Data in Use: How POLAR and BMI2 Expand the Benefits of the LOOP BMIP

In 2025, the development of LOOP BMIP was largely completed and is now on the verge of going live. The technical infrastructure and a central user portal have been established, standardized protocols for data exchange between institutions have been defined, and a comprehensive framework agreement for joint data projects has been developed. Simultaneously, key data protection aspects have been clarified with the authorities. Since the beginning of 2026, the LOOP BMIP has been undergoing an extended testing phase with selected users for validation and will be available to researchers at the participating institutions in the third quarter of 2026

Within this infrastructure, the platform projects POLAR and BMI2, which started in early 2024, illustrate how the benefits of the LOOP BMIP can be concretely expanded: moving beyond the mere availability of clinical data towards specialized data and analysis environments for proteomics-based lymphoma research and AI-supported imaging. The experience gained from both projects is intended to feed into the further development of the LOOP BMIP – for example on questions of data formats, analysis pipelines, FAIR-compliant databases, or governance processes for new data types.

POLAR (ProteOmics for Lymphoma and Prognostication) is a prime example of how the LOOP BMIP can generate additional impact through specialized data spaces and analyses. The project is building one of the world’s largest systematic proteomics databases for lymphatic malignancies and linking these data with clinical and other molecular information in order to better characterize lymphoma subtypes, predict disease courses more accurately, and select therapies more precisely.

A particular advance lies in the reliable analysis of formalin-fixed tissue samples, which are very common in routine clinical practice and therefore make it easier to deploy modern proteomics directly in everyday care. The highly standardized, partially automated laboratory and analysis processes, as well as the database built according to FAIR principles, expand the benefits of the LOOP BMIP by creating quality-assured access to complex proteomics data – both for local and internationally networked research projects.

BMI²: More Benefit Through Imaging Data and AI

BMI² (Biomedical Informatics Imaging Platform) expands the benefits of the LOOP BMIP by systematically integrating medical imaging into the platform and preparing it for AI-supported analysis. The project is developing a unified, SPHN-compatible infrastructure for imaging data from radiology, pathology, radiation oncology, and other disciplines and is linking these data with clinical and molecular information.

In 2025, the focus was on concrete use cases: large, curated datasets for chest radiographs, PET/CT in oligometastatic tumors, and pediatric brain tumors were established and made usable for automated evaluation methods and AI models. At the same time, metadata standards and data pipelines were created that can be seamlessly connected to the LOOP BMIP In doing so, BMI2 extends the benefits of the BMIP by adding structured access to imaging data and lays the groundwork for gradually integrating AI-supported image analysis into research and clinical decision-making.