglobulin and cystatin C (CysC) have been validated as clinical or preclinical biomarkers in urinary and plasma predictive of acute and chronic kidney injuries and diseases. A high-throughput in vitro assay predictive of nephrotoxicity could potentially be implemented in early drug discovery stage to reduce attrition at later stages of drug development. To assess the potential of these known in vivo biomarkers for in vitro evaluation of drug-induced nephrotoxicity, we selected four nephrotoxic agents (cisplatin, cyclosporin, aristolochic acid I and gentamicin) and detected their effects on the protein levels of nephrotoxic biomarkers in RPTEC/TERT1 cells. The protein levels of clusterin, CysC, GSTπ and TIMP-1 significantly increased in the conditioned media of RPTEC/TERT1 cells treated with cisplatin, cyclosporin, aristolochic acid I and gentamicin. The messenger RNA levels of clusterin, CysC, GSTπ and TIMP-1 also increased in RPTEC/TERT1 cells treated with cisplatin, cyclosporin, aristolochic acid I and gentamicin, indicating that drug-induced upregulation involves transcriptional activation. Taken together, the results clearly demonstrate that among the known in vivo nephrotoxic biomarkers, clusterin, CysC, GSTπ and TIMP-1 can be effectively used as in vitro biomarkers for drug-induced nephrotoxicity in RPTEC/TERT1 cells.

This study integrates network toxicology with molecular docking technology to systematically elucidate the key molecular mechanisms and signaling pathways by which bisphenol A (BPA) induces obesity. By cross-referencing multiple databases—including the Comparative Toxicogenomics Database (CTD), SwissTarget prediction platform, and PharmMapper—potential BPA target genes were identified, yielding a total of 1326 candidate targets. Obesity-related genes were collected from GeneCards and OMIM databases, yielding 4570 disease-associated targets. Among these, 653 overlapping genes were identified as potential mediators linking BPA exposure to obesity. Protein interaction networks were constructed using STRING and Cytoscape, and the MCC algorithm identified five core hub genes: STAT3, MYC, TP53, IL6, and mTOR. Validation using random datasets demonstrated significant upregulation of these genes in the obesity group (p < 0.05), highlighting their potential central role in BPA-induced obesity effects. Functional enrichment analysis via GO and KEGG pathways indicated that BPA may promote obesity by interfering with endocrine signaling, activating lipid metabolism, and stimulating atherosclerosis pathways. Molecular docking analysis using CB-Dock2 confirmed strong binding affinity between BPA and core targets, providing structural evidence for their potential interactions. This study elucidates the potential biological mechanism by which BPA exacerbates obesity through endocrine disruption and metabolic reprogramming, employing a multidimensional approach encompassing cross-target analysis, pathway enrichment, and molecular interactions. It provides an innovative systems toxicology framework and empirical basis for assessing metabolic health risks induced by environmental pollutants.