Tel Aviv, Israel & Tokyo, Japan | April 9, 2026
Imagene AI has announced a strategic collaboration with Daiichi Sankyo to accelerate multimodal biomarker discovery and response prediction in oncology, leveraging advanced artificial intelligence and real-world data integration to transform drug development. The partnership will utilize Imagene’s OI Suite platform, powered by the CanvOI foundation model, to generate biologically meaningful insights from histopathology images, molecular data, and clinical outcomes, enabling earlier and more precise identification of biomarkers. This initiative underscores the growing importance of AI-driven precision oncology, where data integration and predictive modeling are key to improving clinical trial success rates and patient outcomes.
Multimodal AI Platform Enhances Biomarker Discovery
At the core of the collaboration is Imagene AI’s OI Suite, a cutting-edge platform designed to integrate Hematoxylin and Eosin (H&E) and Immunohistochemistry (IHC) whole-slide imaging data with omics profiles and longitudinal clinical outcomes. This multimodal approach allows for deep biological interpretation of tumor characteristics, enabling researchers to identify novel biomarkers associated with treatment response.
By combining diverse data types into a unified analytical framework, the platform supports early hypothesis generation, improved patient stratification, and data-driven decision-making across the drug development lifecycle. The integration of large-scale real-world datasets, including more than 3.5 million tissue samples, further enhances the platform’s ability to operate in complex and heterogeneous clinical environments, providing a robust foundation for next-generation oncology research.
AI-Driven Response Prediction Supports ADC Development
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The collaboration will specifically support Daiichi Sankyo’s antibody-drug conjugate (ADC) development programs, a rapidly evolving class of targeted cancer therapies. Imagene AI will deploy its machine learning pipelines to develop predictive models that correlate biomarker expression with treatment outcomes, enabling more accurate identification of patients most likely to benefit from specific therapies.
A key innovation in this process is the use of Composite Continuous Scoring, a proprietary methodology that quantitatively evaluates target expression from IHC data by integrating multiple biological variables into a single continuous metric. This approach provides a more precise and biologically informed assessment of tumor characteristics, improving the reliability of biomarker-driven clinical decisions and supporting the development of companion diagnostics.
Transforming Clinical Development Through Data Integration
By combining AI-powered analytics with large-scale real-world data, the collaboration aims to improve translational research and clinical development efficiency, reducing uncertainty in drug development and enhancing the probability of success. The ability to link histological features, molecular signatures, and clinical outcomes enables a more comprehensive understanding of disease biology, supporting evidence-based trial design and optimized patient selection strategies.
This integrated approach aligns with the broader shift toward precision medicine, where therapies are tailored to individual patient profiles based on data-driven insights. The partnership also highlights the increasing role of digital technologies in biopharmaceutical research, bridging the gap between discovery and clinical application through advanced computational platforms.
The collaboration between Imagene AI and Daiichi Sankyo represents a significant advancement in AI-enabled oncology drug development, combining multimodal data integration, predictive modeling, and biomarker discovery to drive innovation in precision medicine. By enabling earlier and more accurate identification of treatment-responsive patient populations, this partnership has the potential to improve clinical outcomes, accelerate drug development timelines, and enhance the success of targeted therapies. As the biopharmaceutical industry continues to adopt AI-driven approaches, initiatives like this will play a critical role in shaping the future of personalized cancer care and data-driven clinical research.
Source: Imagene AI, Daiichi Sankyo press release
