Machine Learning in Pharmacovigilance On-Demand Course
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Keyword(s)
Online learning; drug safety; pharmacovigilance; artifical intelligence; machine learning; MHRA; FDA; regulatory affairs
This on-demand 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. Example applications, such evaluation of Single Case Drug-Event-Pair (DEP) causality using the Modified Naranjo Causality Score for ICSRs (MONARCSi) will be reviewed and evlauated. 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.Register Here!
Credit Information
ACPE = 3.75
IACET = .4
IACET = .4
Description
Learning Objectives:
At the conclusion of this course, participants should be able to:
- Recognize 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
Featured Topics:
- Introduction to Machine Learning and Artificial Intelligence
- Looking Deeper into Machine Learning
- A Simple Machine Learning Example
- Building Your Human Expert Reference Comparator
- Artificial Intelligence (AI) for Individual Case Safety Report (ICSR) Processing and Assessment: Lessons Learned and a Framework for Readiness
- MHRA opinion on the use of Machine Learning in Pharmacovigilance