Evidence map›Paper›PMID 38778382›Full record

ArticleJournal of cheminformatics2024

AiZynthFinder 4.0: developments based on learnings from 3 years of industrial application.

Lakshidaa Saigiridharan, Alan Kai Hassen, Helen Lai, Paula Torren-Peraire, Ola Engkvist, Samuel Genheden

Abstract read
In one paragraph

Article in Journal of cheminformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Review
  2. AI-Based Retrosynthesis of Known and Unexplored Covalent Organic Framework Monomers.Chemistry of materials : a publication of the American Chemical Society · 2026
    Article
  3. Article
  4. 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 · 2026
    Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Enhancing Monte Carlo Tree Search for Retrosynthesis.Journal of chemical information and modeling · 2025
    Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Investigations into the Efficiency of Computer-Aided Synthesis Planning.Journal of chemical information and modeling · 2025
    Article
  19. Review
  20. DrugGym: A testbed for the economics of autonomous drug discovery.bioRxiv : the preprint server for biology · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Lakshidaa SaigiridharanMolecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg, Sweden. lakshidaa.saigiridharan@astrazeneca.com.
Alan Kai HassenLeiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands.
Helen LaiMolecular AI, Discovery Sciences, R&D, AstraZeneca, Cambridge, UK.
Paula Torren-PeraireInstitute of Structural Biology, Molecular Targets and Therapeutics Center, Helmholtz Zentrum München, Neuherberg, Germany.
Ola EngkvistMolecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg, Sweden.
Samuel GenhedenMolecular AI, Discovery Sciences, R&D, AstraZeneca, Gothenburg, Sweden. samuel.genheden@astrazeneca.com.

Funding

European Commission 956832
6 · The paper itself

Abstract

We present an updated overview of the AiZynthFinder package for retrosynthesis planning. Since the first version was released in 2020, we have added a substantial number of new features based on user feedback. Feature enhancements include policies for filter reactions, support for any one-step retrosynthesis model, a scoring framework and several additional search algorithms. To exemplify the typical use-cases of the software and highlight some learnings, we perform a large-scale analysis on several hundred thousand target molecules from diverse sources. This analysis looks at for instance route shape, stock usage and exploitation of reaction space, and points out strengths and weaknesses of our retrosynthesis approach. The software is released as open-source for educational purposes as well as to provide a reference implementation of the core algorithms for synthesis prediction. We hope that releasing the software as open-source will further facilitate innovation in developing novel methods for synthetic route prediction. AiZynthFinder is a fast, robust and extensible open-source software and can be downloaded from https://github.com/MolecularAI/aizynthfinder .

Indexed as

Computer-aided synthesis planningMulti-step retrosynthesisOpen-sourceRetrosynthesis software

Identifiers

PMID38778382
PMCPMC11112899

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.