AI/ML in Regulated Life Sciences (GxP) Sectors – Operation Phase: Maintaining a State of Control
Complimentary
Learning Level: Intermediate
Time: 1000 - 1130 EDT
Session Length: 1.5 hours
Guiding the pharmaceutical and medical device industries to successfully transition into the era of AI/ML and more generally Pharma 4.0, the presenters will provide tangible insights derived from GAMP and quality perspectives to ensure patient safety, product quality, and data integrity. We will build on the foundations presented in the first four webinars (a) business need and risk assessment, b) considerations on data sets and representativeness, c) iterative training, fine-tuning, and learning, and d) computerized system integration and acceptance by discussing operation of an AI-enabled system in a regulated GxP sector and how to maintain a state of control, e.g. by implementing an ongoing monitoring program.
This webinar will describe how AI-enabled systems can be operated in regulated GxP sectors while maintaining a state of control. Implementing and training of AI-enabled systems is challenging, and so is the validation process. However, the challenges do not end with successful deployment: How to implement effective ongoing monitoring? How to handle changes and updates; in general, how to manage multiple versions and configurations of an AI-enabled system? And what specifics are recommended for incident and problem management or any resulting corrective and preventive actions (CAPA)?
This webinar will introduce critical activities during the operation phase and focus on performance monitoring measures. In addition, it will highlight how these aspects interact with other activities to establish control loops, e.g. with the project phase.
The goal of this webinar is to introduce best practices for ongoing monitoring to maintain a state of control for the operation of AI-enabled systems in regulated GxP sectors to ensure patient safety, product quality, and data integrity.
Learning Objective
- Provide a brief overview of critical activities during the operation of AI-enabled systems in regulated GxP sectors with a focus on performance monitoring.
- Introduce the specific aspects of standard practices like change and configuration management or incident and problem management for AI-enabled systems.
- Explain how to maintain an AI-enabled system under control when being operated in regulated GxP sectors – starting from deployment and including thorough planning for business continuity.
