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Virtual Event

2022 年 06 月 14 日 2:00 下午 - 2022 年 06 月 14 日 5:00 下午

(Eastern Standard Time)

Machine Learning in Pharmacovigilance


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

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.


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).


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