The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Phenotypic screens as a renewed approach for drug discovery
Open accessAbstract
The significant reduction in the number of newly approved drugs in past decade has been partially attributed to failures in discovery and validation of new targets. Evaluation of recently approved new drugs has revealed that the number of approved drugs discovered through phenotypic screens, an original drug screening paradigm, has exceeded those discovered through the molecular target-based approach. Phenotypic screening is thus gaining new momentum in drug discovery with the hope that this approach may revitalize drug discovery and improve the success rate of drug approval through the discovery of viable lead compounds and identification of novel drug targets.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
How many drug targets are there?
Overington, J. P., Al-Lazikani, B., & Hopkins, A. L. (2006) · Nature Reviews Drug Discovery · doi:10.1038/nrd2199 · Cited by 3,505
Hopkins, A. L., & Groom, C. R. (2002) · Nature Reviews Drug Discovery · doi:10.1038/nrd892 · Cited by 3,305
Drug repositioning: identifying and developing new uses for existing drugs
Ashburn, T. T., & Thor, K. B. (2004) · Nature Reviews Drug Discovery · doi:10.1038/nrd1468 · Cited by 3,237
How were new medicines discovered?
Swinney, D. C., & Anthony, J. (2011) · Nature Reviews Drug Discovery · doi:10.1038/nrd3480 · Cited by 1,812
Trends in the exploitation of novel drug targets
Rask-Andersen, M., Almén, M. S., & Schiöth, H. B. (2011) · Nature Reviews Drug Discovery · doi:10.1038/nrd3478 · Cited by 853
Arrowsmith, J. (2011) · Nature Reviews Drug Discovery · doi:10.1038/nrd3439 · Cited by 622
Primary cells and stem cells in drug discovery: emerging tools for high-throughput screening
Eglen, R., & Reisine, T. (2011) · ASSAY and Drug Development Technologies · doi:10.1089/adt.2010.0305 · Cited by 100
Cited by
Organs-on-chips at the frontiers of drug discovery
Esch, E. W., Bahinski, A., & Huh, D. (2015) · Nature Reviews Drug Discovery · doi:10.1038/nrd4539 · Cited by 1,185
Drug repurposing: a promising tool to accelerate the drug discovery process
Parvathaneni, V., Kulkarni, N. S., Muth, A., & Gupta, V. (2019) · Drug Discovery Today · doi:10.1016/j.drudis.2019.06.014 · Cited by 597
The discovery of first-in-class drugs: origins and evolution
Eder, J., Sedrani, R., & Wiesmann, C. (2014) · Nature Reviews Drug Discovery · doi:10.1038/nrd4336 · Cited by 514
Utilizing graph machine learning within drug discovery and development
Gaudelet, T., Day, B., Jamasb, A. R., Soman, J., Regep, C., Liu, G., Hayter, J. B. R., Vickers, R., Roberts, C., Tang, J., et al. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab159 · Cited by 313
Natural Products as a Source for Novel Antibiotics
Moloney, M. G. (2016) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2016.05.001 · Cited by 308
Metadata
- Authors
- Zheng, W., Thorne, N., & McKew, J. C.
- Venue
- Drug Discovery Today
- Publisher
- Elsevier BV
- Published
- 2013-11
- Volume
- 18
- Issue
- 21-22
- Pages
- 1067-1073
- ISSN
- 1359-6446 (ISSN-L)
- OpenAlex
- W1981066521
- Cited by
- 423
- References
- 7
- FWCI
- 32.22
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Phenotypic screens as a renewed approach for drug discovery. https://app.cochat.ai/papers/10.1016/j.drudis.2013.07.001
- The paper
- Zheng, W., Thorne, N., & McKew, J. C. (2013). Phenotypic screens as a renewed approach for drug discovery. Drug Discovery Today. https://doi.org/10.1016/j.drudis.2013.07.001
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
