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Advancing Clinical Operations with AI : 3 High Impact Areas
7 students

Advancing Clinical Operations with AI : 3 High Impact Areas

Applied AI in Clinical Research: Trial Design, PV Automation, FDA-EMA Compliance & 90-Day Action Roadmap
Created bySusmit Bhowmik, PhD
Last updated 6/2026
English

What you'll learn

  • Apply AI tools to clinical trial protocol design using real methods from Gilead, Medidata, and Tufts CSDD benchmarks — no coding required.
  • Automate adverse event case processing and signal detection using AI — reduce PV workload by up to 70% with verified real-world techniques.
  • Build role-specific AI prompt templates for CRA, PV, regulatory, and data management tasks you can use in your workflow immediately.
  • Design and pilot an AI agent workflow for clinical trial monitoring, TMF management, or pharmacovigilance using free and low-cost tools.
  • Execute a 90-day personal AI roadmap with monthly milestones, a prompt library tracker, and a compliance-ready documentation log.

Course content

5 sections • 5 lectures • 1h 30m total length

  • Introduction1:35

    AI is already running in clinical trials at Gilead, Roche, IQVIA, and Medidata. This course shows you exactly how — and how to use it yourself.

    Built for clinical research professionals who want practical skills, not theory. Every tool, technique, and example in this course is verified, referenced, and in production use today.

    In this course you will:

    • Master AI prompt engineering for clinical trial protocol design and pharmacovigilance

    • Understand real FDA-EMA 2026 regulatory requirements for AI in drug development

    • Build AI agent workflows for monitoring, safety surveillance, and TMF management

    • Automate repetitive clinical operations tasks using free no-code tools

    • Apply synthetic control arm methodology backed by peer-reviewed evidence

    • Complete a hands-on capstone project with three real clinical research scenarios

    • Execute a 90-day personal roadmap with trackers, templates, and documentation tools

    No coding. No prior AI experience. Immediately applicable from day one.

Requirements

  • Basic familiarity with clinical research — you work in or study CRA, PV, regulatory affairs, data management, or clinical operations.
  • No coding, programming, or data science background needed. If you can write an email, you can use every tool in this course.
  • No prior AI experience required. The course starts from practical basics and builds to agents and automation step by step.
  • Access to any free AI tool — Claude, ChatGPT, or Microsoft Copilot. A free account is enough to complete all hands-on exercises.

Description

re you working in clinical research and watching AI transform the industry around you — but not yet in your workflow?

This course closes that gap. In 60 focused minutes you will learn exactly how leading pharmaceutical companies, CROs, and regulatory bodies are deploying AI in clinical trials right now — and walk away with tools, templates, and a 90-day action plan you can apply immediately.

No coding. No data science background. No theory without application.

What you will learn:

  • Apply AI to clinical trial protocol design using real methods from Gilead, Medidata, and Tufts CSDD benchmark data

  • Automate adverse event case processing and pharmacovigilance signal detection — reduce manual workload using verified real-world deployments

  • Build a personal prompt library with role-specific templates for CRAs, PV scientists, regulatory affairs, and data managers

  • Understand and apply the FDA-EMA January 2026 joint AI principles and EU AI Act requirements to your clinical research submissions

  • Design AI agent workflows for monitoring, TMF management, and safety surveillance using free and low-cost tools

  • Evaluate synthetic control arms, RBQM platforms, and AI feasibility tools backed by 44 peer-reviewed and regulatory references

  • Complete a hands-on capstone project across three real clinical research scenarios with full grading criteria

  • Execute your personal 90-day AI roadmap with monthly milestones, prompt trackers, and a compliance-ready documentation log

This course is for clinical research associates, pharmacovigilance scientists, regulatory affairs managers, data managers, and clinical project managers at sponsors, CROs, and biotech companies who want practical AI skills — not buzzwords.

What is included: full lecture with 30 quiz questions, presenter scripts, 44 verified references, capstone project, and a downloadable 90-day personal roadmap.

Every tool, every technique, every example is in production use today.

Who this course is for:

  • Clinical Research Associates and monitors who want to use AI to draft monitoring notes, identify site risks, and reduce manual reporting time.
  • Pharmacovigilance and drug safety professionals processing high volumes of adverse events who need faster, compliant narrative generation tools.
  • Regulatory affairs managers and submission specialists who need to understand the FDA-EMA January 2026 AI principles before their next filing.
  • Clinical data managers and biostatisticians looking to automate repetitive data quality tasks and explore AI-assisted protocol feasibility scoring.
  • linical project managers and trial operations leads at sponsors, CROs, or biotech companies piloting AI tools across their trial portfolios.
  • Graduate students and early-career researchers in clinical trials, pharmacology, or regulatory science building AI literacy before entering industry.

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