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Toxicologic pathology is transitioning from analog to digital methods. This transition seems inevitable due to a host of ongoing social and medical technological forces. Of these, artificial intelligence (AI) and in particular machine learning (ML) are globally disruptive, rapidly growing sectors of technology whose impact on the long-established field of histopathology is quickly being realized. The development of increasing numbers of algorithms, peering ever deeper into the histopathological space, has demonstrated to the scientific community that AI pathology platforms are now poised to truly impact the future of precision and personalized medicine. However, as with all great technological advances, there are implementation and adoption challenges. This review aims to define common and relevant AI and ML terminology, describe data generation and interpretation, outline current and potential future business cases, discuss validation and regulatory hurdles, and most importantly, propose how overcoming the challenges of this burgeoning technology may shape toxicologic pathology for years to come, enabling pathologists to contribute even more effectively to answering scientific questions and solving global health issues. *This article is a product of a Special Interest Group of the Society of Toxicologic Pathology (STP). The views expressed in this article are those of the authors and do not necessarily represent the policies, positions, or opinions of the STP. [ABSTRACT FROM AUTHOR]

Digital pathology is defined as the ability to examine digitized microscopic slides and to generate qualitative and quantitative data. The field of digital pathology is rapidly evolving and has the potential to revolutionize toxicologic pathology. Techniques such as automated 2-D image analysis, whole slide imaging, and telepathology are already considered "mature" technologies and have been used for decades in exploratory studies; however, many organizations are reluctant to use digital pathology in regulatory toxicology studies. Innovative technologies using digitized slides including high-content imaging modalities and artificial intelligence are still under development but are increasingly used in toxicologic pathology. While software validation requirements are already described, clear guidance for application of these rules to the digital pathology field are few and the acceptance of these technologies by regulatory authorities remains necessary for successful adoption of digital pathology into the mainstream of toxicologic pathology. This topic was discussed during a roundtable at the 2018 Annual Congress of the French Society of Toxicologic Pathology. This opinion article summarizes the discussion regarding the current questions and challenges on the integration of innovative digital pathology tools within a good laboratory practice framework and is meant to stimulate further discussion among the toxicologic pathology community. *This is an opinion article submitted to the Toxicologic Pathology Forum and does not constitute an official position of the Society of Toxicologic Pathology or the journal Toxicologic Pathology. The views expressed in this article are those of the authors and do not necessarily represent the policies, positions, or opinions of their respective agencies and organizations. The Toxicologic Forum is designed to stimulate broad discussion of topics relevant to regulatory issues in Toxicologic pathology. Readers of Toxicologic Pathology are encouraged to send their thoughts on these articles or ideas for new topics to toxicologicpathologyforum@toxpath.org. [ABSTRACT FROM AUTHOR]