Applications of Artificial Intelligence and Machine Learning in Toxicologic Pathology
Friday, September 24
Co-Chairs: Famke Aeffner, DVM, PhD, DACVP, Amgen; Oliver C. Turner, BSc(Hons), BVSc, MRCVS, PhD, DACVP, DABT, Novartis Institutes for Biomedical Research; and Manu S. Sebastian, DVM, PhD, DACVP, DABT, ACLAM, MD Anderson Cancer Center
Artificial intelligence (AI) and machine learning (ML) are transforming all aspects of health care—including drug development. This CE course aims at introducing this technology to toxicologists and toxicologic pathologists, as well as highlighting promise and pitfalls. To illustrate the power of machine learning, the session concludes with presentations highlighting practical applications, presented by colleagues with hands-on experience.
Introduction to Artificial Intelligence and Machine Learning
Oliver C. Turner, BSc(Hons), BVSc, MRCVS, PhD, DACVP, DABT, Novartis Institutes for Biomedical Research, East Hanover, NJ
General Uses of AI in Drug Development: AI and ML in Other Aspects of Drug Development
Manu S. Sebastian, DVM, PhD, DACVP, DABT, ACLAM, MD Anderson Cancer Center, Smithville, TX
General Uses of AI in Drug Development: Overview of Partnerships Formed by Pharma with AI Companies in the Pathology Space
Bhupinder Bawa, DVM, MVSc, PhD, DACVP, AbbVie, North Chicago, IL
Implementation: Preparing Pathology Data for ML Experiments
Jürgen Funk, DVM, FTA Pathology, Roche, Basel Switzerland
Implementation: IT Infrastructure Requirements
Julie Boisclair, DVM, DES, MSc, DACVP, DABT, Novartis Institutes for Biomedical Research, Novartis Pharma AG, Basel, Switzerland
Practical Examples: Performance of the Differential Ovarian Follicle Count Using Deep Neuronal Networks
Heike A. Marxfeld, PhD, DECVP, EBVS, BASF SE, Ludwigshafen, Germany
Practical Examples: Deep Learning AI in Decision Support for the Bench Toxicologic Pathologis
Daniel G. Rudmann, DVM, PhD, DACVP, FIATP, Charles River Laboratories, Broomfield, CO
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