Researchers in Finland have developed an ML (Machine Learning) model that has the potential to predict the drug combinations to kill a cancer cell with more efficacy. As published in the Nature Communications journal, the results of the research demonstrated that the model found the correlation between cancer cells and drugs, which were not observed before.
The researchers at the University of Helsinki, University of Turku, and Alto University trained their Machine Learning model with a humongous set of data that was obtained from prior studies. The model gave accurate results, a correlation above 0.9, which vouches for outstanding reliability.
Combination drug AI predicts which drug combinations kill cancer cells Medical Xpress
Doctors usually use various combinations of therapies while treating cancer patients who are suffering from advanced cancer. Sometimes, they are treated with medication, radiation therapy (or both) in addition to the surgery. In the case of combined therapies, medications are integrated with a plethora of drugs that act on differing cancer cells. Often, these therapies improve the treatment’s efficiency. Furthermore, if the dosage of specific drugs is reduced, then the therapy can also decrease the critical side-effects.
However, one cannot discover the full advantages of the combination therapy since the experimental screening of this drug combination is costly and extremely slow. But thanks to Artificial Intelligence, we can now recognize the best combinations in order to kill the cancer cells selectively.