A team of LSU researchers has developed a way to determine which drug therapies work best against an individual's unique type of cancer, possibly providing a way to find cures more quickly and make treatment more affordable. The interdisciplinary team includes researchers from the School of Veterinary Medicine, College of Science, College of Engineering and the Center for Computation & Technology. It created CancerOmicsNet, a new drug discovery engine run by artificial intelligence. Using algorithms originally designed to map complex social networks, like those utilized by Facebook, researchers generated three-dimensional graphs of molecular datasets that include cancer cell lines, drug compounds and interactions among proteins inside the human body. The graphs are then analyzed and interconnected by AI, forming a much clearer picture of how a specific cancer would respond to a specific drug.

In the fields of medicine and pharmacology, drugs have historically been discovered either by identifying active ingredients from traditional remedies, or by serendipity, similar to how penicillin was discovered in 1928. But modern scientists have found an alternative method that makes the hunt for new pharmaceuticals quicker, cheaper and more effective. AI, or artificial intelligence, can be found in everything from chess-playing computers, to self-driving cars, to the maps application on your phone when it's calculating directions. And AI has found a new home: discovering new drugs. It currently takes on average 10 years and over $2 billion to create a new drug and get it approved.