Data Integrity & ALCOA+ in Pharma -Practical Approach

Descripción

Are you working in Pharma and afraid of audits, deviations or data integrity issues? This course shows how QA professionals handle ALCOA+ requirements in real GMP situations. Data Integrity is one of the most critical and most inspected topics in the pharmaceutical industry today. Regulatory authorities such as FDA, EMA and MHRA expect companies not only to understand ALCOA+ principles, but to apply them consistently across daily GMP activities. This course provides a practical, real-life approach to Data Integrity and ALCOA+, based on real QA, QC, laboratory and computerized system experience - not theory alone. You will learn how Data Integrity principles are applied throughout the entire data lifecycle: from data generation, recording and processing, through review, approval, audit trail review, archiving and inspection readiness. The course explains how Data Integrity applies to paper records, electronic systems and hybrid processes, with clear examples from laboratories, manufacturing environments and computerized systems. Special focus is given to common Data Integrity failures, how regulators identify them during inspections, and how organizations are expected to respond. You will understand how to recognize early warning signs, how to document issues correctly, and how to manage deviations, investigations and CAPA related to Data Integrity. The course also covers data governance, roles and responsibilities, audit trail review, data review practices, and inspection-ready documentation, aligned with GMP expectations and regulatory guidance. This course is designed to help you think like an inspector, understand regulatory logic, and confidently apply Data Integrity principles in your daily work — whether you work in QA, QC, laboratories, manufacturing or computerized systems.

Lo que aprenderás

• Understand ALCOA and ALCOA+ principles and how regulators apply them in real GMP inspections.
• Identify Data Integrity risks across the full data lifecycle (generation, processing, review, archiving)
• Apply Data Governance concepts to paper, electronic and hybrid systems in GxP environments
• Detect common Data Integrity failures using real-life QC, manufacturing and computerized system examples
• Perform effective data review and audit trail review aligned with FDA, EMA and Annex 11 expectations.

Requisitos

• Basic understanding of GMP or GxP is recommended but not mandatory.
• No prior Data Integrity expertise is required – all concepts are explained step by step using real examples.