InstructorRoyed Training
TypeOnline Course
Price$120 / 10440 INR.
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data integrity training in pharma

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Data Integrity Pharmaceutical Training Course

Data integrity online training course is provide basic fundamental know-how about data integrity issues of pharma, biopharma and medical devices companies. This online course will help to understand the concept of data integrity, interpreting expectations of regulatory agencies. Moreover, the course helps to understand major data integrity issues practically to avoid future mistakes.

This interactive online certification course empowers professionals to grasp the fundamentals of data integrity, master AI-driven practices, and apply practical solutions to ensure compliance and avoid costly mistakes. Special emphasis is given to Audit Trail Management, a core focus area in recent regulatory inspections.

Data Integrity + AI = Compliance Confidence | Master audit trails, governance & AI-driven integrity checks.

Data Integrity is gaining importance day by day in the pharmaceutical, biopharmaceutical and medical devices industry. In cGMP, with both the FDA and European Regulatory Agencies placing a high degree of focus on the subject. This online course will help to understand the concept of data integrity, interpreting expectations, understanding major data integrity issues practically to avoid future mistakes. Course is also focused in detail regarding audit trail.

Learning Objectives:

  • Understand the importance of data integrity in pharmaceutical and biopharmaceutical industry
  • Impact of data integrity issues in pharmaceutical industry
  • Know how to integrate data governance into your quality systems
  • Exposure to practical areas of data integrity
  • Understand the difference between mistakes and falsification or fraud
  • Principle of data integrity management
  • Be able to identify the data lifecycle elements for both manual (paper) and electronic data
  • Understand the potential risks and weaknesses associated with the lack of control of data
  • Know how to incorporate the aspects of data integrity into the design and qualification of new equipment

Course Snapshots

  • Course Code: RYD-033
  • Title of the course: Fundamental Training on Data Integrity in pharmaceutical, Biopharmaceutical and Medical Devices industry.
  • Nature of the course: Online distance learning course. Therefore the course can be accessed online across anywhere 24×7.
  • Duration: 3 Days Microlearning Course.
  • Eligibility: Graduation in any discipline. Even the final year student can join the course.
  • Course Certificate: Certificate will be provided at the end of the successful completion of the course.

Key training areas

  • Understand the importance of data integrity in regulated industries
  • Recognize the impact of DI issues on compliance, product quality, and patient safety
  • Integrate data governance into Quality Systems effectively
  • Gain exposure to practical DI problem areas and learn to mitigate risks
  • Distinguish between human error vs. falsification or fraud
  • Apply the principles of Data Integrity Management (ALCOA+ and ALCOA++)
  • Identify data lifecycle elements for both manual (paper) and electronic records
  • Spot risks and weaknesses linked to poor data control
  • Incorporate data integrity aspects into equipment design & qualification
  • Explore the role of Artificial Intelligence in enhancing DI compliance

Key features of the course

  • AI-Integrated Training: Learn how Artificial Intelligence can transform DI monitoring & reporting
  • Hands-On Focus: Practical exposure to real-world DI issues & case studies
  • Audit Trail Mastery: Deep dive into audit trail design, review & compliance expectations
  • Global Compliance Insights: Align with FDA, EMA, MHRA & other key agency requirements
  • Flexible eLearning: 100% online, self-paced learning with 24×7 access
  • Certification: Royed Training Certificate upon successful completion

Who will Benefit:

  • Person working in the pharmaceutical manufacturing department / F&D personnel
  • Regulatory Affairs personnel
  • Research and Development personnel
  • Quality Assurance & Control personnel
  • Development and Preparation of Submission Materials
  • Strategic management personnel
  • Personnel who involved in internal audit.

Section 1Lecture sessions
Lecture 1Data Integrity issues in Pharmaceutical Industry
Lecture 2Establishment Inspection Report | 483 Observations | USFDA Warning Letter | Handling of FDA inspection | Closing of Warning Letter 
Lecture 3Electronic Batch Record for effective compliance management | Key Understanding | Functionalities | Importance in managing data integrity
Lecture 4RTQs
Section 2AI and Data Integrity
Lecture 5Introduction to AI
Lecture 6Basics of AI ML DL | Key Differences | Application in industry
Lecture 7Types of AI
Lecture 8AI Project | Overview
Lecture 9Comprehensive Training on AI Project | Managing Stages | AI Iteration 
Lecture 10How machine learning
Lecture 11Understanding Regulatory Affairs – Traditional vs. Digital | 2 Case Study
Lecture 12Basics of AI for Regulatory Professionals | Understanding different models used in RA | Case Study | Simulation
Lecture 13AI Terms with Regulatory Significance | Regulatory Applications
Lecture 14Structured Vs. Unstructured Data | Practical Understanding | Explore Patient Datasets
Lecture 15Data Grouping with Unsupervised Learning | Case Simulation | Hands on Exercise
Lecture 16Quality Data and Bias | Bias in datasets | Different Types of Bias in Pharma Datasets 
Lecture 17AI Data Quality Standard | Checklist
Lecture 18Download AI Data Quality Checklist
Lecture 19Sample Data Exercise | Data error | Data Refinement and Cleaning of the data 
Section 3Data Integrity Action Plan
Lecture 20Exercise 1
Lecture 21Exercise 2
Lecture 22Exercise 3
Section 4Request for Course Certificate