IA technology “digital imprint” could lead to patient cancer drugs in half of the current time

Scientists have developed a revolutionary “fingerprint” technology that can show precisely how cancer cells react to new drugs, simply observing changes to their form.

The new technology, which has been developed by a team from the Institute of Cancer Research in London, will allow researchers to quickly assess the ability to new drugs To achieve their planned goal, reducing the years of leave drug development process—OCOURAGE new drugs to reach patients faster.

Scientists believe that their approach could also save millions of books by reducing investments and efforts in failing projects. Research is published in the newspaper Cellular systems.

Using 3D imaging of cells

Above all, technology helps scientists match the right drugs to the right patients, allowing them to design clinical trials for specific cancer subtypes at a much earlier stage – avoiding costly failure of clinical trials.

The team of the Institute of Cancer Research (ICR) formed AI technology using nearly 100,000 3D images of melanoma skin cancer cells—Page with advanced microscopy and geometric learning to analyze information on the shape of the cells.

Previous technologies have only been formed on 2D flat images of cells on a microscope slide – which do not take into account the 3D form of a cell, as it appears in the body.

The team treated cells with a variety of drugs and used its newly created AI tool to find out which form changes have been caused by each medication.

They have shown that the tool could predict which medication was used on cells with an accuracy up to 99.3% and it could even distinguish the changes of form caused by drugs which, although targeting different proteins, ultimately have very similar effects on the cell.

Researchers have shown that AI technology learned with precision the underlying biochemical changes that occurring when melanoma cells have been treated with certain drugs. He was able to identify the important proteins that the team now explores as potential targets to develop new drugs.

Cut the steps in the drug development process

The team has also shown that their AI tool operated for other types of cells – including red blood cells, cerebral vessel cells and stem cells, indicating that other diseases could benefit from this technology.

The development of a new medication generally takes 10 to 12 years. However, the ICR team believes that using its AI technology at the start of this process could reduce many stages in the preclinical phase – breaking from three years to three months – and reducing the delay to test new drugs up to six years, as patients most likely to benefit could be determined earlier, and side effects could be predicted.

The AI ​​tool has outperformed other similar algorithms because it is the first to use 3D information on the form of a cell – the complete image of the cell, as it would appear in a body – instead of only 2D information on a microscope slide. The tool has also been formed to take into account the variability of a cell population, while other algorithms consult either unique cells or take an average of cell shape through the population.

Implementation of the tool in research on the discovery of ICR drugs

Researchers will work with teams from the Center for Cancer Drug Discovery of the ICR to implement their AI technology in the process of discovery of targeted protein degrearmen – a new type of medication that cooptes the cell elimination system of a cell to eliminate the criminal protein.

The research team has also patented its tool and set up a spin-out, sentine4D company, to take innovation in the next phase and implement it in the discovery and development of drugs.

Sental4D is the last spin-out company to be announced by the ICR and follows the recent successes of Spinout, in particular the Foundation of Monte Rosa Therapeutics, which is now registered on the New York Stock Exchange in New York.

“The tool is so powerful that we can rationalize the drug discovery process”

Professor Chris Bakal, professor of cancer morphodynamics at the Research Institute on Cancer, London, said: “The form of 3D cells is like a fingerprint of the State and cellular function – it is a tank of information before unexploited. Using AI, we can decode this fingerprint and reveal how the cells react to drugs.

“The tool that we have created is so powerful that we will be able to rationalize the process of discovery of drugs that lasted years, which saves time and money. Patients with cancer need new treatment options as quickly as possible, so accelerating this process will be extremely precious.”

Dr. Matt de Vries, co-founder and director of SENTALINE4D technology, said: “With the AI ​​tool that we have created, it will be possible to predict how effective a drug will be and if there will be side effects. The tool could work for a range of diseases, because we have shown that it will collect the changes in form for a number of different diseases, because we have shown that Different elements different, because we have shown that it would pick up the changes of form for a certain number of different different elements, because we have shown that it would pick up form changes for a certain number of different different elements. cell types and drugs.

“Our new company, Sental4D, aims to use this tool to eliminate conjectures and increase the chances of success in the subsequent phases of drug development – to provide treatment to patients earlier.”

Professor Kristian Helin, director general of the Institute of Cancer Research in London, said: “The ICR is dedicated to discovering new drugs to meet the challenges of cancer and resistance to drugs, so that cancer patients have more treatment options – lives and save lives.

“This latest technology is based on years of work at the ICR to understand the form of cancer cells and use artificial intelligence to analyze data. I can’t wait to see this technology used to develop new drugs that have a real impact for people with cancer.”