Results of the European Society of Toxicologic Pathology Survey on the Use of Artificial Intelligence in Toxicologic Pathology

Author:

Palazzi Xavier1ORCID,Barale-Thomas Erio2ORCID,Bawa Bhupinder3ORCID,Carter Jonathan4,Janardhan Kyathanahalli5ORCID,Marxfeld Heike6ORCID,Nyska Abraham7,Saravanan Chandrassegar8ORCID,Schaudien Dirk9ORCID,Schumacher Vanessa L.10ORCID,Spaet Robert H.11,Tangermann Simone6,Turner Oliver C12ORCID,Vezzali Enrico13ORCID

Affiliation:

1. Pfizer Inc., Groton, Connecticut, USA

2. Janssen Research & Development, Beerse, Belgium

3. AbbVie Inc., Chicago, Illinois, USA

4. Labcorp Early Development Laboratories, Harrogate, UK

5. Merck & Co., Inc., Rahway, New Jersey, USA

6. Badische Anilin- und Sodafabrik, Ludwigshafen, Germany

7. Tel Aviv University, Tel Aviv, Israel

8. Novartis Institutes for BioMedical Research, Cambridge, Massachusetts, USA

9. Fraunhofer Institute for Toxicology and Experimental Medicine, Hanover, Germany

10. Roche Pharma Research and Early Development, Basel, Switzerland

11. RSPathologics, LLC, Bend, Oregon, USA

12. Novartis Institutes for BioMedical Research, East Hanover, New Jersey, USA

13. Idorsia Pharmaceuticals Ltd, Allschwil, Switzerland

Abstract

The European Society of Toxicologic Pathology (ESTP) initiated a survey through its Pathology 2.0 workstream in partnership with sister professional societies in Europe and North America to generate a snapshot of artificial intelligence (AI) usage in the field of toxicologic pathology. In addition to demographic information, some general questions explored AI relative to (1) the current status of adoption across organizations; (2) technical and methodological aspects; (3) perceived business value and finally; and (4) roadblocks and perspectives. AI has become increasingly established in toxicologic pathology with most pathologists being supportive of its development despite some areas of uncertainty. A salient feature consisted of the variability of AI awareness and adoption among the responders, as the spectrum extended from pathologists having developed familiarity and technical skills in AI, to colleagues who had no interest in AI as a tool in toxicologic pathology. Despite a general enthusiasm for these techniques, the overall understanding and trust in AI algorithms as well as their added value in toxicologic pathology were generally low, suggesting room for the need for increased awareness and education. This survey will serve as a basis to evaluate the evolution of AI penetration and acceptance in this domain.

Publisher

SAGE Publications

Subject

Cell Biology,Toxicology,Molecular Biology,Pathology and Forensic Medicine

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