Irish researchers have used the latest technology to “force” cancer cells to become healthy in a major breakthrough in the fight against serious diseases.
Ancer cells were transformed into healthy cells using an AI-based data analysis technology developed by a team of researchers at University College Dublin at Systems Biology Ireland (SBI).
UCLA-based researchers report today in the journal Nature that they’ve changed cancerous neuroblastoma cells into “near healthy cells,” using new artificial intelligence and machine-based learning technology, which they call “cSTAR.”
Says Professor Walter Kolsch, Director of the SBI.
Cells may be thought of as biological factories that produce proteins and chemicals.
Communication between the different parts of the plant is fundamental to ensuring that the entire entity operates efficiently.
Until now, it was not clear why these small “biological factories” had broken down, and made them sick.
SBI data analysis technology does this by determining that something in the factory is not working, finding where the problem is, and finally providing solutions to fix it.
“In this paper, we build on the fundamental work of SBI researchers to understand the cellular genes and protein networks that control cell life,” said Professor Boris Kolodenko, who led the research effort.
“Like many of the world’s leading laboratories, we have a long-standing interest in understanding how to control cell states or fates,” says Professor Kholodenko.
“Where our work differs is in its use of machine learning, advanced computational and physical methods and models with the ultimate goal of creating digital twins to accurately model human diseases and targeted interventions to treat these diseases.”
Digital twin, in the context of health, refers to a virtual version of a cell, tissue, organ, or even a person, containing all relevant biological data.
“In the future, it is expected that every person will have a digital twin created for them at birth, who will follow them throughout their life,” says Dr. Oleksiy Rokhlenko SBI, first author on the Nature paper.
cSTAR technology will initially be applied to the huge problem of drug resistance, in cancer, and many other diseases by suggesting which drug combinations or drugs might work best in patients who are resistant to prescribed drug therapy.
“About 80% of people do not respond to medications on the market today according to a 2015 research paper in Nature,” says Professor Kolsch.
“Our best-selling drugs are only effective in between 4 and 20 percent of patients across a spectrum of diseases,” says Professor Kolsch.
“This is very shocking, but we believe that with our new technology we can bring the numbers up to 30 percent or 40 percent,” he says.
In the long term, CSTAR could push the pharmaceutical industry down the personalized medicine model and away from the traditional, costly and costly efforts to find new, highly profitable drugs.
Professor Kolsch says it could take up to 15 years, and cost billions, to bring a new drug to market. This technology can speed up this process and reduce the time the industry randomly spends searching for new drugs.
c-STAR technology could also revolutionize the promising field of regenerative medicine, as scientists use stem cells to repair diseased, aging or damaged cells.
“Our technology provides greater control over the repair of pathological cells than using stem cells,” says Professor Kolsch.