Imagene AI and Daiichi Sankyo collaborate on multimodal biomarker discovery for ADC development

Imagene AI (Nasdaq: IMA), a Miami-based precision oncology AI company, announced a collaboration with Japan-based Daiichi Sankyo (TSE: 4568) to apply Imagene’s OI Suite platform to biomarker discovery and response prediction in support of select antibody-drug conjugate (ADC) development programs. Financial terms and specific assets were not disclosed.

Under the agreement, Daiichi Sankyo will use Imagene’s platform — built on its CanvOI foundation model — to analyze H&E (hematoxylin and eosin staining) and IHC (immunohistochemistry) whole-slide images alongside molecular and clinical datasets. The aim is to improve patient stratification and inform biomarker hypotheses earlier in development.

A core focus is Imagene’s “Composite Continuous Scoring” approach to IHC, a technique that uses antibodies to detect and quantify protein expression in tissue samples. Inmagene’s system replaces traditional categorical scoring (0-3+) with a continuous readout of target expression. This reflects a growing need in ADC development for more precise quantification, particularly as therapies expand into lower or heterogeneous expression populations.

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Daiichi Sankyo, which has one of the industry’s largest ADC pipelines built around its DXd payload platform, has been at the forefront of this shift. The success of trastuzumab deruxtecan in HER2-low breast cancer has highlighted the limitations of conventional IHC thresholds and increased demand for more granular biomarker tools.

Imagene AI positions its platform as enabling multimodal analysis across pathology, omics, and clinical outcomes data. The company has built a large real-world dataset spanning millions of tissue samples to support model training and deployment in oncology R&D.

The collaboration also brings added visibility to Imagene AI, which has attracted backing from Larry Ellison and applies Oracle Cloud Infrastructure within its AI-driven precision oncology platform. The company has focused on applying foundation models to pathology data, targeting use cases from early discovery through clinical development.