Daiichi Sankyo Leverages AI to Strengthen ADC Clinical Strategy

As antibody-drug conjugates (ADCs) move into increasingly crowded and competitive oncology pipelines, the ability to precisely identify which patients will benefit is emerging as a critical differentiator, not just for clinical success, but for regulatory approval and commercial positioning.¹ Under this market pressure, Tempus AI and Daiichi Sankyo’s newly announced collaboration points to a broader industry shift toward embedding artificial intelligence (AI) directly into ADC development to improve trial design, biomarker discovery, and ultimately, therapeutic impact.

On March 25, 2026, the companies said they entered a strategic collaboration to apply multimodal AI and real-world data to accelerate the clinical development of a novel ADC program. The partnership will leverage Tempus’ proprietary foundation models, including PRISM2, which integrates pathology imaging with clinical datasets to generate predictive insights for oncology applications.²

By combining Daiichi Sankyo’s clinical and preclinical datasets with Tempus’ large-scale real-world oncology database, the collaboration aims to identify new biomarkers and refine patient stratification strategies, two areas that have historically limited the full potential of ADC therapies.^2,3

“Our collaboration with Daiichi Sankyo signals a new chapter in how multimodal AI and real-world data can be applied to advance the development of ADCs,” said Ryan Fukushima, CEO of Data and Apps at Tempus, in a company press release.² “Our multimodal foundation models seek to radically accelerate and improve our ability to uncover unmet patient needs and identify patients most likely to benefit from novel therapies. Applying AI in clinical development isn’t just about efficiency anymore, … companies like Daiichi Sankyo are using these models to enhance the design of more targeted, impactful clinical trials.”

Why is AI-driven biomarker discovery becoming essential for ADC development?

While ADCs combine targeted antibodies with cytotoxic payloads, their clinical performance often depends on selecting the right patient populations based on tumor biology and antigen expression. Variability in response has made biomarker-driven development increasingly important, particularly as more ADCs enter similar indications.¹

Through this collaboration, Tempus and Daiichi Sankyo will develop proof-of-concept AI models designed to optimize patient selection and increase the probability of clinical success. These models will generate response maps across diverse patient populations, which are expected to enable more precise cohort identification and support the design of more efficient and predictive clinical trials. The approach may also improve benchmarking of control arms, which is an area of growing scrutiny in oncology trials, according to the companies.

How does this collaboration fit into the broader ADC pipeline strategy?

For Daiichi Sankyo, the partnership reflects a continued effort to strengthen its position in the ADC space by pairing its drug development capabilities with advanced data science. This strategy is increasingly important as ADC pipelines expand and competition intensifies across tumor types.¹

Previously, Daiichi Sankyo and AstraZeneca’s ADC, trastuzumab deruxtecan (brand name Enhertu), was granted priority review in early March 2026 by FDA as a post-neoadjuvant treatment for HER2-positive early breast cancer, which marked continued expansion into earlier lines of therapy.⁴ This move reflects a broader industry trend toward advancing ADCs into settings where patient selection and differentiation are even more critical.

The collaboration between Tempus and Daiichi Sankyo highlights how AI is transitioning from a supportive tool to a core component of drug development strategy, especially in complex modalities like ADCs, where precision in both biology and trial design will define the future of innovation in this space.

References

1. Chen B, Zheng X, Wu J, et al. Antibody-drug conjugates in cancer therapy: current landscape, challenges, and future directions. Mol. Cancer 2025;24(1):279. doi: 10.1186/s12943-025-02489-2 
2. Tempus AI. Tempus announces strategic collaboration with Daiichi Sankyo to advance AI-driven biomarker discovery and clinical differentiation across an ADC clinical program. Published March 25, 2026. Accesed March 26, 2026. https://www.tempus.com/news/pr/tempus-announces-strategic-collaboration-with-daiichi-sankyo-to-advance-ai-driven-biomarker-discovery-and-clinical-differentiation-across-an-adc-clinical-program/
3. Shi R, Jia L, Lv Z, Cui J. Another power of antibody-drug conjugates: immunomodulatory effect and clinical applications. Front. Immunol. 2025;16:1632705. doi: 10.3389/fimmu.2025.1632705
4. AstraZeneca. Enhertu granted Priority Review in the US as post-neoadjuvant treatment for patients with HER2-positive early breast cancer. Published March 9, 2026. Accessed March 26, 2026. https://www.astrazeneca.com/media-centre/press-releases/2026/enhertu-granted-priority-review-in-the-us-as-post-neoadjuvant-treatment-for-patients-with-her2-positive-early-breast-cancer.html