AI Tool Developed To Enhance Personalised Cancer Treatment

An international team of scientists has developed an Artificial Intelligence tool called AAnet to enhance cancer treatment by mapping cellular diversity within tumours.

Xinhua News Agency stated that the innovation of this AI tool will help address tumour heterogeneity in oncology. There, it will cause treatment resistance and recurrence.

Researchers developed the AAnet AI tool to study gene activity in individual cancer cells.

Sydney-based Garvan Institute of Medical Research, in collaboration with Yale School of Medicine, have given birth to this invention.

Researchers created AAnet using deep learning to tackle tumour heterogeneity in oncology.

A multinational research team stated that the AAnet AI tool can identify five different types of cells within tumours.

It will also give information about each cell’s behaviour and its risk of spreading.

They said that it will help doctors to understand tumours in a new and better way that is different from older methods.

It will give better results in treatment by differentiating tumour cells rather than treating all the tumour cells the same way.

Why is heterogeneity still a problem?

The study’s co-senior author, Associate Professor Christine Chaffer from the Garvan Institute, explained why Heterogeneity is still a problem.

He said, “Heterogeneity is a problem because currently, we treat tumours as if they are made up of the same cell. This means we give one therapy that kills most cells in the tumour by targeting a particular mechanism. But not all cancer cells may share that mechanism”.

Chaffer said that, as a result of this treatment, some cancer cells manage to survive and regrow the disease again.

Further, she added more, which provides a way to biologically characterise tumour diversity.

Also enables the design of combination therapies that target all tumour cell groups simultaneously.

The co-developer of the AI and Associate Professor Smita Krishnaswamy of Yale University indicated the potential of AAnet.

She said that this is the first method to deal with the complexity of tumour cells into practical archetypes.

AAnet will transform the precision of oncology.

This new technology is ready to step in clinical use.

Soon, the AI analysis and traditional diagnostics will combine to give a treatment to each tumour’s cell types.

A study published in the journal Cancer Discovery revealed it has been validated for breast Cancer and has also been proposed for other cancers and immune diseases.

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