Drug Regulatory Affairs (DRA) Using Machine Learning

18–20 Hours | Certification Program | Minimum Batch Size: 50+ Students

🌟 Course Overview

The pharmaceutical industry is rapidly shifting towards digital transformation, and Drug Regulatory Affairs (DRA) is no exception. This 18–20 hour certification program is designed to equip students with a strong understanding of global drug regulations combined with the power of machine learning applications.

This course blends regulatory frameworks, documentation, compliance requirements, and AI-driven automation techniques to prepare learners for modern, tech-enabled roles in the regulatory sector.

Ideal for:
🎓 Biotechnology, Pharmacy, Life Sciences, Microbiology, Chemistry students (UG/PG)
💼 Freshers looking to enter pharma & regulatory careers
🧑‍🔬 Professionals seeking to upskill for DRA roles in the AI era

🎯 Key Learning Outcomes

By the end of this program, learners will be able to:

Understand foundational concepts of Drug Regulatory Affairs.

Learn global regulatory systems: USFDA, EMA, CDSCO, WHO.

Prepare and manage regulatory submissions.

Work with essential documents: CTD, ACTD, Module 1–5, labeling, and dossiers.

Use Machine Learning concepts to analyze regulatory data.

Build simple ML models for:

Document classification

Risk prediction

Compliance automation

Regulatory decision support

Explore real-world regulatory datasets.

Understand how AI tools are transforming global DRA processes.

Become job-ready for modern Regulatory Affairs profiles.

📚 Course Curriculum (18–20 Hours)

Module 1: Introduction to Drug Regulatory Affairs

Basics of DRA

Regulatory bodies worldwide

Drug approval pathways

IND, NDA, ANDA process

Module 2: Regulatory Documentation

CTD & ACTD structure

eCTD submissions

Dossier preparation

Quality, Non-clinical & Clinical data

Module 3: Overview of Machine Learning

What is ML?

Supervised & Unsupervised learning

Data preprocessing basics

Use of ML in documentation & compliance

Module 4: ML in Regulatory Submissions

Building text classification models for regulatory docs

AI for label comparison

Predictive analytics for compliance risk

Case studies from global industries

Module 5: Hands-on Practical Sessions

Working with regulatory datasets

Building a simple ML model using Python

Automation of regulatory workflow

Practical exercises & mini-project

Module 6: Career Pathways & Industry Expectations

Job roles in Regulatory Affairs

AI-powered regulatory job opportunities

Resume building + interview guidance

🎁 Benefits of the Course

Industry-Relevant Knowledge: Learn current regulatory practices used by global pharma companies.

Tech Integration: Understand how machine learning is reshaping regulatory systems.

Hands-on Training: Work on practical datasets and ML projects.

3-Level Certification: Completion certificate + project certificate.

High Employability: Prepares students for Regulatory Associate, DRA Analyst, ML-Assisted Regulatory roles.

Placement Support: Assistance with internship & job opportunities.

Expert Faculty: Delivered by industry professionals in RA + AI/ML.

Recorded Access: Students get recordings for revision.

📈 Why Offer This Course to Your Students?

High-demand skillset combining Life Sciences + AI + Regulatory

Enhances departmental academic strength

Boosts student employability and placement numbers

Perfect for NAAC, NIRF & Accreditation skill-based activities

Practical, project-driven learning experience

Minimum batch size of 50+ students ensures affordability and institutional collaboration

📜 Certification

After completing the course, students receive:
✔️ Course Completion Certificate
✔️ ML Project Certificate
✔️ Regulatory Affairs Training Certificate

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📞 Contact for Institutional Collaboration

For college departments (Pharmacy, Biotechnology, Life Sciences, Chemistry, Microbiology, etc.)
We offer this training directly on campus or online with complete support.