Introducing AI to the molecular tumor board: one direction toward the establishment of precision medicine using large-scale cancer clinical and biological information

被引：26

作者：

Hamamoto, Ryuji ^{[1
,2
]}

Koyama, Takafumi ^{[3
]}

Kouno, Nobuji ^{[1
,4
]}

Yasuda, Tomohiro ^{[1
,5
]}

Yui, Shuntaro ^{[1
,5
]}

Sudo, Kazuki ^{[3
,6
]}

Hirata, Makoto ^{[7
]}

Sunami, Kuniko ^{[8
]}

Kubo, Takashi ^{[8
]}

Takasawa, Ken ^{[1
,2
]}

Takahashi, Satoshi ^{[1
,2
]}

Machino, Hidenori ^{[1
,2
]}

Kobayashi, Kazuma ^{[1
,2
]}

Asada, Ken ^{[1
,2
]}

Komatsu, Masaaki ^{[1
,2
]}

Kaneko, Syuzo ^{[1
,2
]}

Yatabe, Yasushi ^{[9
,10
]}

Yamamoto, Noboru ^{[3
]}

机构：

[1] Natl Canc Ctr, Div Med AI Res & Dev, Chuo Ku, 5-1-1 Tsukiji, Tokyo 1040045, Japan

[2] RIKEN, Canc Translat Res Team, Ctr Adv Intelligence Project, Chuo Ku, 1-4-1 Nihonbashi, Tokyo 1030027, Japan

[3] Natl Canc Ctr, Dept Expt Therapeut, Chuo Ku, 5-1-1 Tsukiji, Tokyo 1040045, Japan

[4] Kyoto Univ, Grad Sch Med, Dept Surg, Sakyo Ku, Yoshida Konoe Cho, Kyoto 6068303, Japan

[5] Hitachi Ltd, Res & Dev Grp, 1-280 Higashi Koigakubo, Kokubunji, Tokyo 1858601, Japan

[6] Natl Canc Ctr, Dept Med Oncol, Chuo Ku, 5-1-1 Tsukiji, Tokyo 1040045, Japan

[7] Natl Canc Ctr, Dept Genet Med & Serv, Chuo Ku, 5-1-1 Tsukiji, Tokyo 1040045, Japan

[8] Natl Canc Ctr, Dept Lab Med, Chuo Ku, 5-1-1 Tsukiji, Tokyo 1040045, Japan

[9] Natl Canc Ctr, Dept Diagnost Pathol, Chuo Ku, 5-1-1 Tsukiji, Tokyo 1040045, Japan

[10] Natl Canc Ctr, Div Mol Pathol, Chuo Ku, 5-1-1 Tsukiji, Tokyo 1040045, Japan

来源：

EXPERIMENTAL HEMATOLOGY & ONCOLOGY | 2022年 / 11卷 / 01期

关键词：

Molecular tumor board; Precision medicine; Artificial intelligence; Next-generation sequencing; Natural language processing; ELECTRONIC HEALTH RECORDS; ARTIFICIAL-INTELLIGENCE; CARE; ONCOLOGY; COMPUTER; DEVICES; RISK; IDENTIFICATION; FEASIBILITY; CHECKPOINT;

D O I：

10.1186/s40164-022-00333-7

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

Since U.S. President Barack Obama announced the Precision Medicine Initiative in his New Year's State of the Union address in 2015, the establishment of a precision medicine system has been emphasized worldwide, particularly in the field of oncology. With the advent of next-generation sequencers specifically, genome analysis technology has made remarkable progress, and there are active efforts to apply genome information to diagnosis and treatment. Generally, in the process of feeding back the results of next-generation sequencing analysis to patients, a molecular tumor board (MTB), consisting of experts in clinical oncology, genetic medicine, etc., is established to discuss the results. On the other hand, an MTB currently involves a large amount of work, with humans searching through vast databases and literature, selecting the best drug candidates, and manually confirming the status of available clinical trials. In addition, as personalized medicine advances, the burden on MTB members is expected to increase in the future. Under these circumstances, introducing cutting-edge artificial intelligence (AI) technology and information and communication technology to MTBs while reducing the burden on MTB members and building a platform that enables more accurate and personalized medical care would be of great benefit to patients. In this review, we introduced the latest status of elemental technologies that have potential for AI utilization in MTB, and discussed issues that may arise in the future as we progress with AI implementation.

引用

页数：23

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