ReviewTherapeutic advances in drug safety2025
Artificial intelligence in drug development: reshaping the therapeutic landscape.
Review in Therapeutic advances in drug safety, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed.
- Based on artificial intelligence-assisted generation and in-depth in-silico evaluation of potential inhibitors targeting Stearoyl-CoA desaturase 1 (SCD-1).Scientific reports · 2026Article
- Globalization in the Healthcare Industry: Drivers, Risks, and Adaptation.Healthcare (Basel, Switzerland) · 2026Review
- Artificial Intelligence For 6P Medicine: Consolidating AI Needs of Predictive, Preventive, Personalized, Participatory, Precision, and Public Health Trajectories.Journal of medical systems · 2026Review
- DrugPlayGround: Benchmarking Large Language Models and Embeddings for Drug Discovery.bioRxiv : the preprint server for biology · 2026Article
- A Comparative Review of Artificial Intelligence Applications in Small Molecule Versus Peptide Drug Discovery.International journal of molecular sciences · 2026Review
- RGReco: a unified framework for automated R-group recognition in chemical publications.Journal of cheminformatics · 2026Article
- Development and validation of an interpretable machine learning model for postoperative radiotherapy decision-making in ypN0 breast cancer after neoadjuvant chemotherapy: a real-world study.BMC medical informatics and decision making · 2026Article
- Artificial Intelligence in Selected Domains of Drug Discovery: A Critical Narrative Review.Drug design, development and therapy · 2026Review
- How is AI developing in pharmacovigilance?Therapeutic advances in drug safety · 2026Article
- AI-powered mapping of tumor immunity for optimized mRNA vaccine engineering.Frontiers in oncology · 2026Review
- The central role of EMT in tumor progression: mechanistic drivers, biomarker discovery, and therapeutic horizons.Frontiers in pharmacology · 2026Review
- Prompt-based multimodal representation learning for drug repurposing.Briefings in bioinformatics · 2025Article
- AI-driven epitope prediction: a system review, comparative analysis, and practical guide for vaccine development.NPJ vaccines · 2025Review
- Artificial Intelligence in Small-Molecule Drug Discovery: A Critical Review of Methods, Applications, and Real-World Outcomes.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Women's hormonal health research and care: the times, they are a-changin'.Translational cancer research · 2025Article
- Time-Dependent Impact of Betulin and Its Derivatives on IL-8 Expression in Colorectal Cancer Cells with Molecular Docking Studies.International journal of molecular sciences · 2025Article
- AI-driven transformation of precision medicine: a comprehensive narrative review of key application areas, emerging paradigms, and future directions.Frontiers in public health · 2025Review
- Artificial intelligence-, organoid-, and organ-on-chip-powered models to improve pre-clinical animal testing of vaccines and immunotherapeutics: potential, progress, and challenges.Frontiers in artificial intelligence · 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is transforming medication research and development, giving clinicians new treatment options. Over the past 30 years, machine learning, deep learning, and neural networks have revolutionized drug design, target identification, and clinical trial predictions. AI has boosted pharmaceutical R&D (research and development) by identifying new therapeutic targets, improving chemical designs, and predicting complicated protein structures. Furthermore, generative AI is accelerating the development and re-engineering of medicinal molecules to cater to both common and rare diseases. Although, to date, no AI-generated medicinal drug has been FDA-approved, HLX-0201 for fragile X syndrome and new molecules for idiopathic pulmonary fibrosis have entered clinical trials. However, AI models are generally considered "black boxes," making their conclusions challenging to understand and limiting the potential due to a lack of model transparency and algorithmic bias. Despite these obstacles, AI-driven drug discovery has substantially reduced development times and costs, expediting the process and financial risks of bringing new medicines to market. In the future, AI is expected to continue to impact pharmaceutical innovation positively, making life-saving drug discoveries faster, more efficient, and more widespread.
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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.