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Scaling agentic AI systems across R&D use cases
R&D teams often work in silos prototyping AI capabilities for narrow use cases Prototypes and pilots are very fit for purpose and often do not share architectures even for similar use cases In this talk, we'll discuss what layer of AI infrastructure is common across use cases in drug development and what concepts can remain similar but still enable fit-for-purpose solutions Specific examples from content generation and insight generation will be used to highlight the reusability of AI platform elements
