| URL: | http://apps.chiragjpgroup.org/repoDB |
| Full name: | repoDB-drug repository database |
| Description: | repoDB contains a standard set of drug repositioning successes and failures that can be used to fairly and reproducibly benchmark computational repositioning methods. repoDB data was extracted from DrugCentral and ClinicalTrials.gov. |
| Year founded: | 2017 |
| Last update: | |
| Version: | 1.2 |
| Accessibility: |
Accessible
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| Country/Region: | United States |
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| University/Institution: | Harvard University |
| Address: | Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck St, Boston, Massachusetts 02115, USA |
| City: | Massachusetts |
| Province/State: | |
| Country/Region: | United States |
| Contact name (PI/Team): | Chirag J. Patel |
| Contact email (PI/Helpdesk): | chirag_Patel@hms.harvard.edu |
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A standard database for drug repositioning. [PMID: 28291243]
Drug repositioning, the process of discovering, validating, and marketing previously approved drugs for new indications, is of growing interest to academia and industry due to reduced time and costs associated with repositioned drugs. Computational methods for repositioning are appealing because they putatively nominate the most promising candidate drugs for a given indication. Comparing the wide array of computational repositioning methods, however, is a challenge due to inconsistencies in method validation in the field. Furthermore, a common simplifying assumption, that all novel predictions are false, is intellectually unsatisfying and hinders reproducibility. We address this assumption by providing a gold standard database, repoDB, that consists of both true positives (approved drugs), and true negatives (failed drugs). We have made the full database and all code used to prepare it publicly available, and have developed a web application that allows users to browse subsets of the data (http://apps.chiragjpgroup.org/repoDB/). |