AI/ML in Early Drug Discovery: From Data to Decisions (Hybrid Colloquium) • BioSolveIT

We invite biotech/pharma investors, VCs, computational chemists, and medicinal chemists.
Join Congruence Therapeutics for a focused industry colloquium exploring practical AI/ML workflows in early small molecule drug discovery. This event brings together experts to discuss how AI/ML is being applied in real discovery programs today, separating real impact from platform hype.

In-person participation (Request): Limited to 40 participants. Requests are handled (a) by invitation or (b) on a first-come, first-served basis, with a preference for diverse representation rather than multiple attendees from the same organization.

Online attendance: Available if preferred or once in-person capacity is reached.

Montreal, QC & Online

February 9, 2026

Presentations: 1:00 PM to 5:00 PM (EST) / 7:00 PM to 11:00 PM (GMT+1)

Location: MILA Co-working Space

Mila – Quebec Artificial Intelligence Institute, 6650 St-Urbain, Montreal [Maps]

Event Description

AI and machine learning are now embedded across early drug discovery, but distinguishing actionable workflows from industry noise remains a challenge. This colloquium explores the narrative arc from Hype to Fundamentals, moving through Data/Informatics and Molecules/Physics to reach solid Decisions.

The program is delivered through four invited presentations featuring scientists from Congruence Therapeutics, BioSolveIT, and Chemical Computing Group (CCG), followed by an informal networking reception.

Featured Presentation: BioSolveIT

Beatriz Büschbell, PhD will present: “AI Needs Molecules: Turning Real Chemical Space into Actionable Drug Discovery Data”

In this session, Dr. Büschbell will guide us through the critical transition from raw data to physics-grounded real chemistry. Key takeaways include:

The “Infinite Space” Myth: Why unconstrained chemical space misleads AI, and how feasibility constraints enable better learning.
Defining Real Space: Focusing on synthesizability and tractability to create reaction-aware, chemistry-grounded enumeration.
Physics Grounding: Utilizing structure-based methods to turn vast spaces into learning-ready datasets.
Chemistry to Decisions: How AI acts as a consumer of chemistry to reduce false positives and drive actionable decisions.

General Topics of the Colloquium

AI/ML fundamentals for early drug discovery (AI/ML 101).
AI/ML Toolchains and workflows used in practice across discovery organizations.
Walking through the story arc: Hype to Fundamentals to Data/Informatics to Molecules/Physics to Decisions.
Invited presentations featuring scientists from Congruence Therapeutics, BioSolveIT, and Chemical Computing Group (CCG).

Looking forward to seeing you at the colloquium!