• November 30, 2022

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Researchers from the Institute of Medical Science at the University of Tokyo (IMSUT) and Fujitsu Research are using artificial intelligence (AI)-powered language processing technology to create a knowledge database of 860,000 medical papers. The research team says this technology reduces the time to develop genetic mutation treatment plans by more than 50%, reducing the hours of examination work from 6,000 to 3,000 hours.

According to Dr. Masaru Fuji, Project Manager, Innovative Computing Project, Computing Laboratory, Fujitsu Research, Cancer genome therapies benefit from AI technology. “They are already improving the accuracy of operations, anticancer drugs, and radiation, but AI could make them even more effective,” said Fuji.

Fuji says that in cancer genome treatments, doctors predict the physical makeup, disease stage, drug response, and side effects of cancer patients, but to decide the best course of therapy, medical practitioners must spend significant time finding and analyzing relevant medical research papers.


“This is where AI can help the most,” said Fuji. “Genomic medical AI can recommend suitable treatment information for target patients quickly and flexibly by being trained from a large amount of genomic data, including the latest research data.”

Fuji says that AI can sometimes predict relevant information, even for unknown genomic information not directly described in the training data.

“This technology will allow physicians to consider novel treatment options for patients for whom it has not been possible to reliably predict treatment in the past,” said Fuji.

Fuji says the treatment reach rate for genomic medicine remains an ongoing issue.

“In genomic medicine, experts anticipate that effective treatment outcomes can be obtained if genomic information that leads to treatment is obtained through testing,” said Fuji, “But under the current situation in which unknown genomes account for the majority of genomic data, the ratio of genomic information that leads to treatment is low.”

Fujitsu Laboratories and Aichi Cancer Center are also exploring how AI can make cancer genome information analysis more efficient.

“We are working to create technology that makes it faster to analyze cancer gene panel testing results and explore the links between patients’ genetic mutations and diseases,” said Fuji.


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