cGMP Analytical Methods and Validation

Length: 2 Days

This training course provides a comprehensive understanding of current Good Manufacturing Practices (cGMP) for analytical methods and validation in the pharmaceutical industry. Participants will learn essential principles and practices to ensure compliance with regulatory requirements and to develop reliable analytical methods for drug quality control.

Learning Objectives:

  • Understand the regulatory framework of cGMP for analytical methods and validation.
  • Learn the principles and practices of method validation and verification.
  • Gain knowledge of analytical method development and optimization techniques.
  • Explore the critical parameters and considerations for analytical method transfer.
  • Understand the role of analytical instruments in cGMP compliance.
  • Learn strategies for managing deviations and maintaining data integrity in analytical testing.

Audience: This course is designed for professionals working in the pharmaceutical, biotechnology, and related industries, including:

  • Quality assurance and control personnel
  • Analytical chemists
  • Regulatory affairs professionals
  • Research and development scientists
  • Compliance officers

Course Outline:

Module 1: Regulatory Overview

  • Introduction to cGMP regulations for analytical methods
  • Regulatory expectations for method validation and verification

Module 2: Method Validation Principles

  • Key concepts and principles of method validation
  • Validation parameters and acceptance criteria

Module 3: Analytical Method Development

  • Strategies for method development and optimization
  • Considerations for robustness and ruggedness testing

Module 4: Method Transfer

  • Critical parameters and documentation for method transfer
  • Challenges and best practices in method transfer processes

Module 5: Instrumentation and Compliance

  • Role of analytical instruments in cGMP compliance
  • Calibration, qualification, and maintenance of analytical instruments

Module 6: Data Integrity and Deviation Management

  • Strategies for maintaining data integrity in analytical testing
  • Procedures for managing deviations and out-of-specification results