Artificial Intelligence Learning algorithms validation in the context of GxP

Introduction

Artificial intelligence (AI) and machine learning (ML) systems have a revolutionary potential for many industries, including the pharmaceutical and medical device sectors. These systems can analyze large amounts of data, identify patterns and trends, and make predictions or support making decisions that can help improve patient outcomes and streamline operations. In particular, a few examples of applications of AI/ML can be found in: 

• Manufacturing: Data analytics and process improvement, real-time batch release, Automated Quality inspections (e.g. tablets inspections). 
• Pharmacovigilance: Automated adverse events monitoring. 
• Research: Drug-discovery, population selection and stratification.  
• Medical Devices: Computer vision-based automated diagnostics. 

However, with the increasing reliance on AI and ML in these fields, it is crucial to ensure that these systems are validated and operate as intended. That is also why in the Second Edition of the GAMP 5 Guide “A Risk-Based Approach to Compliant GxP Computerized Systems, the Appendices have been expanded to encompass these new and evolving concepts, which are having a considerable impact on the entire life science sector.