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Japan-based Fujitsu Laboratories has signed a comprehensive joint research agreement with Aichi Cancer Centre to leverage artificial intelligence (AI) to improve cancer genome information analysis.

Aichi Cancer Centre intends to establish a system that could connect the results of multigene panel testing for cancer to advanced medical care for cancer patients.

Due to an increase in the number of genomic tests, the burden on a doctor to interpret individual results also increases, which is a time-consuming process.

The two entities plan to create AI technology to increase the practicability of cancer genomic medicine by introducing technology developed by Fujitsu Laboratories through a joint research project with the Institute of Medical Science at the University of Tokyo.

The technology will be built using data for genomic and clinical profiles for solid cancers held by Aichi Cancer Centre to improve the efficacy results of comprehensive genomic analysis.

The goal of the project is to elucidate the relationship between genomic profiles in cancers and their responsiveness towards anti-cancer reagents.

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The entities also plan to expand the scope of cancers that can be targeted by genomic medicine and to deliver treatments for each patient.

In the collaboration, Fujitsu Laboratories will use AI technology to develop fundamental technical elements for database development and integration of clinical information and genomic profiles for each disease area.

It will also be involved in the development of technologies that support diagnosis and selection of therapeutic reagents in cancer genomic medicine.

Aichi Cancer Center will provide confidential patient-specific cancer genomic profiles and medical records.

Fujitsu Laboratories and Aichi Cancer Center plan to integrate the results to promote cancer genomic medicine and AI, applying them to hospitals in the Tokai region.

Furthermore, cancer genome data collected from patients at hospitals will be registered in a database, expanded to develop integrated functions, allowing a more accurate selection of anti-cancer drugs.