ArticleNature chemistry2024
Probing the chemical 'reactome' with high-throughput experimentation data.
Article in Nature chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
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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
27 citing papers in PubMed.
- High-throughput reaction screening using acoustic ejection mass spectrometry.Nature protocols · 2026Review
- Robust out-of-distribution prediction of Buchwald-Hartwig reactions.Nature computational science · 2026Article
- LipiDecipher: A Structure-Oriented Analytical Framework for Interpretable Clinical Lipidomics.Metabolites · 2026Article
- Generalized Analysis of Electrophilic Small Molecules.Angewandte Chemie (International ed. in English) · 2026Article
- Mapping Regioisomer-Dependent Buchwald-Hartwig C-N Coupling: Bromoimidazo[1,5-a]pyridines as a Model Electrophile Series.Molecules (Basel, Switzerland) · 2026Article
- Which Reaction Conditions Work on Drug-Like Molecules? Lessons from 66,000 High-Throughput Experiments.ACS central science · 2026Article
- The Impact of Continuous Flow Technology and Collaboration between Academia and Industry.JACS Au · 2026Review
- Drug repurposing to combat multidrug-resistant hookworm.Biology open · 2026Article
- Accelerating compound synthesis in drug discovery: the role of digitalisation and automation.RSC medicinal chemistry · 2025Article
- NOCTIS: open-source toolkit that turns reaction data into actionable graph networks.Journal of cheminformatics · 2025Article
- Expediting hit-to-lead progression in drug discovery through reaction prediction and multi-dimensional optimization.Nature communications · 2025Article
- Using Yield Profiles to Study Reaction Mechanism.ACS catalysis · 2025Article
- Reaction-conditioned generative model for catalyst design and optimization with CatDRX.Communications chemistry · 2025Article
- Advancing Organic Chemistry Using High-Throughput Experimentation.Angewandte Chemie (International ed. in English) · 2025Review
- Predictive design of crystallographic chiral separation.Nature communications · 2025Article
- Highly parallel optimisation of chemical reactions through automation and machine intelligence.Nature communications · 2025Article
- Negative chemical data boosts language models in reaction outcome prediction.Science advances · 2025Article
- Applying Active Learning toward Building a Generalizable Model for Ni-Photoredox Cross-Electrophile Coupling of Aryl and Alkyl Bromides.Journal of the American Chemical Society · 2025Article
- Predicting three-component reaction outcomes from ~40,000 miniaturized reactant combinations.Science advances · 2025Article
- Towards global reaction feasibility and robustness prediction with high throughput data and bayesian deep learning.Nature communications · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-throughput experimentation (HTE) has the potential to improve our understanding of organic chemistry by systematically interrogating reactivity across diverse chemical spaces. Notable bottlenecks include few publicly available large-scale datasets and the need for facile interpretation of these data's hidden chemical insights. Here we report the development of a high-throughput experimentation analyser, a robust and statistically rigorous framework, which is applicable to any HTE dataset regardless of size, scope or target reaction outcome, which yields interpretable correlations between starting material(s), reagents and outcomes. We improve the HTE data landscape with the disclosure of 39,000+ previously proprietary HTE reactions that cover a breadth of chemistry, including cross-coupling reactions and chiral salt resolutions. The high-throughput experimentation analyser was validated on cross-coupling and hydrogenation datasets, showcasing the elucidation of statistically significant hidden relationships between reaction components and outcomes, as well as highlighting areas of dataset bias and the specific reaction spaces that necessitate further investigation.
Identifiers
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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.