ReviewClinical pharmacology and therapeutics2020
Will Artificial Intelligence for Drug Discovery Impact Clinical Pharmacology?
Review in Clinical pharmacology and therapeutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 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
46 citing papers in PubMed.
- Priorities and Implementation Barriers in End-to-End Digital Transformation in the Pharmaceutical Industry: Sequential Mixed Methods Analysis.Journal of medical Internet research · 2026Article
- TechBio 3.0 closes the drug discovery loop with multimodal AI and generative chemistry.npj drug discovery · 2026Review
- Integration of artificial intelligence and multi-omics for precision medicine.Functional & integrative genomics · 2026Review
- Accelerating the clinical translation of bioengineered anticancer therapeutics.Journal of the National Cancer Center · 2026Article
- Metronomic Chemotherapy in Ovarian Cancer: Current Scenario and AI-Integrated Future Strategies.Cancer reports (Hoboken, N.J.) · 2026Review
- Forensic "ToxAIcology": is it really over for the forensic human community?Forensic science, medicine, and pathology · 2026Article
- Lead optimization of 3-indoleacetonitrile identifies candidate compounds with improved anti-influenza activity and safety profiles.Frontiers in microbiology · 2026Article
- Generative artificial intelligence in predictive analysis of diabetes and its complications: a narrative review.Annals of translational medicine · 2025Review
- Responsible artificial intelligence in public health: a Delphi study on risk communication, community engagement and infodemic management.BMJ global health · 2025Article
- Article
- Progress, Pitfalls, and Impact of AI-Driven Clinical Trials.Clinical pharmacology and therapeutics · 2025Review
- Review
- AI in Clinical Trials and Drug Development: Challenges and Potential Advancements.Current drug discovery technologies · 2025Review
- Artificial intelligence in drug development: reshaping the therapeutic landscape.Therapeutic advances in drug safety · 2025Review
- Application of Virtual Drug Study to New Drug Research and Development: Challenges and Opportunity.Clinical pharmacokinetics · 2024Review
- A multimodal Transformer Network for protein-small molecule interactions enhances predictions of kinase inhibition and enzyme-substrate relationships.PLoS computational biology · 2024Article
- Ethics for artificial intelligence use in clinical pharmacology.Indian journal of pharmacology · 2024Article
- Photonics-powered augmented reality skin electronics for proactive healthcare: multifaceted opportunities.Mikrochimica acta · 2024Review
- Modulating autophagy to treat diseases: A revisited review on in silico methods.Journal of advanced research · 2024Review
- Developing an Improved Cycle Architecture for AI-Based Generation of New Structures Aimed at Drug Discovery.Molecules (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
As the field of artificial intelligence and machine learning (AI/ML) for drug discovery is rapidly advancing, we address the question "What is the impact of recent AI/ML trends in the area of Clinical Pharmacology?" We address difficulties and AI/ML developments for target identification, their use in generative chemistry for small molecule drug discovery, and the potential role of AI/ML in clinical trial outcome evaluation. We briefly discuss current trends in the use of AI/ML in health care and the impact of AI/ML context of the daily practice of clinical pharmacologists.
Indexed as
Identifiers
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.