Nicolas Triballeau | Director, Drug Discovery - Chemistry
Revvity Signals Software Inc

Day 1: 27th May @ 12:20

AI Operational Excellence in Drug Discovery: Turning Models-as-a-Service into Actionable Science

Operationalizing artificial intelligence in medicinal chemistry requires closing the gap between computational models and experimental workflows. Revvity’s Signals Xynthetica™ embeds AI models directly into the environment where scientific data is captured and analyzed, creating a continuous learning loop that improves predictions over time. As a Models-as-a-Service platform, it delivers in-silico design and property prediction alongside real-world validation, without requiring organizations to build or maintain complex AI infrastructure. Through a strategic collaboration with Eli Lilly, Signals Xynthetica now provides access to Lilly TuneLab™ models, trained on extensive proprietary research data, via privacy-preserving approaches, democratizing high-value predictive capabilities for discovery teams. For medicinal chemists, this operationalizes AI-augmented discovery at scale, accelerating design cycles for both traditional small molecules and emerging modalities while maintaining robust governance and scientific rigor. 

Nicolas Triballeau, Director, Drug Discovery - Chemistry, Revvity Signals Software Inc

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Nicolas Triballeau / AI Operational Excellence in Drug Discovery: Turning Models-as-a-Service into Actionable Science

Nicolas Triballeau, Director, Drug Discovery - Chemistry,
Revvity Signals Software Inc

Nicolas Triballeau is the Drug Discovery Chemistry Lead at Revvity Signals. With 17 years of experience in drug discovery, he has not only provided direct project support and led teams but has also played a significant role in establishing scientific standards and ontologies. Nicolas holds a...

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