Mount Sinai Researchers Develop Novel Computational Approach for Identifying Synergistic Drug Combinations
New method accurately predicts effective drug pairings, laying the foundation for faster development of novel therapeutics
Researchers at the Icahn School of Medicine at Mount Sinai have developed a powerful computational tool, named iDOMO, to improve the prediction of drug synergy and accelerate the development of combination therapies for complex diseases. The study, published in Briefings in Bioinformatics on February 20 [10.1093/bib/bbaf054], highlights iDOMO’s ability to identify synergistic drug combinations using gene expression data, outperforming existing methods.
Advancing Drug Discovery Through Computational Approaches
Combination therapies, which use multiple drugs to target different pathways involved in disease, are increasingly critical for treating complex conditions such as cancer. However, the process of experimentally identifying effective drug pairs is costly and time-consuming. iDOMO provides a computational solution by analyzing gene expression data—which measures the activity levels of genes in a given biological sample—and gene signatures, which are distinct patterns of gene activity associated with a specific condition, such as a disease state or drug response. By comparing gene signatures of drugs and diseases, iDOMO predicts the beneficial and detrimental effects of drug combinations.
"Our approach offers a more effective way to predict drug combinations that could serve as novel therapeutic options for treating human diseases," said senior author Bin Zhang, PhD, Willard T.C. Johnson Research Professor of Neurogenetics and Director of the Mount Sinai Center for Transformative Disease Modeling. "This could significantly expand treatment options for clinicians and improve outcomes for patients who do not respond to standard therapies."
Validation in Triple-Negative Breast Cancer
The study applied iDOMO to triple-negative breast cancer, a particularly aggressive and difficult-to-treat form of cancer. The model identified a promising drug combination—trifluridine and monobenzone—which was subsequently tested in in vitro experiments. The findings confirmed that this combination inhibited triple-negative breast cancer cell growth more effectively than either drug alone, validating iDOMO’s prediction.
"By leveraging computational approaches like iDOMO, we can prioritize the most promising drug combinations for further experimental validation, potentially accelerating the discovery of new treatments for a wide range of diseases," Dr. Zhang added.
Implications for Medicine and Research and Future Directions
iDOMO offers clinicians more therapeutic options, potentially leading to new and more effective treatments for patients resistant to conventional therapies. The approach provides a cost-efficient, scalable solution for identifying synergistic drug pairs, paving the way for broader applications across a variety of diseases.
Future work will focus on expanding iDOMO’s application to other diseases beyond triple-negative breast cancer, further refining its predictive capabilities, and integrating it into broader drug development pipelines.
This work was supported in part by grants from the National Institutes of Health (NIH)/National Institute on Aging (RF1AG074010, R01AG046170, RF1AG057440, R01AG057907, U01AG052411, R01AG062355, U01AG058635, RF1AG054014, RO1AG068030 and R56AG058655), and NIH/National Institute of Diabetes and Digestive and Kidney Diseases (R01DK118243).
The paper is titled “iDOMO: identification of drug combinations via multi-set operations for treating diseases.”
About the Icahn School of Medicine at Mount Sinai
The Icahn School of Medicine at Mount Sinai is internationally renowned for its outstanding research, educational, and clinical care programs. It is the sole academic partner for the eight- member hospitals* of the Mount Sinai Health System, one of the largest academic health systems in the United States, providing care to New York City’s large and diverse patient population.
The Icahn School of Medicine at Mount Sinai offers highly competitive MD, PhD, MD-PhD, and master’s degree programs, with enrollment of more than 1,200 students. It has the largest graduate medical education program in the country, with more than 2,600 clinical residents and fellows training throughout the Health System. Its Graduate School of Biomedical Sciences offers 13 degree-granting programs, conducts innovative basic and translational research, and trains more than 500 postdoctoral research fellows.
Ranked 11th nationwide in National Institutes of Health (NIH) funding, the Icahn School of Medicine at Mount Sinai is among the 99th percentile in research dollars per investigator according to the Association of American Medical Colleges. More than 4,500 scientists, educators, and clinicians work within and across dozens of academic departments and multidisciplinary institutes with an emphasis on translational research and therapeutics. Through Mount Sinai Innovation Partners (MSIP), the Health System facilitates the real-world application and commercialization of medical breakthroughs made at Mount Sinai.
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About the Mount Sinai Health System
Mount Sinai Health System is one of the largest academic medical systems in the New York metro area, with 48,000 employees working across eight hospitals, more than 400 outpatient practices, more than 600 research and clinical labs, a school of nursing, and a leading school of medicine and graduate education. Mount Sinai advances health for all people, everywhere, by taking on the most complex health care challenges of our time—discovering and applying new scientific learning and knowledge; developing safer, more effective treatments; educating the next generation of medical leaders and innovators; and supporting local communities by delivering high-quality care to all who need it.
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