Imagene AI Announces Collaboration with Daiichi Sankyo to Advance Multimodal Biomarker Discovery in Oncology

Collaboration leverages Imagene’s OI Suite, powered by CanvOI and a large-scale multimodal real-world data lake, alongside Composite Continuous Scoring to strengthen biomarker-driven decisions.

MIAMI, FL / ACCESS Newswire / April 9, 2026 / Imagene AI, a pioneer in multimodal AI for precision oncology, today announced a collaboration with Daiichi Sankyo (TSE:4568) to advance biomarker discovery and response prediction in oncology drug development.

Through this collaboration, Daiichi Sankyo will leverage Imagene AI’s OI Suite, a multimodal platform powered by the CanvOI foundation model, to generate biologically grounded insights from Hematoxylin and Eosin (H&E) and Immunohistochemistry (IHC) whole-slide images in the context of molecular profiles and longitudinal clinical outcomes. The goal is to inform biomarker hypotheses earlier, strengthen patient stratification, and support data-driven development decisions from translational research through clinical development.

“Collaborating with Daiichi Sankyo reflects a shared commitment to advancing biomarker discovery as a key driver of development success,” said Dean Bitan, Co-founder and CEO of Imagene AI. “By working together, we are integrating multimodal discovery and quantitative IHC scoring to move from biomarker hypothesis to patient stratification with greater confidence, and to generate quantitative signals to enhance companion diagnostic strategy and improve how patients are matched to the therapies most likely to benefit them.”

A key component of the collaboration is the identification of biomarkers and features that correlate with treatment response using Imagene’s OI Suite and large-scale real-world multimodal data to support select antibody drug conjugate (ADC) development programs of Daiichi Sankyo. Through its AI-driven pipelines, Imagene will develop response prediction models to evaluate biomarker candidates, associated biological pathways, and relevant histologic features. In addition, Imagene will apply its proprietary Composite Continuous Scoring methodology to assess target expression from IHC. This AI-powered quantitative framework integrates multiple factors into a single continuous score, potentially enabling a more precise and biologically informed evaluation of target expression to support clinical programs.

Imagene AI’s infrastructure is reinforced by a proprietary real-world data lake integrating more than 3.5 million tissue samples alongside diverse omics and clinical outcomes records, strengthening its ability to operate in heterogeneous and data-constrained development environments.

About Imagene AI
Imagene AI powers a Cross-Modality Intelligence Engine for precision oncology, integrating histology, omics, clinical outcomes, and proprietary real-world data to derive meaningful insights that support biomarker discovery, response prediction, patient stratification, and evidence-based trial design. Our platform enables multimodal AI-driven response modeling from H&E whole-slide images and quantitative assessment of target expression through proprietary IHC Composite Continuous Scoring. We collaborate with leading pharma organizations to advance biomarker-driven programs from discovery through clinical development and deployment.

For more information, visit imagene-ai.com

Media Contact:
Avital Rabani
Imagene AI Corporate Communications
avital@imagene-ai.com

SOURCE: Imagene AI

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