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数字病理学与人工智能在非临床毒理学病理学中的应用——现状、挑战及未来方向

Digital Pathology and Artificial Intelligence Applied to Nonclinical Toxicology Pathology-The Current State, Challenges, and Future Directions.

作者信息

Pohlmeyer-Esch Gabriele, Halsey Charles, Boisclair Julie, Ram Sripad, Kirschner-Kitz Sarah, Knight Brian, Moulin Pierre, Frisk Anna-Lena

机构信息

Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany.

Drug Safety Research and Development, Pfizer Inc, Groton, Connecticut, USA.

出版信息

Toxicol Pathol. 2025 Aug;53(6):516-535. doi: 10.1177/01926233251340622. Epub 2025 Jun 3.

DOI:10.1177/01926233251340622
PMID:40459370
Abstract

Advancements in digital pathology and artificial intelligence (AI) have enormous transformative potential for nonclinical toxicologic pathology and are already changing the ways in which pathologists work. However, due to the rapid evolution of digital pathology and AI, the toxicologic pathology community would benefit from an update on these advancements, which can be used to aid drug development. Here we identify key articles published on the use of digital pathology and AI in the field and provide current regulatory statuses and guidelines. For digital pathology, we outline the requirements for equipment, validation processes, workflows, and archiving. Challenges to achieve system interoperability and to establish harmonization through Digital Imaging and Communications in Medicine compatibility are also discussed. For AI, we highlight considerations for model development, including the determination of ground truth, problems that may arise due to bias, and how the accuracy and precision of AI algorithms can be assessed. Finally, we discuss the challenges and potential for AI-assisted toxicologic pathology, picturing a future where technology and scientific expertise work hand-in-hand to improve the quality and efficiency of nonclinical drug safety evaluation. This publication is a deliverable of the European Innovative Medicines Initiative 2 Joint Undertaking, "Bigpicture."

摘要

数字病理学和人工智能(AI)的进展对非临床毒理病理学具有巨大的变革潜力,并且已经在改变病理学家的工作方式。然而,由于数字病理学和人工智能的快速发展,毒理病理学领域将受益于对这些进展的更新,这些进展可用于辅助药物开发。在此,我们确定了该领域发表的关于数字病理学和人工智能应用的关键文章,并提供了当前的监管状态和指南。对于数字病理学,我们概述了设备要求、验证过程、工作流程和存档。还讨论了实现系统互操作性以及通过医学数字成像和通信兼容性实现协调统一所面临的挑战。对于人工智能,我们强调了模型开发的注意事项,包括确定真值、因偏差可能出现的问题,以及如何评估人工智能算法的准确性和精确性。最后,我们讨论了人工智能辅助毒理病理学的挑战和潜力,描绘了一个技术与科学专业知识携手合作以提高非临床药物安全性评估质量和效率的未来。本出版物是欧洲创新药物倡议2联合事业“大图景”的一项成果。

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