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Updated: Feb 8, 2026

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
DeCoST: A New Approach in Drug Repurposing From Control System Theory
Thanh M Nguyen1, Syed A Muhammad2, Sara Ibrahim3
1Department of Computer and Information Science, Indiana University-Purdue University Indianapolis, Indianapolis, IN, United States.
We introduce the DeCoST framework, applying control system theory to drug repurposing. This novel approach identifies potential new cancer treatments by modeling drug-gene-disease interactions, offering a systematic and cost-effective discovery method.
Area of Science:
- Pharmacology and Systems Biology
- Control Theory Applications in Medicine
Background:
- Drug repurposing accelerates new treatment discovery for complex diseases.
- Existing methods evolve but often lack systematic, model-based approaches.
- Control system paradigms are underutilized for modeling drug-gene-disease networks.
Purpose of the Study:
- To introduce the DeCoST (Drug Repurposing from Control System Theory) framework.
- To apply control system theory to drug repurposing for identifying novel therapeutic strategies.
- To construct disease-specific mathematical models integrating drug, gene, and disease data.
Main Methods:
- Developed the DeCoST framework, integrating biological and pharmaceutical knowledge.
- Quantified connective data sources among drugs, genes, and diseases.
- Utilized linear-quadratic regulator control techniques to assess therapeutic effects.
- Validated the framework's ability to classify drug approval status.
Main Results:
- Successfully applied DeCoST to Breast Cancer (ER+ and ER-) and Bladder Cancer.
- Identified 8 candidate drugs for ER+ Breast Cancer (e.g., Erbitux, Flutamide).
- Identified 2 candidate drugs for ER- Breast Cancer (e.g., Daunorubicin, Donepezil).
- Identified 10 candidate drugs for Bladder Cancer (e.g., Zafirlukast, Tenofovir).
Conclusions:
- DeCoST provides a novel, systematic, and model-based approach to drug repurposing.
- The framework demonstrates potential for identifying promising candidate drugs for various cancers.
- Control theory offers a powerful paradigm for understanding complex biological systems in drug discovery.
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