Machine learning algorithms could predict breast cancer treatment responses

Different patients with the same type of cancer can have different responses to the same medication, which leaves doctors in a tough spot: how do they know which treatment will have the best response? If they get it right, their patient may enter remission; but if they're wrong the patient's health will deteriorate. Now researchers at Western University might have the answer. They developed machine learning algorithms – a branch of artificial intelligence – that crunch genetic data to determine the most likely treatment response and allow more personalized treatment regimens. The researchers used a set of 40 genes that are found in 90 per cent of breast cancer tumors for their analysis of data from cell lines and tumor tissue samples from around 350 cancer patients who were treated with at least one of the two chemotherapy drugs paclitaxel and gemcitabine.

They then set their computers to work crunching the data and identifying associations between the drug and patient genes. Their machine learning tool managed to predict gemcitabine resistance and paclitaxel sensitivity with 84 per cent accuracy, paclitaxel resistance with 82 per cent accuracy, and gemcitabine response (i.e. remission or not) with 62 to 71 per cent accuracy.

This is not the first case of machine learning being used to help with cancer treatment. A new company called Deep Genomics founded earlier this year to identify never before seen gene variants and mutations in various diseases, including cancer, by pitting computers against huge data sets. And last year 15-year-old Nathan Han won an Intel prize for his machine learning tool that studies mutations of a particular gene linked to breast cancer.

A paper describing the study was published in the journal Molecular Oncology.


4 Replies

  • These are similar to Chemosensitivity test which are performed on patient own tumour cells (in-vitro). In future we hope to have personalised kind of treatment for each and every patient.

  • This will help a lot

  • Hope this becomes the norm for cancer treatment in India.

  • Future holds lots of promises.

    This is with machines. Presently we do have saliva based genetic tests which enable one to assess whether a person will respond to a particular chemo drug or not and helps to individualise treatment. Not in widespread use and also requires lot of validation in India yet, but we are slowly reaching there

    It's good to see the phenomenal level of progress that goes on. Thanks for sharing this with us.

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