BAGIM is an active community of Boston area scientists bringing together people from diverse fields of modeling and informatics to impact life and health sciences. BAGIM strives to create a forum for great scientific discussions covering a wide range of topics including data management, visualization, computational chemistry, drug discovery, protein structure, molecular modeling, structure-based drug design, data mining, software tools, and the sharing of goals and experiences. Our community is made up of participants from academia, government, and industry whose goal is to engage in the discussion of science involving a synthesis of theory and technology. Discussions sponsored by BAGIM are targeted to the needs and interests of informatics scientists, computational chemists, medicinal chemists, and statisticians. BAGIM also provides opportunities for networking within these disciplines as well as an arena for the dissemination of information of specific interest to the membership.

Wednesday, February 1, 2023

Eric Sigel - Exploring Predictive Workflows in Small Molecule Discovery through DEL-ML

BAGIM is excited to announce our first in-person event of 2023. We are partnering with TandemAI on this event with invited speaker Eric Sigel.

Date: March 1, 2023

Time: Event time: 5:30 - 7:30PM - Talk promptly starts at 6 pm ET with Q&A immediately afterwards. Please arrive no later than 6 pm.

We will be serving complimentary drinks and refreshments.

Sign-up: BAGIM Meetup

Location: The Royal Sonesta, Riverfront Room - East Tower, Level 2, 40 Edwin Land Blvd., Cambridge, MA 02142

TitleExploring Predictive Workflows in Small Molecule Discovery through DEL-ML

AbstractAI/ML has rapidly moved from being a curiosity to center stage across the biotech industry. Novel approaches are being enabled by these new methods and the increasing ability to generate the large-scale data needed to drive the technology. However, the impact of these rapid advances is limited by an industry that is only beginning to adapt to the new paradigm. The presentation will use DEL-ML (Machine Learning on DNA Encoded Library data) to explore the predictive workflow including results of its application, needed shifts in the small molecule discovery mindset, and directions where the technology can move from here.

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