Evidence map›Paper›PMID 36624665›Full record

ArticleNucleic acids research2023

canSAR: update to the cancer translational research and drug discovery knowledgebase.

Patrizio di Micco, Albert A Antolin, Costas Mitsopoulos, Eloy Villasclaras-Fernandez, Domenico Sanfelice, Daniela Dolciami, Pradeep Ramagiri, Ioan L Mica, Joseph E Tym, Philip W Gingrich and 3 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. PDBe tools for an in-depth analysis of small molecules in the Protein Data Bank.Protein science : a publication of the Protein Society · 2025
    Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Cancer pharmacoinformatics: Databases and analytical tools.Functional & integrative genomics · 2024
    Review
  16. Article
  17. 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

13 authors.

Patrizio di MiccoThe Department of Genomic Medicine & The Institute of Data Science in Oncology, MD Anderson Cancer Center, Houston, TX, USA.ORCID 0000-0002-2242-6294
Albert A AntolinCentre for Cancer Drug Discovery, The Division of Cancer Therapeutics, The Institute of Cancer Research, London, UK.ORCID 0000-0002-1634-9034
Costas MitsopoulosCentre for Cancer Drug Discovery, The Division of Cancer Therapeutics, The Institute of Cancer Research, London, UK.
Eloy Villasclaras-FernandezThe Department of Data Science, The Institute of Cancer Research, London, UK.
Domenico SanfeliceThe Department of Data Science, The Institute of Cancer Research, London, UK.
Daniela DolciamiThe Department of Data Science, The Institute of Cancer Research, London, UK.
Pradeep RamagiriCentre for Cancer Drug Discovery, The Division of Cancer Therapeutics, The Institute of Cancer Research, London, UK.
Ioan L MicaThe Department of Genomic Medicine & The Institute of Data Science in Oncology, MD Anderson Cancer Center, Houston, TX, USA.
Joseph E TymThe Department of Data Science, The Institute of Cancer Research, London, UK.
Philip W GingrichThe Department of Genomic Medicine & The Institute of Data Science in Oncology, MD Anderson Cancer Center, Houston, TX, USA.
Huabin HuCentre for Cancer Drug Discovery, The Division of Cancer Therapeutics, The Institute of Cancer Research, London, UK.
Paul WorkmanCentre for Cancer Drug Discovery, The Division of Cancer Therapeutics, The Institute of Cancer Research, London, UK.ORCID 0000-0003-1659-3034
Bissan Al-LazikaniThe Department of Genomic Medicine & The Institute of Data Science in Oncology, MD Anderson Cancer Center, Houston, TX, USA.ORCID 0000-0003-3367-2519

Funding

Cancer Research UK 22897Wellcome Trust
6 · The paper itself

Abstract

canSAR (https://cansar.ai) is the largest public cancer drug discovery and translational research knowledgebase. Now hosted in its new home at MD Anderson Cancer Center, canSAR integrates billions of experimental measurements from across molecular profiling, pharmacology, chemistry, structural and systems biology. Moreover, canSAR applies a unique suite of machine learning algorithms designed to inform drug discovery. Here, we describe the latest updates to the knowledgebase, including a focus on significant novel data. These include canSAR's ligandability assessment of AlphaFold; mapping of fragment-based screening data; and new chemical bioactivity data for novel targets. We also describe enhancements to the data and interface.

Indexed as

Antineoplastic AgentsDrug DiscoveryKnowledge BasesTranslational Research, BiomedicalAlgorithmsHumansNeoplasmsAntineoplastic Agents

Identifiers

PMID36624665
PMCPMC9825411

What OpenQuestion holds

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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.