Vanderbilt University Medical Center and Bertis Forge Strategic Alliance to Revolutionize Cancer Drug Discovery through Molecular AI and Spatial ProteomicsNASHVILLE, TN and GWACHEON, SOUTH KOREA — March 5, 2026 — Vanderbilt University Medical Center (VUMC) and Bertis, an AI-driven proteomics-based precision medicine company led by co-CEOs Dong-young Noh and Seung-man Han, today announced a joint research and co-development collaboration. This strategic alliance marks a significant milestone in oncology by advancing the convergence of artificial intelligence, spatial biology, and translational cancer research through VUMC’s Molecular AI Initiative. By integrating VUMC’s Molecular AI capabilities with Bertis’ proprietary deep proteomics and AI-enabled target discovery technologies, the partnership will build an advanced, spatially resolved dataset to identify novel therapeutic targets and predictive biomarkers.The collaboration centers on the transformative power of AI-driven spatial biology and Molecular AI. Traditional target discovery often relies on bulk tissue analysis, which loses the critical context of how cells are organized within a tumor. VUMC’s Molecular AI approach changes this paradigm by employing sophisticated computational spatial analysis to generate high-resolution spatial molecular maps. This AI-driven spatial biology allows researchers to visualize and decode the complex architecture of the tumor microenvironment, specifically identifying how tumor, immune, and stromal cells interact in biologically and therapeutically relevant regions. By mapping the precise locations and spatial relationships of these cells, the Molecular AI platform can isolate the key cell populations responsible for treatment response or resistance.These advanced spatial insights are then seamlessly integrated with Bertis’ cutting-edge proteomics capabilities. While VUMC maps the critical spatial context, Bertis will conduct deep proteomic and metabolomic profiling, applying its proprietary AI-enabled computational models to prioritize the most viable, druggable targets. The initial focus of this joint research will be on HER2-low tumors, a historically challenging clinical area, with the potential to expand into additional tumor types based on data outcomes and joint scientific discussions. By layering spatial context over proteome-level data, the teams aim to pinpoint cell-surface proteins that are uniquely positioned for emerging therapeutic modalities, including antibody-drug conjugates (ADCs) and cell-based therapies.This sophisticated AI-driven spatial multimodal and deep proteomics pipeline is spearheaded by Tae Hyun Hwang, PhD, the Endowed Director of AI Research, Founding Director of the Molecular AI Initiative, and Professor of Surgery at VUMC. Recognized as a leader in spatial AI and Molecular AI, Dr. Hwang also co-leads gastric cancer atlas efforts within the NCI-funded Human Tumor Atlas Network (HTAN) and is spearheading international HTAN collaborations with South Korea’s National Cancer Center. Highlighting the clinical necessity of this integrated approach, Dr. Hwang said, “Identifying therapeutic targets and understanding treatment response require a precise view of proteins, spatial context, and tumor biology. By combining VUMC’s Molecular AI and spatial analysis capabilities with Bertis’ proteomics and AI-enabled target discovery platform, this collaboration is designed to generate high-confidence therapeutic targets and predictive biomarkers that can support future translational research and therapeutic development”.Seung-man Han, CEO of Bertis, emphasized that the alliance accelerates the global reach of their platform. “Partnering with VUMC, a leading U.S. academic medical center with strong expertise in Molecular AI, spatial biology, and cancer research, is highly meaningful and reflects the growing global recognition of Bertis’ technological capabilities,” stated Mr. Han. “Through this collaboration, we aim to expand the role of AI-driven proteomics in drug discovery and identify therapeutic targets that may open new possibilities in oncology”. Ultimately, this joint endeavor reflects a shared commitment to building a more precise, biologically informed approach to cancer drug discovery.