ReviewFrontiers in pharmacology2025
Advancing precision oncology with AI-powered genomic analysis.
Review in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 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
35 citing papers in PubMed.
- Decoding cancer with artificial intelligence: Transforming research, diagnosis, and therapy with future insights.Translational oncology · 2026Review
- Artificial Intelligence as a Discovery Engine for Routine Molecular Techniques: Extracting Biological Insight from Western Blotting, ELISA, Immunostaining, and Immunoprecipitation.Cell biochemistry and biophysics · 2026Review
- Research progress on biomarkers of blast lung injury: Transition from traditional indicators to novel molecular markers.iScience · 2026Review
- Multi-omics technologies: Novel tools and methods for assessing nerve injury and regeneration.Neural regeneration research · 2026Article
- Mechanisms and advances of drug resistance in colorectal cancer: A systematic overview of multi-layered regulatory networks.Translational oncology · 2026Review
- Comprehensive overview of AI methodologies in nano-drug delivery Optimization and Design.NPJ precision oncology · 2026Review
- Closing the Translational Gap: Closed-Loop AI Discovery Frameworks for Experimental Validation and Clinical Implementation in Cancer Therapeutics.Cancer medicine · 2026Review
- In silico analysis of gene expression signatures and drug repurposing associated with metastatic progression in melanoma (skin cancer).Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Artificial intelligence and transforming cancer care.Discover oncology · 2026Review
- Review
- Next-Generation Artificial Intelligence Strategies for Mechanistic Cancer Target Discovery and Drug Development: A State-of-the-Art Review.International journal of molecular sciences · 2026Review
- Further Promise and Potential for Precision Medicine in Oncology.Journal of medical Internet research · 2026Article
- Experimental models of chemical carcinogenesis: bridging toxicology and preclinical pharmacology.Journal of the Egyptian National Cancer Institute · 2026Review
- Artificial intelligence and machine learning-driven advancements in gastrointestinal cancer: Paving the way for precision medicine.World journal of gastroenterology · 2026Review
- Inflammatory bowel diseases: pathological mechanisms and therapeutic perspectives.Molecular biomedicine · 2026Review
- The Role of Artificial Intelligence in Modern Analytical Chemistry: Current Trends and Future Directions.International journal of analytical chemistry · 2026Review
- Array comparative genomic hybridisation in haematological malignancies: A comprehensive review.African journal of laboratory medicine · 2026Review
- A narrative review of spatial multi-omics and organ-on-a-chip technologies for cardio-cerebral-renal crosstalk.Frontiers in bioengineering and biotechnology · 2026Review
- The role of AI-powered molecular profiling in the diagnosis and management of cancers of unknown primary: a case report and literature review.Frontiers in oncology · 2026Article
- From Germline Susceptibility to Therapeutic Vulnerability: DNA Damage Response Gene Mutations Driving Multiple Myeloma Evolution and Precision Therapy.Human mutation · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multiomics data integration approaches offer a comprehensive functional understanding of biological systems, with significant applications in disease therapeutics. However, the quantitative integration of multiomics data presents a complex challenge, requiring highly specialized computational methods. By providing deep insights into disease-associated molecular mechanisms, multiomics facilitates precision medicine by accounting for individual omics profiles, enabling early disease detection and prevention, aiding biomarker discovery for diagnosis, prognosis, and treatment monitoring, and identifying molecular targets for innovative drug development or the repurposing of existing therapies. AI-driven bioinformatics plays a crucial role in multiomics by computing scores to prioritize available drugs, assisting clinicians in selecting optimal treatments. This review will explain the potential of AI and multiomics data integration for disease understanding and therapeutics. It highlight the challenges in quantitative integration of diverse omics data and clinical workflows involving AI in cancer genomics, addressing the ethical and privacy concerns related to AI-driven applications in oncology. The scope of this text is broad yet focused, providing readers with a comprehensive overview of how AI-powered bioinformatics and integrative multiomics approaches are transforming precision oncology. Understanding bioinformatics in Genomics, it explore the integrative multiomics strategies for drug selection, genome profiling and tumor clonality analysis with clinical application of drug prioritization tools, addressing the technical, ethical, and practical hurdles in deploying AI-driven genomics tools.
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What OpenQuestion 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 OpenQuestion graph.