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Updated: Mar 16, 2026
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Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
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Drug repositioning in SLE: crowd-sourcing, literature-mining and Big Data analysis
A C Grammer1, M M Ryals2, S E Heuer2
1AMPEL BioSolutions and RILITE Foundation, University of Virginia Research Park, Charlottesville, VA, USA amriegrammer@comcast.net.
Lupus
|August 7, 2016
Summary
Drug repositioning offers new hope for lupus patients by identifying existing medications for repurposing. This approach uses big data and literature mining to find safe, effective treatments for systemic lupus erythematosus (SLE).
Area of Science:
- Rheumatology and pharmacology
- Translational medicine
- Drug discovery and development
Background:
- Systemic lupus erythematosus (SLE) treatment options are limited, with few new drugs approved in recent decades.
- Existing treatments for SLE lack specificity and safety, necessitating novel therapeutic strategies.
- Drug repositioning presents a viable avenue to accelerate the development of new treatments for lupus patients.
Purpose of the Study:
- To explore novel therapeutic strategies for systemic lupus erythematosus (SLE) through drug repositioning.
- To identify and rank potential drug candidates for lupus by integrating multiple data analysis approaches.
- To mitigate risks associated with new drug development by focusing on already-approved medications.
Main Methods:
- Utilizing "Big Data" analysis for unbiased identification of potential lupus therapies.
- Employing literature mining and crowd-sourcing with the Combined Lupus Treatment Scoring (CoLTs) system for hypothesis-based candidate ranking.
- Validating hypothesis-driven predictions through orthogonal "Big Data" analysis of differentially expressed genes in SLE patient samples.
Main Results:
- A multi-pronged drug repositioning strategy confirmed predictions through independent data analyses.
- "Big Data" analysis of gene expression data corroborated findings from hypothesis-based approaches.
- The study highlights the synergy between unbiased and hypothesis-driven methods in identifying therapeutic candidates.
Conclusions:
- Drug repositioning, combining "Big Data" and hypothesis-based methods, is a promising strategy for discovering novel SLE therapies.
- Collaborative efforts, including patient and scientist involvement via platforms like LRxL-STAT, can accelerate testing of potential lupus drugs.
- The Lupus Clinical Investigators Network (LuCIN) facilitates rapid, small-scale trials to assess the efficacy of repositioned drugs in SLE patients.
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