Evidence map›Paper›PMID 38755219›Full record

ArticleScientific data2024

Exploring SureChEMBL from a drug discovery perspective.

Yojana Gadiya, Simran Shetty, Martin Hofmann-Apitius, Philip Gribbon, Andrea Zaliani

Abstract read
In one paragraph

Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. 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

5 authors.

Yojana GadiyaFraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525, Hamburg, Germany. Yojana.Gadiya@itmp.fraunhofer.de.ORCID 0000-0002-7683-0452
Simran ShettyFraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525, Hamburg, Germany.
Martin Hofmann-ApitiusBonn-Aachen International Center for Information Technology (B-IT), University of Bonn, 53113, Bonn, Germany.ORCID 0000-0001-9012-6720
Philip GribbonFraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525, Hamburg, Germany.
Andrea ZalianiFraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525, Hamburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the pharmaceutical industry, the patent protection of drugs and medicines is accorded importance because of the high costs involved in the development of novel drugs. Over the years, researchers have analyzed patent documents to identify freedom-to-operate spaces for novel drug candidates. To assist this, several well-established public patent document data repositories have enabled automated methodologies for extracting information on therapeutic agents. In this study, we delve into one such publicly available patent database, SureChEMBL, which catalogues patent documents related to life sciences. Our exploration begins by identifying patent compounds across public chemical data resources, followed by pinpointing sections in patent documents where the chemical annotations were found. Next, we exhibit the potential of compounds to serve as drug candidates by evaluating their conformity to drug-likeness criteria. Lastly, we examine the drug development stage reported for these compounds to understand their clinical success. In summary, our investigation aims at providing a comprehensive overview of the patent compounds catalogued in SureChEMBL, assessing their relevance to pharmaceutical drug discovery.

Indexed as

Databases, FactualDrug DiscoveryPatents as TopicDrug Industry

Identifiers

PMID38755219
PMCPMC11099139

What OpenQuestion holds

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LicenceCC BY
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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.