TetraScience , the scientific data and AI company, launched its Scientific AI Lighthouse (SAIL) program with Takeda as a founding partner. This program introduces a new model to transform biopharmaceutical R&D and manufacturing in the era of AI.
As a founding partner of SAIL, Takeda will have first access to TetraScience’s full range of data and AI capabilities to accelerate AI-assisted drug discovery, reduce CMC cycle times, enable in silico modeling, and increase scientist productivity through the use of agent-based AI. The program aims to enable biopharmaceutical companies to bring more products to market at lower cost and risk by increasing productivity and improving candidate quality.
For decades, productivity in pharmaceutical research and development has been limited by highly fragmented data sets, customized workflows, manual processes, and one-off project approaches that couldn’t be scaled. TetraScience’s SAIL model offers a fully integrated set of capabilities specifically designed for the AI era that directly addresses these challenges:
Scientific Data Foundry
decomposes scientific data captured in proprietary vendor silos into atomic units (experimental measurements, metadata, derived results, instrument telemetry). These units are organized into AI-proprietary schemas, taxonomies, and ontologies, and then prepared for reuse, continuous improvement, and collaborative sharing. This future-proofs biopharmaceutical data against vendor lock-in in a rapidly evolving landscape of ELNs, LIMS, instrumentation, IoT, and robotics, while improving compliance and audit readiness.
Scientific Use Case Factory:
Productization and mass production of AI-enabled use cases and workflows by combining AI-native data from the Foundry into standardized, repeatable, and configurable processes. Hundreds of common scientific use cases across the entire R&D and manufacturing value chain will be deployed within the SAIL program and then made widely available to the biopharmaceutical industry.
Tetra AI
offers semi- and fully autonomous agent capabilities that help scientists navigate complex, multi-step processes in research and development. Tetra AI proactively identifies and delivers the most relevant data from diverse experiments, explores broad chemical and biological domains, uncovers patterns missed by manual workflows, and synthesizes large amounts of input in parallel to make faster and more confident decisions.
Sciborgs:
To ensure successful implementation and change management, TetraScience deploys teams of scientists and engineers – Sciborgs – who work at the intersection of science, data, and AI. Sciborgs accelerate cultural and operational transformation by embedding themselves within client teams and ensuring a sustainable adoption of Scientific AI.
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Together, these four elements form a self-reinforcing cycle of value creation: Every dataset refined in the Foundry increases the accuracy of future workflows; every use case created in the Factory feeds into Tetra AI; and every new ontology connects workflows and domains. The result is a scientific innovation flywheel more usage generates better data, leading to higher-quality insights, which in turn enable new, more powerful use cases.
“Integrating AI and digital technologies across the entire R&D value chain is one of Takeda’s core strategic areas for our future,” said Nicole Glazer, Head of R&D Data, Digital and Technology at Takeda. “Our data-driven R&D approach will shorten discovery times, enable faster target identification, and help us develop better therapeutic candidates.”
“By transforming how our scientists access, analyze, and share research data, we are unlocking new levels of productivity and enabling AI-powered insights through a connected online data environment,” said Jim Villa, global head of research strategy and operations at Takeda. “We are not only increasing productivity but also driving innovation by leveraging data and agent-based AI to integrate information more quickly, uncover new relationships, define better hypotheses, and accelerate innovation in our drug discovery efforts.”
“For decades, the pharmaceutical industry has lived under the shadow of Eroom’s Law the observation that drug development costs double approximately every nine years,” said Patrick Grady, CEO of TetraScience. “By evolving the industry from non-scalable, bespoke data projects and workflows to productive and industrialized AI-native scientific data and AI-powered workflows, we can help bend the curve of Eroom’s Law, accelerating discovery, shortening cycle times, and pushing the boundaries of what science can achieve. Our SAIL partnership with Takeda is a model for the future of the industry.”
Source: PRNewswire
