ReviewNature2019
The digitization of organic synthesis.
Review in Nature, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 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
32 citing papers in PubMed.
- Yield Prediction of Organic Reactions in Biased Data Sets via Positive-Unlabeled Learning.Journal of the American Chemical Society · 2026Article
- A Versatile Flow Reactor Platform for Machine Learning Guided RAFT Synthesis, Amidation of Poly(Pentafluorophenyl Acrylate).Macromolecular rapid communications · 2025Article
- Predicting reaction conditions: a data-driven perspective.Chemical science · 2025Review
- Article
- Article
- From Cortisone to Enlicitide: A Journey of Synthetic Chemistry Innovations at Merck.The Journal of organic chemistry · 2025Review
- Data-Driven Search Algorithm for Discovery of Synthesizable Zeolitic Imidazolate Frameworks.JACS Au · 2025Article
- Data accessibility in the chemical sciences: an analysis of recent practice in organic chemistry journals.Beilstein journal of organic chemistry · 2025Article
- An Automated Electrochemical Flow Platform to Accelerate Library Synthesis and Reaction Optimization.Angewandte Chemie (International ed. in English) · 2024Article
- Reaction blueprints and logical control flow for parallelized chiral synthesis in the Chemputer.Nature communications · 2024Article
- Roboticized AI-assisted microfluidic photocatalytic synthesis and screening up to 10,000 reactions per day.Nature communications · 2024Article
- Cheminformatic Identification of Tyrosyl-DNA Phosphodiesterase 1 (Tdp1) Inhibitors: A Comparative Study of SMILES-Based Supervised Machine Learning Models.Journal of personalized medicine · 2024Article
- Site-specific template generative approach for retrosynthetic planning.Nature communications · 2024Article
- Prediction of chemical reaction yields with large-scale multi-view pre-training.Journal of cheminformatics · 2024Article
- An integrated self-optimizing programmable chemical synthesis and reaction engine.Nature communications · 2024Article
- An intriguing vision for transatlantic collaborative health data use and artificial intelligence development.NPJ digital medicine · 2024Review
- Catalysing (organo-)catalysis: Trends in the application of machine learning to enantioselective organocatalysis.Beilstein journal of organic chemistry · 2024Review
- Quantum chemical calculations for reaction prediction in the development of synthetic methodologies.Chemical science · 2023Review
- Review
- A deep learning framework for accurate reaction prediction and its application on high-throughput experimentation data.Journal of cheminformatics · 2023Article
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
Organic chemistry has largely been conducted in an ad hoc manner by academic laboratories that are funded by grants directed towards the investigation of specific goals or hypotheses. Although modern synthetic methods can provide access to molecules of considerable complexity, predicting the outcome of a single chemical reaction remains a major challenge. Improvements in the prediction of 'above-the-arrow' reaction conditions are needed to enable intelligent decision making to select an optimal synthetic sequence that is guided by metrics including efficiency, quality and yield. Methods for the communication and the sharing of data will need to evolve from traditional tools to machine-readable formats and open collaborative frameworks. This will accelerate innovation and require the creation of a chemistry commons with standardized data handling, curation and metrics.
Indexed as
Identifiers
31190012What 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.