When healthcare professionals treat patients suffering from advanced cancers, they usually need to use a combination of different therapies. In addition to cancer surgery, the patients are often treated with radiation therapy, medication, or both.

Medication can be combined, with different drugs acting on different cancer cells. Combinatorial drug therapies often improve the effectiveness of the treatment and can reduce the harmful side-effects if the dosage of individual drugs can be reduced. However, experimental screening of drug combinations is very slow and expensive, and therefore, often fails to discover the full benefits of combination therapy. With the help of a new machine learning method, one could identify best combinations to selectively kill cancer cells with specific genetic or functional makeup. 

Read the article in full on the helsinki.fi website: https://www.helsinki.fi/en/news/life-science-news/ai-predicts-which-drug-combinations-kill-cancer-cells 

Original publication:

Heli Julkunen, Anna Cichonska, Prson Gautam, Sandor Szedmak, Jane Douat, Tapio Pahikkala, Tero Aittokallio, and Juho Rousu. Leveraging multiway interactions for systematic prediction of pre-clinical drug combination effects. Nature Communications. DOI: 10.1038/s41467-020-19950-z