Dr. Cadotte specializes in FDA interactions and strategy, development of regulatory submissions, medical and regulatory writing, review and analysis of pre-clinical and clinical data, design of clinical trials, regulatory review of marketing materials, and regulatory strategy for medical devices. He specializes in medical device software, Software as a Medical Device (SaMD), Software in a Medical Device (SiMD), Artificial Intelligence / Machine Learning (AI/ML) devices, Clinical Decision Support, Predetermined Change Control Plans, and Computer Aided Devices including Triage, Notification, Detection, and Diagnosis (CADt, CADe, CADx, and CADe/x).
Dr. Cadotte received a M.S and Ph.D. in Biomedical Engineering, specializing in Neuroengineering and Multivariate Time Series Analysis, from the University of Florida. He also received a Bachelor of Science in Chemical Engineering from Virginia Tech.
Dr. Cadotte was the Team Lead for Imaging Software review at FDA, leading a team of scientists, clinicians, and engineers in the regulation of imaging software devices marketed in the United States. His specialty being computer aided devices including Computer Aided Triage and Notification (CADt) and Computer Aided Detection and Diagnosis (CADe, CADx, CADe/x) devices which included the majority of AI/ML devices currently reviewed by CDRH. He previously served as a Health Scientist and Team Lead with Digital Health at FDA where he worked on software review and the Pre-Certification Program. He was also a member of the CDRH Artificial Intelligence Machine Learning Working Group where he contributed to the white paper “Proposed Regulatory Framework for Modifications to Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device” and the “Artificial Intelligence/Machine Learning (AI/ML)-Based Software as a Medical Device (SaMD) Action Plan.”
He worked in industry as an applications scientist and product development prior to working for FDA where he learned and led medical device hardware and software development for high density electrophysiology acquisition systems and optogenetics.