Titles and Affiliations
Professor, Clinical Artificial Intelligence
Senior Physician, Medical Oncology
National Center for Tumor Diseases
Heidelberg, Germany
Professor
TUD Dresden University of Technology
Dresden, Germany
Research Area
Developing a comprehensive groundwork for accurate and reliable integration of artificial intelligence into breast cancer care.
Impact
Artificial intelligence (AI) tools are utilized in virtually all aspects of life, including in oncology. As patients, caregivers, and clinicians all have access to vast amounts of information through AI, the accuracy and safety of using it remains under scrutiny. Large language models (LLMs) are advanced AI systems that can process and generate text as a person would. Trained on huge amounts of text, it is still not clear how efficient LLMs are at answering breast cancer questions. Dr. Kather and his colleagues are utilizing their considerable expertise in LLMs and AI to solve this pressing problem. By creating and testing a comprehensive benchmark for evaluating LLM performance specifically in breast oncology, Dr. Kather hopes to optimize their use and provide a groundwork for responsible integration of AI into breast cancer care to ultimately benefit patients.
Progress Thus Far
Dr. Kather’s team used their extensive experience developing AI-driven biomarker discovery tools, decision-support systems for oncologists, and automated research workflows to develop BELLADONNA, the first-of-its-kind agent that can pursue a project in breast cancer research step by step. BELLADONNA is being tested to address the major treatment gaps in hormone receptor-positive cases that progress after CDK4/6-inhibitor treatment, triple-negative breast cancer, or invasive lobular carcinoma. Using evidence from millions of papers, data from clinical trials, drug records, and guidelines that is nearly impossible for a person to read in total, the Kather team built BELLADONNA: The largest organized library of breast cancer evidence to date, with over 4.6 million verified pieces of information from more than 181,000 documents. The long-term goal of the program is to turn this massive amount of information into an engine for scientific discovery.
What’s Next
In the coming year, Dr. Kather and his colleagues will extend the BELLADONNA knowledge base with curated drug and pharmacology resources and build an autonomous reasoning agent to aid breast oncologists in caring for patients. They will continue to develop and test BELLADONNA-2 with the goal to leverage the potential benefits of AI to improve personalized patient education and medical guidelines—while minimizing risks. This project lays the groundwork for responsible AI integration into breast cancer care, ultimately helping to deliver better care more consistently and safely to patients.
Biography
Jakob Nikolas Kather, MD MSc is a Professor of Clinical Artificial Intelligence at Heidelberg University Hospital and the Medical Faculty of Heidelberg in Heidelberg, Germany. He is also an adjunct professor TUD Dresden University of Technology in Dresden, Germany and affiliated with the National Center for Tumor Diseases (NCT) in Heidelberg. His research is focused on applying artificial intelligence in precision oncology. Prof. Kather’s research team is using deep learning techniques to analyze a spectrum of clinical data, including histopathology, radiology images, textual records, and multimodal datasets. Guided by the belief that medical and tech expertise needs to be combined, medical researchers in his team learn computer programming and data analysis, while computer scientists are immersed in cancer biology and oncology. Prof. Kather chairs the “Working group on Artificial Intelligence” at the German Society of Hematology and Oncology (DGHO) and is a member of the pathology task force of the American Association for Cancer Research (AACR). His work is supported by numerous European and national grants, which enable the team to develop new deep learning methods for medical data analysis techniques and to apply them in precision oncology. He has received several awards including the Felix Burda Award in Medicine & Science (Felix Burda Foundation,2025), Teaching Award for “Clinicum Digitale” (TU Dresden,2023), and the Thannhauser Prize for outstanding and pioneering scientific work in the field of digestive and metabolic diseases from the German Society for Digestive and Metabolic Diseases (2022).
