Mathematical Method Provides Deeper Understanding of Drug Interactions

Technology Networks | November 13, 2019

Researchers at the CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences have developed a new methodology characterizing more precisely how drugs influence each other when combined during treatment. Their analysis of over 30k drug pairs applied to cell lines identified 1,832 interactions between 242 different drugs and sheds new light on how drugs perturb the underlying molecular networks. Combining two or more drugs can be an effective treatment of diverse diseases, such as cancer. Yet, at the same time, the wrong drug combination can cause major side effects. Currently there is no systematic understanding of how different drugs influence each other. Thus, elucidating how two given drugs interact, and whether they have a beneficial effect, would mean a major step towards drug development to treat diseases more effectively in the future. On a molecular level, drugs cause complex perturbations of various cellular processes in our body. These processes are orchestrated by an intricate network of molecular interactions, the so-called interactome. Over the last decade, numerous studies have revealed a close relationship between the structure of the interactome and the functional organization of the molecular machinery within the cell. This opened exciting opportunities for using network-based approaches to investigate the foundations of both healthy and disease states. Following this trend, Principal Investigator Jörg Menche and his group at CeMM developed a novel mathematical framework for mapping out precisely how different perturbations of the interactome influence each other.

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Spotlight

From a patient perspective, hub services can often be a lifeline to managing complicated, chronic conditions. Creating a solution that supports patients who rely on “middle-ground” specialty medications is a necessity for an area that is becoming a larger part of the overall pharmaceutical landscape. The Hub-Lite™ model ores an e client approach to drugs whose cost or pattern of treatment don’t justify the expense of full-edged patient services.

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