TetraScience, the scientific data and AI company, today unveiled its Scientific AI Lighthouse (SAIL) program, designed to transform biopharma R&D and manufacturing in the era of AI. Takeda joins as the founding partner, gaining first-mover access to TetraScience’s AI and data capabilities to accelerate drug discovery, reduce CMC cycle times, and boost scientist productivity through agentic AI.
For decades, pharmaceutical R&D has been hampered by fragmented datasets, manual processes, and bespoke workflows that fail to scale. The SAIL program addresses these challenges through four integrated elements:
Scientific Data Foundry
This component deconstructs proprietary vendor datasets into atomic units—experimental measurements, metadata, and instrument telemetry—structured in AI-native schemas, taxonomies, and ontologies. The approach future-proofs data, enhances compliance, and enables federated sharing across ELNs, LIMS, IoT, and robotics.
Scientific Use Case Factory
By productizing AI-enabled workflows, the Factory allows hundreds of common R&D and manufacturing processes to be standardized, repeatable, and configurable. These AI-driven use cases are made broadly available to the biopharma industry, creating an industrialized approach to scientific innovation.
Tetra AI
Tetra AI provides semi-autonomous and fully autonomous agentic capabilities, helping scientists navigate complex, multi-step processes. The AI identifies relevant data across experiments, uncovers patterns missed by manual workflows, and synthesizes vast inputs in parallel, enabling faster, more confident decision-making.
Sciborgs
TetraScience deploys “Sciborgs”—scientist-engineers embedded with client teams—to drive cultural and operational transformation, ensuring sustainable adoption of AI-enabled workflows.
Together, these elements create a scientific innovation flywheel: refined datasets improve workflow fidelity, use cases feed back into Tetra AI, and ontologies compound across domains—accelerating discovery and R&D productivity.
“Embedding AI and digital technologies across the R&D value chain is a core strategic area for our future,” said Nicole Glazer, Head of R&D Data, Digital and Technology at Takeda. “Our data-driven approach reduces discovery timelines, identifies targets faster, and helps design better therapeutic candidates.”
Patrick Grady, CEO of TetraScience, added, “By industrializing AI-native scientific data and workflows, we can bend the curve on Eroom’s Law—accelerating discovery, shrinking cycle times, and expanding what science can achieve. Our SAIL partnership with Takeda is a model for the industry’s future.”
The SAIL program signals a major shift toward AI-driven, scalable, and fully integrated R&D in biopharma, promising higher productivity, faster insights, and more reliable drug discovery outcomes.
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