Complimentary
Learning Level: Basic
Time: 1000 - 1130 ET
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. Building on the foundations presented in the first five webinars (a) business need and risk assessment, (b) considerations on data sets and representativeness, (c) iterative training, fine-tuning, and learning, (d) computerized system integration and acceptance and (e) maintaining a state of control - ongoing monitoring we will discuss supporting processes to support an AI-enabled computerized system in a regulated GxP area, including its three main components as per GAMP 5 Second Edition: Risk management, data governance, and change management.
While some aspects of supporting processes have been discussed in previous webinars, this episode will take a horizontal perspective, connecting the dots throughout the life cycle of an AI-enabled computerized system, from early concept and design to operation of the system. In addition, organizational and technical aspects like roles and responsibilities are discussed, supporting the use of AI and ML in regulated areas from a wider perspective. Key questions covered in this webinar include how risk management stays in sync with new insights as new data is generated, how organizations can manage and govern data to support wider adoption of data-driven approaches, and best practices on managing changes throughout the life cycle in connection with agile approaches.
The goal of this webinar is to introduce provide a holistic view on supporting processes, demonstrating their critical role in achieving high-quality AI-enabled computerized systems, their integrated nature and practical and organizational aspects in successfully implementing these processes.
Learning Objectives
- The goal of this webinar is to introduce provide a holistic view on supporting processes, demonstrating their critical role in achieving high-quality AI-enabled computerized systems, their integrated nature and practical and organizational aspects in successfully implementing these processes.
- Provide a horizontal perspective of risk management, data governance and change management throughout the life cycle.
- Show how organizational aspects support effective and efficient supporting processes, such as roles and responsibilities, agile frameworks and the use of tools.
