Cloud Labs: Providing the Infrastructure to Enable AI/ML in Pharmaceutical Research and Development

Description:
In some fields, AI/ML tools have begun to demonstrate their value in a variety of practical applications. In the area of analytical science, and more broadly laboratory research, these tools have not made the same kind of impact or ubiquity. One of the biggest reasons why this has lagged in this area is the lack of infrastructure and standardized ontology, which makes the barrier between data science and laboratory science hard to bridge. This is particularly true for open ended research, where a scientist is investigating a new idea and can’t predefine the model parameters they will need in the future. As a byproduct of how they operate (ensuring the scientist completely defines their experiment up front), cloud labs create a unique environment where every step of the process and every resulting data is fully captured and organized, allowing AI/ML tools to interact with physical experimentation more readily. In this discussion, we will overview specific use cases as well as the future development aimed at making AI/ML tools much more useful in the day-to-day of scientific research.

Speaker: Ben Kline - Emerald Cloud Lab