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

• Published in: Journal of Toxicologic Pathology Vol. 38; no. 3; pp. 205 - 211
• Main Authors: Yamazaki, Masaki, Tomikawa, Emi, Okada, Miyoko, Kajikawa, Satoru, Terayama, Yui, Kumabe, Shino, Sakairi, Tetsuya, Inomata, Akira, Matsumoto, Izumi, Sato, Gen, Suzuki, Mutsumi
• Format: Journal Article
• Language: English
• Published: Japan JAPANESE SOCIETY OF TOXICOLOGIC PATHOLOGY 01.01.2025; 日本毒性病理学会; Japanese Society of Toxicologic Pathology
• Subjects: AI pathology; Artificial Intelligence (AI) pathology; digital pathology; non-clinical; questionnaire survey; digital pathology; non-clinical; Artificial Intelligence (AI) pathology; questionnaire survey
• ISSN: 0914-9198; 1881-915X
• DOI: 10.1293/tox.2024-0099

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.