AI-DRIVEN ANALYTICS – PHARMACOVIGILANCE - Qtech-Sol offers Clinical Research / Trials, Pharmacovigilance, Drug Safety, Clinical Data Management, Clinical SAS Programming and Healthcare BA Training Programs
Category:
Analytics and Reporting
 
Duration:
8 Weeks / 140 Hours
 
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AI-Driven Analytics – Pharmacovigilance

Introduction – AI in Pharmacovigilance

Pharmacovigilance (PV) teams today face the challenge of managing large volumes of adverse event (AE) data from clinical trials, post-marketing surveillance, literature, and real-world evidence. Artificial Intelligence (AI) and Machine Learning (ML) are now being applied to streamline ICSR processing, accelerate MedDRA/WHO-DD coding, enhance signal detection, and strengthen risk management strategies.
The AIPV program introduces learners to AI-driven solutions in pharmacovigilance, equipping them with the skills to integrate automation, predictive analytics, and intelligent tools into PV workflows.

Course Name :  AI-Driven Analytics – Pharmacovigilance
Course Code :  AIPV
Experience Level :  Intermediate to Advanced
Qualification :  Bachelor’s / Master’s in Life Sciences, Pharmacy, Nursing, Medicine, Public Health, Data Science, or related fields
Student Category :  Drug Safety Associates, PV Specialists, Medical Reviewers, Data Analysts, Career Changers into AI-enabled PV

Delivery Type

SIP – Self-Paced Online with Support

Duration & Delivery
  1. Course Duration: 8 weeks (140 hours)
  2. Format: Self-Paced Online with Support (narrated lessons, readings, quizzes, and role-based tasks).
Key Learning Objectives

   By completing this program, learners will:

  2. Understand how AI technologies enhance pharmacovigilance efficiency.
  3. Learn about automation in ICSR intake, triage, and case assessment.
  4. Explore NLP for adverse event narrative writing and literature monitoring.
  5. Gain knowledge of AI-assisted MedDRA/WHO-DD coding.
  6. Apply ML techniques for signal detection and benefit–risk analysis.
  7. Explore how AI integrates with Argus, ArisG, and other safety databases.
  8. Review regulatory expectations for AI in PV (ICH-E2B(R3), FDA, EMA).
  9. Study case examples of AI implementation in global PV operations.
Who Should Take This Course
  1. Drug Safety Associates / Specialists expanding into AI-enabled PV.
  2. Medical Reviewers seeking AI tools for narrative and risk evaluation.
  3. Clinical Data Managers working with PV databases.
  4. Data Scientists / Analysts moving into life sciences and drug safety.
  5. Career changers preparing for PV and AI-integrated safety roles.
Benefits & Outcomes
  1. Build practical skills in AI-enabled pharmacovigilance.
  2. Automate key PV tasks – ICSR handling, coding, narratives, reporting.
  3. Improve readiness for AI-integrated PV roles in pharma and CROs.
  4. Strengthen employability in global pharmacovigilance and regulatory operations.
  5. Position yourself as a specialist in the future of intelligent PV systems
Career Pathways: After completing this course.
  1. AI-Enabled Pharmacovigilance Specialist
  2. Drug Safety Data Scientist
  3. Signal Detection Analyst
  4. Medical Reviewer (AI-assisted)
  5. PV Operations Lead / Manager

Curriculum & Modules

Modules
1. Introduction to AI in Pharmacovigilance

2. AI in ICSR Processing – Intake, Triage & Case Workflow

3. Natural Language Processing (NLP) for Narratives & Literature Mining

4. AI-Assisted MedDRA & WHO-DD Coding

5. Signal Detection & Risk Management with Machine Learning

6. Predictive Analytics in PV – Safety Trends & Risk Forecasting

7. AI-Enabled PV Databases (Argus, ArisG, Veeva Safety)

8. Regulatory Compliance – ICH, FDA, EMA, GDPR, HIPAA

9. Case Studies – AI Applications in Pharma & CRO PV Teams

10. Future Trends – Digital Pharmacovigilance & AI-Driven Safety
Getting in Touch:

For more information, please call us at +91 8925971788 / +91 8977943100 (WhatsApp)or email qpdc@qtechelearncenter.com. Our course specialists will reach out to you promptly to assist you in taking the next steps toward your career goals.