Collaboration Supports Global ADC Development with AI-Powered Tissue Analysis
Posted on 13 Aug 2026
Selecting patients for antibody-drug conjugates (ADCs) increasingly requires broader tissue context, as target expression alone may not fully explain therapeutic response. Laboratories and translational teams therefore need standardized analyses that connect tissue architecture, biomarker expression, and clinical outcomes. A large-scale collaboration is now applying AI-powered tissue intelligence across global ADC development programs to identify candidate spatial biomarkers and generate translational insights.
Nucleai (Tel Aviv, Israel) has announced an ongoing translational research collaboration with Gilead Sciences (Foster City, CA, USA) to support global ADC clinical development programs. The effort centers on Nucleai’s AI-native Tissue Intelligence platform, which integrates multimodal tissue image analysis with clinical data to deliver quantitative insights for biomarker discovery and precision oncology development. The collaboration is designed to demonstrate how AI-powered tissue analytics can transform discovery and translational workflows in oncology.
The technology transforms routine pathology images into quantitative biological readouts by unifying computational pathology, spatial biology, clinical outcomes, and multimodal data within a single framework. This approach enables standardized biomarker assessment from preclinical research through late-stage clinical development while revealing mechanisms of response, resistance, and disease progression. By integrating protein expression with tissue architecture, tumor heterogeneity, and the tumor microenvironment, the platform seeks to better characterize biological drivers of ADC efficacy.
As part of the collaboration, Nucleai has analyzed a large dataset of hematoxylin and eosin (H&E) and immunohistochemistry (IHC) whole-slide images across several clinical studies spanning multiple oncology indications. These analyses are integrated with clinical outcomes to generate novel biological insights and candidate spatial biomarkers for future scientific presentations and publications. The work underscores how AI-enabled standardization and scale can connect tissue biology to outcomes across diverse study cohorts.
According to the collaborators, this strategy establishes a scalable foundation for translational research, biomarker development, and precision medicine. The ongoing project with Gilead, alongside partnerships with other pharmaceutical companies, reflects growing recognition that AI-powered tissue analytics can strengthen biomarker programs across oncology portfolios. Nucleai reports continued expansion of collaborations aimed at biomarker discovery, translational medicine, companion diagnostic development, and enterprise-scale tissue intelligence across the oncology development lifecycle.
“Precision oncology is entering a new phase, where understanding tissue architecture is becoming just as important as understanding molecular alterations. Tissue Intelligence is becoming a foundational capability for precision medicine, helping identify the patients most likely to benefit while enabling pharmaceutical companies to translate tissue biology into reproducible biomarkers that improve the speed and success of oncology drug development,” said Avi Veidman, Chief Executive Officer of Nucleai.
“Scale and reproducibility are becoming essential requirements for biomarker development. Our platform enables standardized spatial analyses across thousands of clinical samples while directly linking tissue biology to patient outcomes, generating evidence that can support translational research, biomarker qualification, and future companion diagnostic strategies,” said Dr. Ken Bloom, Head of Pathology, Nucleai.
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