{"title":"日本制药企业协会非临床评价专家委员会人工智能病理工作组报告:人工智能病理问卷调查及全幻灯片影像数据库的利用","authors":"Masaki Yamazaki, Emi Tomikawa, Miyoko Okada, Satoru Kajikawa, Yui Terayama, Shino Kumabe, Tetsuya Sakairi, Akira Inomata, Izumi Matsumoto, Gen Sato, Mutsumi Suzuki","doi":"10.1293/tox.2024-0099","DOIUrl":null,"url":null,"abstract":"<p><p>In recent years, the development of Artificial Intelligence (AI) technology has led to the introduction and use of AI-based histopathological evaluation (AI pathology) by various companies and organizations. The AI Pathology Task Force of the Non-clinical Evaluation Expert Committee within the Drug Evaluation Committee of the Japan Pharmaceutical Manufacturers Association (JPMA) recognizes the importance of understanding the current use and needs surrounding AI pathology in Japan. This includes its role in non-clinical research fields, such as toxicity evaluation, drug efficacy evaluation, and basic research. In addition, assessing needs and challenges related to pathology image databases is essential. Between October and November 2023, with the cooperation of the Japanese Society of Toxicologic Pathology (JSTP), we conducted a questionnaire survey on non-clinical pathology image databases to explore these issues among JPMA-affiliated and JSTP-affiliated organizations. The questionnaire survey consisted of three items: (1) implementation and utilization of whole slide images, (2) use of AI pathology in non-clinical research fields, and (3) needs and feasibility of establishing a precompetitive pathology image database (repository) and AI pathology in the non-clinical pathology field. This report summarizes the survey results and serves as a foundation for guiding future directions in the use of AI pathology in non-clinical studies in Japan.</p>","PeriodicalId":17437,"journal":{"name":"Journal of Toxicologic Pathology","volume":"38 3","pages":"205-211"},"PeriodicalIF":0.9000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12208863/pdf/","citationCount":"0","resultStr":"{\"title\":\"Report of the AI Pathology Task Force, Non-clinical Evaluation Expert Committee, Japan Pharmaceutical Manufacturers Association: questionnaire survey on AI pathology and utilization of whole slide image database.\",\"authors\":\"Masaki Yamazaki, Emi Tomikawa, Miyoko Okada, Satoru Kajikawa, Yui Terayama, Shino Kumabe, Tetsuya Sakairi, Akira Inomata, Izumi Matsumoto, Gen Sato, Mutsumi Suzuki\",\"doi\":\"10.1293/tox.2024-0099\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In recent years, the development of Artificial Intelligence (AI) technology has led to the introduction and use of AI-based histopathological evaluation (AI pathology) by various companies and organizations. The AI Pathology Task Force of the Non-clinical Evaluation Expert Committee within the Drug Evaluation Committee of the Japan Pharmaceutical Manufacturers Association (JPMA) recognizes the importance of understanding the current use and needs surrounding AI pathology in Japan. This includes its role in non-clinical research fields, such as toxicity evaluation, drug efficacy evaluation, and basic research. In addition, assessing needs and challenges related to pathology image databases is essential. Between October and November 2023, with the cooperation of the Japanese Society of Toxicologic Pathology (JSTP), we conducted a questionnaire survey on non-clinical pathology image databases to explore these issues among JPMA-affiliated and JSTP-affiliated organizations. The questionnaire survey consisted of three items: (1) implementation and utilization of whole slide images, (2) use of AI pathology in non-clinical research fields, and (3) needs and feasibility of establishing a precompetitive pathology image database (repository) and AI pathology in the non-clinical pathology field. This report summarizes the survey results and serves as a foundation for guiding future directions in the use of AI pathology in non-clinical studies in Japan.</p>\",\"PeriodicalId\":17437,\"journal\":{\"name\":\"Journal of Toxicologic Pathology\",\"volume\":\"38 3\",\"pages\":\"205-211\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12208863/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Toxicologic Pathology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1293/tox.2024-0099\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/3/11 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q4\",\"JCRName\":\"PATHOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Toxicologic Pathology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1293/tox.2024-0099","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/3/11 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"PATHOLOGY","Score":null,"Total":0}
Report of the AI Pathology Task Force, Non-clinical Evaluation Expert Committee, Japan Pharmaceutical Manufacturers Association: questionnaire survey on AI pathology and utilization of whole slide image database.
In recent years, the development of Artificial Intelligence (AI) technology has led to the introduction and use of AI-based histopathological evaluation (AI pathology) by various companies and organizations. The AI Pathology Task Force of the Non-clinical Evaluation Expert Committee within the Drug Evaluation Committee of the Japan Pharmaceutical Manufacturers Association (JPMA) recognizes the importance of understanding the current use and needs surrounding AI pathology in Japan. This includes its role in non-clinical research fields, such as toxicity evaluation, drug efficacy evaluation, and basic research. In addition, assessing needs and challenges related to pathology image databases is essential. Between October and November 2023, with the cooperation of the Japanese Society of Toxicologic Pathology (JSTP), we conducted a questionnaire survey on non-clinical pathology image databases to explore these issues among JPMA-affiliated and JSTP-affiliated organizations. The questionnaire survey consisted of three items: (1) implementation and utilization of whole slide images, (2) use of AI pathology in non-clinical research fields, and (3) needs and feasibility of establishing a precompetitive pathology image database (repository) and AI pathology in the non-clinical pathology field. This report summarizes the survey results and serves as a foundation for guiding future directions in the use of AI pathology in non-clinical studies in Japan.
期刊介绍:
JTP is a scientific journal that publishes original studies in the field of toxicological pathology and in a wide variety of other related fields. The main scope of the journal is listed below.
Administrative Opinions of Policymakers and Regulatory Agencies
Adverse Events
Carcinogenesis
Data of A Predominantly Negative Nature
Drug-Induced Hematologic Toxicity
Embryological Pathology
High Throughput Pathology
Historical Data of Experimental Animals
Immunohistochemical Analysis
Molecular Pathology
Nomenclature of Lesions
Non-mammal Toxicity Study
Result or Lesion Induced by Chemicals of Which Names Hidden on Account of the Authors
Technology and Methodology Related to Toxicological Pathology
Tumor Pathology; Neoplasia and Hyperplasia
Ultrastructural Analysis
Use of Animal Models.