Research Team Builds AI Cancer Drug Discovery Engine
September 20, 2022
Discovering Personalized Cancer Cures
An interdisciplinary LSU research team with members in the School of Veterinary Medicine, College of Science, College of Engineering, and the Center for Computation & Technology are using artificial intelligence, or AI, to discover personalized cures for cancer more quickly and affordably.
Developing algorithms originally designed to map complex social networks, such as those used by Facebook, the researchers have created a cancer drug discovery engine called CancerOmicsNet. It combines three-dimensional graph representations of vast molecular datasets, including cancer cell lines, drug compounds, as well as protein-protein interactions. Once analyzed and interconnected by AI, they form a much clearer picture of how a specific cancer would respond to a specific drug, removing much of the guesswork in current oncology.
The researchers have completed an initial wet lab study of breast, prostate, and pancreatic cancer cells, which are among the most aggressive and difficult to treat. They tested six cell-drug combinations suggested by AI, and four of them worked. Cancer growth was slowed, even reversed.
“In the future, doctors could potentially take a cancer sample from a patient and run simple, low-cost genomic testing—no more than a few hundred dollars—and use our AI technology to select the most effective drug,” said Michal Brylinski, associate professor of computational biology, who also is a member of the LSU DeepDrug team.
Next, the researchers are going to expand the scope of their study and use CancerOmicsNet to discover effective combinations of cancer drugs at scale. Synergistic combinations would allow lower doses with less side effects.
LSU researchers have built an AI-driven cancer drug discovery engine called CancerOmicsNet by modifying algorithms originally designed to map social networks, such as those used by Facebook. CancerOmicsNet can predict how a specific cancer would respond to a specific drug, removing much of the guesswork in current oncology. The image above was generated by AI based on keywords: molecular speed dating, cell lines, pharmacy.
– LSU
“In the state of Louisiana, we have some of the poorest outcomes of cancer in the entire country [but] LSU’s work to leverage AI for precision medicine will allow us to devise new molecular-driven treatments for every patient.”
Dr. John Stewart, surgical oncologist and director of the LSU Health New Orleans/LCMC Health Cancer Center