Merck–Mayo Clinic Partnership Aligns Clinical Data with AI Drug Discovery

Under a new R&D collaboration formed in February 2026, Merck, known as MSD outside of the United States and Canada, and Mayo Clinic aim to integrate AI, multimodal clinical datasets, and advanced analytics to support drug discovery and precision medicine development. The agreement combines Mayo Clinic’s clinical and genomic data resources with Merck’s expanding investments in AI- and machine learning (ML)-enabled discovery technologies, including virtual cell modeling approaches intended to improve disease characterization and early-stage development decision-making.¹

Their collaboration reflects a broader industry shift toward platform-based partnerships designed to address persistent challenges in target identification and translational success across drug development pipelines.²

“New cutting-edge technologies are enhancing our ability to innovate with the potential to bring important new therapies to patients faster,” said Robert M. Davis, chairman and CEO, Merck, in a company press release.¹ “By working with Mayo Clinic, we aim to integrate high-quality clinical data and AI-enabled insights into discovery research to improve target identification and, ultimately, the probability of success for our programs.”

How can multimodal clinical data improve target identification and early development decisions?

Under the agreement, Merck will access the Mayo Clinic Platform infrastructure, which aggregates de-identified clinical, molecular, imaging, and real-world healthcare data within a secure research environment. The platform integrates datasets from Mayo Clinic’s US operations and international partner network, enabling large-scale analysis across diverse patient populations.

Through the Mayo Clinic Platform_Orchestrate program, Merck researchers will utilize multimodal datasets, including laboratory results, medical imaging, clinical documentation, and genomic information, to validate AI models and refine biological hypotheses during discovery and preclinical development. The approach is intended to strengthen mechanistic understanding of disease biology while improving the probability that selected drug targets translate successfully into clinical development, according to the company.

Why are platform-based AI collaborations becoming central to biopharma R&D strategy?

The collaboration represents Mayo Clinic’s first partnership of this scale with a global biopharmaceutical company and highlights growing industry reliance on integrated data ecosystems to support AI-driven research.^1,3

Rather than applying AI solely as a downstream analytics tool, the partnership will embed computational modeling and advanced analytics earlier in the discovery workflow. Merck and Mayo Clinic expect that this approach will enable iterative validation between clinical observations and experimental biology, which is becoming an increasingly important capability as therapeutic development grows more complex.¹

Initial research efforts will focus on therapeutic areas for which multimodal data integration may accelerate precision medicine strategies, including inflammatory bowel disease in gastroenterology, atopic dermatitis in dermatology, and multiple sclerosis in neurology. By aligning large-scale clinical datasets with AI-enabled discovery platforms, the partners aim to identify biologically defined patient subgroups and support development of more targeted therapeutic interventions.

“By combining Mayo Clinic Platform's de-identified data, clinical expertise and Platform technology with Merck's … research and development capabilities, we are poised to speed innovative breakthroughs to patients and redefine drug development,” said Gianrico Farrugia, MD, president and CEO, Mayo Clinic, in the release.¹ “This collaboration represents a new present and future for healthcare—one where platform-based collaboration leads to more answers, more cures, and better outcomes for patients worldwide.”

What does this collaboration signal for AI adoption across drug development pipelines?

The agreement builds on Merck’s broader strategy to incorporate AI foundation models, computational and spatial biology, and real-world data into discovery workflows. Across the industry, such collaborations are increasingly viewed as a means to reduce attrition rates by improving biological validation prior to clinical entry.¹

As biopharmaceutical companies seek to improve R&D productivity amid rising development costs, partnerships linking clinical data platforms with AI-enabled discovery capabilities may play an expanding role in shaping next-generation precision medicine pipelines.

References

1. Merck. Merck and Mayo Clinic Announce New Research and Development Collaboration to Support AI-Enabled Drug Discovery and Precision Medicine. Press Release. Feb. 18, 2026.
2. Jones CH, Beitelshees M, Hill A, et al. Framework to identify innovative sources of value creation from platform technologies. Proc. Natl. Acad. Sci. U.S.A. 2025;122(21):e2424665122. doi: 10.1073/pnas.2424665122
3. Bhushan A, Misra P. Unlocking the potential: multimodal AI in biotechnology and digital medicine—economic impact and ethical challenges. npj Digit. Med. 2025;8:619. doi: 10.1038/s41746-025-01992-6