In a new study, researchers developed a machine learning model that accurately predicts how combinations of cancer drugs kill various types of cancer cells.
The new AI model was trained with a large set of data obtained from previous studies that examined the association between drugs and cancer cells.
The research was conducted by at Aalto University, University of Helsinki and the University of Turku in Finland.
When healthcare professionals treat patients suffering from advanced cancers, they usually need to use a combination of therapies.
In addition to cancer surgery, the patients are often treated with radiation therapy, medication or both.
Medication can be combined with drugs selected for specific 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, it is possible to identify the best combinations that selectively kill cancer cells with specific genetic or functional makeup.
In the study, the team showed that the model found associations between drugs and cancer cells that were not observed previously.
The model accurately predicts how a drug combination selectively inhibits particular cancer cells when the effect of the drug combination on that type of cancer has not been previously tested.
This will help cancer researchers to prioritize which drug combinations to choose from thousands of options for further research.
The team says the same machine learning approach could be used for non-cancerous diseases. In this case, the model would have to be re-taught with data related to that disease.
For example, the model could be used to study how different combinations of antibiotics affect bacterial infections or how effectively different combinations of drugs kill cells that have been infected by the COVID-19 virus.
One author of the study is Professor Juho Rousu from Aalto University.
The study is published in Nature Communications.
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