ReviewNature reviews. Drug discovery2018
Automating drug discovery.
Review in Nature reviews. Drug discovery, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 268 papers, 1 of them a synthesis that pooled it.
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
268 citing papers in PubMed, 1 synthesis or guideline pooled it.
- AI in pharmacy education: a comparative visualization analysis of global and Chinese research trends.Frontiers in medicine · 2026Pooled it
- Article
- TechBio 3.0 closes the drug discovery loop with multimodal AI and generative chemistry.npj drug discovery · 2026Review
- Priorities and Implementation Barriers in End-to-End Digital Transformation in the Pharmaceutical Industry: Sequential Mixed Methods Analysis.Journal of medical Internet research · 2026Article
- Active learning in pharmaceutical 3D printing: a multi-dataset comparison.Drug delivery and translational research · 2026Article
- Target discovery and drug design in the era of artificial intelligence.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2026Review
- Syndirella: synthesis-directed fragment elaboration enables extensive and cost-effective binding site exploration beyond catalog compounds.Chemical science · 2026Article
- Artificial intelligence-assisted lead optimization in drug discovery: bridging computational advances and translational challenges.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2026Review
- The Chemical Imitation Game: Navigating Spaces of Meaning in Language and Chemistry.Journal of chemical information and modeling · 2026Article
- Integrating Artificial Intelligence with Emerging Pharmaceutical Technologies: Current Progress, Clinical Translation, and Future Challenges.International journal of molecular sciences · 2026Review
- From Executor to Orchestrator: The Pharmacology Scientist in the Age of Agentic AI.Clinical pharmacology and therapeutics · 2026Review
- Rethinking Chiral Decision-Making in Pharmaceutical Analysis: The Emerging Role of Artificial Intelligence.Chirality · 2026Review
- Integration of Artificial Intelligence and Microfluidics for Drug Delivery Applications.Micromachines · 2026Review
- A unified framework and benchmark for generalizable biomedical knowledge extraction and applications with large language models.Cell reports. Medicine · 2026Article
- Hybrid artificial intelligence and quantum annealing as an optimization layer in drug discovery.Patterns (New York, N.Y.) · 2026Review
- Multimodal deep learning with a joint uncertainty quantification scheme for drug-target interaction prediction.Molecular diversity · 2026Article
- Mentorship Strategies for New Principal Investigators in Computational Chemistry.Journal of chemical information and modeling · 2026Article
- Why do AI projects fail in drug development and pharma? Insights from multi-year Pistoia Alliance studies.Journal of computer-aided molecular design · 2026Article
- From Marine Peptides to Oncology: The Therapeutic Potential of Conotoxins in Cancer Treatment.Chemistry & biodiversity · 2026Review
- Machine Learning for RNA-Targeting Drug Design.Journal of chemical information and modeling · 2026Review
208 more citing papers are in PubMed but not listed here.
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
Small-molecule drug discovery can be viewed as a challenging multidimensional problem in which various characteristics of compounds - including efficacy, pharmacokinetics and safety - need to be optimized in parallel to provide drug candidates. Recent advances in areas such as microfluidics-assisted chemical synthesis and biological testing, as well as artificial intelligence systems that improve a design hypothesis through feedback analysis, are now providing a basis for the introduction of greater automation into aspects of this process. This could potentially accelerate time frames for compound discovery and optimization and enable more effective searches of chemical space. However, such approaches also raise considerable conceptual, technical and organizational challenges, as well as scepticism about the current hype around them. This article aims to identify the approaches and technologies that could be implemented robustly by medicinal chemists in the near future and to critically analyse the opportunities and challenges for their more widespread application.
Indexed as
Identifiers
29242609What 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.