CHICAGO, Illinois, March 25, 2026
Tempus AI has announced a strategic collaboration with Daiichi Sankyo to accelerate AI-driven biomarker discovery and clinical differentiation within an antibody-drug conjugate (ADC) oncology program. The partnership aims to leverage multimodal artificial intelligence, real-world data, and clinical trial insights to enhance patient selection, treatment response prediction, and overall clinical trial success rates, marking a significant advancement in data-driven oncology drug development.
AI-Driven Models Enhance Clinical Trial Precision
The collaboration will integrate Tempus’ proprietary multimodal AI platforms, including its advanced PRISM2 foundation model, with Daiichi Sankyo’s clinical and preclinical ADC data to create highly predictive models for oncology research. These models are designed to analyze pathology images, genomic information, and patient clinical data simultaneously, enabling a deeper understanding of disease biology and therapeutic response.
By combining these datasets, the partnership aims to optimize patient stratification and improve trial design, ultimately increasing the probability of clinical success. The initiative will also generate detailed response maps across Tempus’ extensive oncology database, providing actionable insights that can guide both clinical development strategies and regulatory decision-making. This approach reflects the growing importance of AI-enabled precision medicine in transforming traditional drug development workflows.
Biomarker Discovery Unlocks Personalized Oncology Approaches
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A central focus of the collaboration is the identification of novel biomarkers that can predict treatment response and disease progression. By leveraging real-world data combined with clinical trial datasets, the companies aim to uncover previously unrecognized biological signals that can improve patient outcomes.
The use of AI in this context allows for more precise matching of patients to therapies, ensuring that individuals most likely to benefit from ADC treatments are identified early in the clinical process. This capability is expected to enhance clinical differentiation of ADC therapies, a critical factor in an increasingly competitive oncology landscape.
Furthermore, the collaboration supports the development of data-driven control arms and benchmarking strategies, which can improve the efficiency and robustness of clinical trials. This represents a shift toward more adaptive and intelligent trial designs, where data continuously informs decision-making throughout the development process.
Transforming ADC Development Through Data and Innovation
Antibody-drug conjugates represent one of the most promising classes of targeted cancer therapies, combining the specificity of monoclonal antibodies with the potency of cytotoxic agents. However, their success depends heavily on accurate patient selection and biomarker identification, areas where AI-driven approaches can deliver significant advantages.
The Tempus and Daiichi Sankyo collaboration reflects broader industry trends toward integrating artificial intelligence into clinical development, enabling faster, more efficient, and more precise therapeutic innovation. By leveraging large-scale multimodal datasets, the partnership aims to accelerate discovery timelines, reduce trial failures, and improve patient outcomes.
This initiative also underscores the growing role of technology-driven platforms in biopharmaceutical research, where the convergence of AI, genomics, and clinical data is reshaping how new therapies are developed and evaluated. As oncology continues to evolve toward personalized medicine, such collaborations are expected to play a critical role in defining future treatment paradigms.
The collaboration between Tempus and Daiichi Sankyo represents a significant step forward in the application of artificial intelligence to oncology drug development, particularly in the rapidly advancing field of ADC therapies. By combining cutting-edge AI technology with extensive clinical expertise, the partnership aims to unlock new insights into biomarker discovery and optimize clinical trial performance.
As the pharmaceutical industry continues to embrace data-driven innovation and precision medicine, this collaboration highlights the potential of AI to transform clinical development processes and improve therapeutic outcomes, ultimately delivering more effective treatments to patients with cancer.
Source: Tempus AI, Daiichi Sankyo press release
