Did you miss last week’s inaugural SLAS AI in Process Automation Symposium in Boston? Bummer! We hope to see you next year, but until then, here’s a quick recap of all the learning (and fun!) we had this past week.
To kick off the two-day event, our illustrious keynote speaker, Alán Aspuru-Guzik, Ph.D., (University of Toronto) led us on a humorous, dance music-infused tour of his lab’s progress towards open-source cheminformatics platforms, closed-loop automation and the quest to build new materials, the way other groups develop pharmaceuticals. Aspuru-Guzik raised a theme we heard throughout the conference: using AI / ML and robotics as a force multiplier to push ahead solutions to pressing problems like energy storage and precision medicines.
Day one featured speakers in drug discovery, data automation and (a first for SLAS!) a lightning session of short talks in diverse fields. Design-Make-Test-Analyze cycles and Amazon Web Services (AWS) utilities abounded, just about everyone explore how other organizations in the life sciences space handled their automation and deep learning challenges. Attendees learned about virtual models, grooming data on its way into repositories and how to scale up dramatically without increasing headcount. And it wasn’t all just pharma – battery capacitance degradation in cell phones, global instrument monitoring and checking machines’ work also took center stage.
At night, after the servers were shut down and the robots stopped, these AI trailblazers were treated to sliders, lobster rolls and cheese plates while a variety of competitive board games and classic Xbox hits were offered during the onsite reception.
Day two’s discussions shifted to specific impacts in image analysis and screening, followed by chemistry workflows in the afternoon. Counting stem cells was compared to playing the classic “How many jellybeans?” game played in school fundraisers everywhere. Phenotypic screening based on image recognition and feature separation led to amazing AI-powered revelations in drug mechanisms of action, especially at smaller firms. Likewise, the promise of the keynote speaker’s fully closed-loop processes was realized in our chemistry session, where groups from big pharma to plucky academics optimized reactions and assays alike without human intervention.
Finally, we’d be remiss if we didn’t note our own feedback loops – SLAS got good, actionable topics and interests at our lunchtime roundtables to make next year even better, and we’re still listening to attendees and speakers through our post-event evaluation. We look forward to seeing you back in Beantown September 2-3, 2020.