ReviewToxics2024
Recent Advances in Omics, Computational Models, and Advanced Screening Methods for Drug Safety and Efficacy.
Review in Toxics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Chemical Epigenetics: Small Molecules Targeting Chromatin Modifiers in Disease Modulation.Cell biochemistry and biophysics · 2026Review
- Integrating chemical structure and high-throughput transcriptomics for mechanistically interpretable Tox21 bioactivity prediction.Journal of cheminformatics · 2026Article
- How new approach methods are reshaping virology research.Journal of virology · 2026Review
- Computational Identification of Potential Novel Allosteric IHF Inhibitors Using QSAR Modeling to Inhibit Plasmid-Mediated Antibiotic Resistance.International journal of molecular sciences · 2026Article
- Advancements and Challenges in Tissue-Engineered Heart Valves: Integrating Biomechanics, Biomaterials, and Biomimetic Design for Functional Maturity.Biomimetics (Basel, Switzerland) · 2026Review
- Decoding the cellular landscape of biological stress in the human brain.Neurobiology of stress · 2026Article
- Research progress in animal models of dry eye disease: Types, mechanisms, and application prospects.Animal models and experimental medicine · 2026Review
- Marine nutraceuticals as a source of SIRT1 and NRF2 activators for diabetes and aging-related metabolic disorders.Diabetology & metabolic syndrome · 2025Review
- Endocrine-Disrupting Chemicals and Male Infertility: Mechanisms, Risks, and Regulatory Challenges.Journal of xenobiotics · 2025Review
- Overcoming translational barriers in RNA-protein docking: enhancing computational accuracy for targeted drug discovery.Future medicinal chemistry · 2025Review
- Artificial Intelligence-Driven Drug Toxicity Prediction: Advances, Challenges, and Future Directions.Toxics · 2025Review
- Quinoline Quest: Kynurenic Acid Strategies for Next-Generation Therapeutics via Rational Drug Design.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Machine Learning-Enabled Drug-Induced Toxicity Prediction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Food contaminants: mechanisms of toxicity, computational assessment, and mitigation.Frontiers in toxicology · 2025Review
- A comprehensive review on computational metabolomics: Advancing multiscale analysis throughComputational and structural biotechnology journal · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
It is imperative to comprehend the mechanisms that underlie drug toxicity in order to enhance the efficacy and safety of novel therapeutic agents. The capacity to identify molecular pathways that contribute to drug-induced toxicity has been significantly enhanced by recent developments in omics technologies, such as transcriptomics, proteomics, and metabolomics. This has enabled the early identification of potential adverse effects. These insights are further enhanced by computational tools, including quantitative structure-activity relationship (QSAR) analyses and machine learning models, which accurately predict toxicity endpoints. Additionally, technologies such as physiologically based pharmacokinetic (PBPK) modeling and micro-physiological systems (MPS) provide more precise preclinical-to-clinical translation, thereby improving drug safety assessments. This review emphasizes the synergy between sophisticated screening technologies, in silico modeling, and omics data, emphasizing their roles in reducing late-stage drug development failures. Challenges persist in the integration of a variety of data types and the interpretation of intricate biological interactions, despite the progress that has been made. The development of standardized methodologies that further enhance predictive toxicology is contingent upon the ongoing collaboration between researchers, clinicians, and regulatory bodies. This collaboration ensures the development of therapeutic pharmaceuticals that are more effective and safer.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.