The promise of Artificial Intelligence in biotechnology and pharmaceuticals is immense, from accelerating drug discovery to optimizing clinical trials and enhancing manufacturing.  Realizing this potential within highly regulated environments demands more than just innovative algorithms; it requires a robust design qualification framework in support of process validation.

Join us for this essential webinar with Jason Dow—a recognized expert on critical topics such as Computer Software Assurance, Data Integrity, and qualification/validation strategies for next-generation technologies such as AI—where we will delve into a practical design qualification (DQ) approach to demonstrating your AI models utilized in validated processes are designed effectively and meet the stringent requirements of regulatory agencies.

In this 1-hour webinar, you will learn:

1. The critical role Design Qualification (DQ) plays in establishing confidence and trustworthiness in AI models.

2. How DQ of AI models fits within the larger umbrella of process validation.

3. Practical steps you can take to document the critical elements of your AI model designs to support DQ.

4. Techniques to accelerate adoption of AI models within validated processes; leverage DQ and SDLC effort to confidently deploy AI innovation.

5. Common challenges and pitfalls for regulated use of AI and how to navigate them. 

Who should attend?

This session is tailored for IT professionals, Quality Assurance specialists, and data scientists navigating the complexities of AI adoption in GMP regulated spaces.