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Bruker, Noetik Expand Collaboration, Advance Foundational Models for Therapeutics Applications

The announcement follows a study of more than 3500 patient samples with the CosMx imager.

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By: Patrick Lavery

Content Marketing Editor

Bruker Spatial Biology, a division of Bruker Corporation, and Noetik are expanding a collaboration involving foundational models for therapeutics applications.

More specifically, the expansion follows a study of more than 3500 patient samples with Bruker’s CosMx Spatial Molecular Imager (SMI).

How Bruker and Noetik Work Together

As Bruker explains, CosMx SMI powers Noetik’s pre-training and scaling of bio-foundation models. In turn, those models are then able to perform complex, genome-wide simulations of human biology at cellular- and tissue-level.

Ultimately, this process results in the enabling of applications across a wide swath of therapeutic areas.

Bruker’s spatial biology portfolio, taken collectively, supports high-fidelity data generation for discovery as well as translational research. With Noetik imaging thousands of additional patients with the CosMx whole transcriptome assay, the expanded collaboration builds on that portfolio.

Collaboration Combines AI and Therapeutics

Not only that, but the imaging done by Noetik will train its world models that learn from human tissue data.

Noetik co-founder and CEO Ron Alfa, MD, PhD, said his company’s models exhibit clear scaling laws.

“Spatial context is necessary for training foundation models that truly learn human biology,” Alfa said. “As we ingest more high-resolution CosMx data, we see a predictable and powerful increase in the models’ ability.”

“Noetik’s multiple spatial AI models … represent transformative breakthroughs for tackling human disease,” said Mark Munch, PhD, President, Bruker NANO.

One noteworthy component regarding the CosMx SMI platform is how Noetik is able to leverage it to develop self-supervised AI. With this artificial intelligence backing, the collaboration can generate some of the largest datasets in oncology.

Bruker says these datasets are also the most biologically complete in terms of single-cell and subcellular spatial transcriptomics and multiomics.

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