Executive Director, Head of Regulated Bioanalysis Operations Bristol-Myers Squibb Princeton, New Jersey
Artificial Intelligence (AI) is making significant advancements across various sectors, including pharmaceutical research, driven by large language models and machine learning. Although AI is still in its early stages within the regulated bioanalytical environment, there are numerous opportunities for engagement. This presentation aims to provide foundational knowledge of AI and machine learning in a clear and accessible manner for an audience without a background in computer science. The discussion will cover the following topics: 1): What AI is and how it differs from machine learning 2): Various AI models 3:) General approaches to using AI in bioanalytical laboratories Additionally, the presentation will offer a vision of the future where AI and machine learning are integrated into regulated laboratories. It will also include two examples of current research approaches utilizing AI in regulated bioanalytical science.
Learning Objectives:
Review current research examples of AI applications in regulated bioanalytical science.
Envision the future integration of AI and machine learning in regulated labs.
Explore general approaches to implementing AI in bioanalytical laboratories.
Identify various AI models and their applications.
Understand the basics of AI and its distinction from machine learning.
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