The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Systematic Drug Repositioning Based on Clinical Side-Effects
Open accessAbstract
Drug repositioning helps fully explore indications for marketed drugs and clinical candidates. Here we show that the clinical side-effects (SEs) provide a human phenotypic profile for the drug, and this profile can suggest additional disease indications. We extracted 3,175 SE-disease relationships by combining the SE-drug relationships from drug labels and the drug-disease relationships from PharmGKB. Many relationships provide explicit repositioning hypotheses, such as drugs causing hypoglycemia are potential candidates for diabetes. We built Naïve Bayes models to predict indications for 145 diseases using the SEs as features. The AUC was above 0.8 in 92% of these models. The method was extended to predict indications for clinical compounds, 36% of the models achieved AUC above 0.7. This suggests that closer attention should be paid to the SEs observed in trials not just to evaluate the harmful effects, but also to rationally explore the repositioning potential based on this "clinical phenotypic assay".
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The WEKA data mining software: an update
Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., & Witten, I. H. (2009) · ACM SIGKDD Explorations Newsletter · doi:10.1145/1656274.1656278 · Cited by 17,750
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
Predicting new molecular targets for known drugs
Keiser, M. J., Setola, V., Irwin, J. J., Laggner, C., Abbas, A. I., Hufeisen, S. J., Jensen, N. H., Kuijer, M. B., Matos, R. C., Tran, T. B., et al. (2009) · Nature · doi:10.1038/nature08506 · Cited by 1,667
Drug target identification using side-effect similarity
Campillos, M., Kuhn, M., Gavin, A.-C., Jensen, L. J., & Bork, P. (2008) · Science · doi:10.1126/science.1158140 · Cited by 1,248
Luo, H., Chen, J., Shi, L., Mikailov, M., Zhu, H., Wang, K., He, L., & Yang, L. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr299 · Cited by 206
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Cited by
Drug repurposing: progress, challenges and recommendations
Pushpakom, S., Iorio, F., Eyers, P. A., Escott, K. J., Hopper, S., Wells, A., Doig, A., Guilliams, T., Latimer, J., McNamee, C., et al. (2019) · Nature Reviews Drug Discovery · doi:10.1038/nrd.2018.168 · Cited by 4,718
Data-driven prediction of drug effects and interactions
Tatonetti, N. P., Ye, P. P., Daneshjou, R., & Altman, R. B. (2012) · Science Translational Medicine · doi:10.1126/scitranslmed.3003377 · Cited by 936
A survey of current trends in computational drug repositioning
Li, J., Zheng, S., Chen, B., Butte, A. J., Swamidass, S. J., & Lu, Z. (2016) · Briefings in Bioinformatics · doi:10.1093/bib/bbv020 · Cited by 555
Drug repurposing from the perspective of pharmaceutical companies
Cha, Y., Erez, T., Reynolds, I. J., Kumar, D., Ross, J., Koytiger, G., Kusko, R., Zeskind, B., Risso, S., Kagan, E., et al. (2018) · British Journal of Pharmacology · doi:10.1111/bph.13798 · Cited by 429
Jarada, T. N., Rokne, J. G., & Alhajj, R. (2020) · Journal of Cheminformatics · doi:10.1186/s13321-020-00450-7 · Cited by 384
Metadata
- Authors
- Yang, L., & Agarwal, P.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2011-12-21
- Volume
- 6
- Issue
- 12
- Pages
- e28025
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W2020132970
- Cited by
- 266
- References
- 6
- FWCI
- 12.86
- Type
- journal article
- Language
- en
- Open access
- gold
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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.
