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AI in Pharmacovigilance: Prompting, Compliance, Workflows
Hot & New
New
Rating: 4.3 out of 5(21 ratings)
109 students

AI in Pharmacovigilance: Prompting, Compliance, Workflows

Generative AI, prompting, compliance, governance, and workflow automation for practical pharmacovigilance use
Hot & New
New
Created bySafeMeds Academy
Last updated 4/2026
English

What you'll learn

  • Explain how AI, NLP, LLMs, and generative AI apply to pharmacovigilance workflows
  • Use prompting techniques for PV tasks such as summarization, drafting, extraction, and workflow support
  • Identify compliance, governance, privacy, and validation considerations for AI in regulated PV work
  • Evaluate practical AI use cases across case processing, literature review, signal support, and safety operations
  • Distinguish low-risk support use cases from higher-risk judgment tasks in PV
  • Build a practical roadmap for piloting and adopting AI in a pharmacovigilance team

Course content

12 sections • 46 lectures • 5h 37m total length

  • Welcome to the Course5:58
  • Who This Course Is For and What You Will Build5:10

Requirements

  • No programming experience is required
  • Basic familiarity with pharmacovigilance, drug safety, or life sciences will be helpful
  • An interest in AI, workflow improvement, and regulated healthcare operations
  • A willingness to think critically about compliance, oversight, and real-world implementation

Description

This course contains the use of artificial intelligence.


Artificial intelligence is rapidly changing how pharmacovigilance teams think about workflow, efficiency, review, and compliance. But many professionals still struggle to connect AI concepts to real PV work in a clear and practical way. This course is designed to bridge that gap.


In this course, you will learn how AI fits into pharmacovigilance from a workflow-first perspective. You will build a practical understanding of core concepts such as AI, machine learning, NLP, LLMs, generative AI, retrieval, and agentic systems without needing a technical or coding-heavy background. More importantly, you will learn how these concepts apply to real PV work.


We will cover prompting, AI-supported drafting, summarization, literature review support, signal-related workflows, governance, privacy, validation thinking, audit readiness, and implementation planning. You will also learn how to recognize the limits of AI, where human judgment must remain central, and how AI can be introduced responsibly in a regulated environment.


This course is built for pharmacovigilance professionals, drug safety teams, pharmacy and life-science learners, and regulated-work professionals who want a practical understanding of AI in PV. It is designed to help you speak more confidently about AI use cases, evaluate tools more critically, and understand how AI can support real workflows without losing compliance and oversight.


By the end of the course, you will be better prepared to understand, discuss, and apply AI concepts in pharmacovigilance in a practical, structured, and professionally credible way.


Who this course is for:

  • Pharmacovigilance professionals who want to understand how AI fits into real PV workflows
  • Drug safety associates, case processors, reviewers, and managers exploring AI-supported work
  • Pharmacy, life-science, and regulatory professionals interested in AI in a regulated environment
  • Beginners who want a practical introduction to AI in pharmacovigilance without heavy coding

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