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Tuesday, June 14 • 2:00pm - 5:00pm
22P: Machine Learning in Pharmacovigilance

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Component Type: Tutorial
CE: ACPE 2.75 Application UAN: 0286-0000-22-503-L04-P ; CME 2.75; IACET 2.75; RN 2.75

Preregistration required and is an additional fee. Already registered? Log in to DIA's My Account/My Events

This short course will explore machine learning (ML) within the Regulatory/ Pharmacovigilance (PV) landscape. The instructors will provide a high-level introduction to machine learning, including common tools and project tips. We will then evaluate example applications, such evaluation of Single Case Drug-Event-Pair (DEP) causality using the Modified Naranjo Causality Score for ICSRs (MONARCSi). The course will also focus on important non-technical aspects of using ML in PV, including potential approaches to performance evaluation, monitoring over time, maintaining human oversight, reporting, and legal considerations. Since machine learning requires resources from across the organization, this course is designed for anyone interested in sponsoring or joining a machine learning project within their organization.

Registration Info Rate: $350
Need approval in order to attend? Download and fill out our Justification Letter to demonstrate to your supervisor why this is a must-attend event.
Enhance your experience and register for two or more short courses at the same time and receive $50 in savings. 
Purchase must happen at same time. Discount will be reflected on the last page of the cart.Upon completion of registration, participants will gain access to the following:
  • Live Event Access
  • Presentation Slides

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Who should attend?

This course is designed for anyone with broad interest in PV, Statistics, or Quality that is interested in sponsoring/participating in machine learning projects applied to Pharmacovigilance (PV).

Learning Objectives

At the conclusion of this short course, participants should be able to:
  • Discuss key recent advances making Machine Learning in pharmacovigilance practical
  • Identify potential use cases in pharmacovigilance
  • Assess the potential benefits, limitations, and risks of Machine Learning applied to pharmacovigilance

avatar for Shaun Comfort

Shaun Comfort

Principal Science Enablement Director, Genentech, A Member of the Roche Group, United States
Dr. Comfort is a Principle Scientific Enablement Director for Roche in Science Enablement and Processes, leading innovation work supporting Pharmacovigilance. He is a Board Certified Neurologist with 20 years combined biopharma industry/regulatory experience. Dr. Comfort’s current... Read More →
avatar for Bruce Donzanti

Bruce Donzanti

PV Consultant, Self, United States
Bruce has a PhD in pharmacology/neuroscience with almost 30 years of experience in the pharma/biotech industry. Prior to industry, he performed research on mechanisms of neuronal degeneration and neurotoxicology and lectured in neuropharmacology to graduate and medical students while... Read More →
avatar for Robert Ball

Robert Ball

Deputy Director, Office of Surveillance and Epidemiology, CDER, FDA, United States
Robert Ball MD, MPH, ScM is Deputy Director, Office of Surveillance and Epidemiology (OSE), Center for Drug Evaluation and Research (CDER), FDA. Dr. Ball shares in the responsibilities for leading OSE staff evaluating drug and biologic product safety and effectiveness using Real World... Read More →
avatar for Sunita Dhar

Sunita Dhar

Executive Medical Group Director, Genentech, United States
Sunita Dhar is an Executive Medical Group Director in Clinical Safety and the Franchise head for the I2O portfolio at Genentech. Sunita joined the industry after 12 years of clinical practice and has over seventeen years of experience in drug development, safety science, and pharmacovigilance... Read More →

Tuesday June 14, 2022 2:00pm - 5:00pm CDT
Virtual McCormick Place 2301 South Indiana Avenue Gate 40 Chicago, IL 60616
  20: Short Courses, Tutorial |   01: ClinSafety-PV, Tutorial
  • Credit Type ACPE, CME, IACET, RN
  • Tags Tutorial