Medical Data Science

The Medical Data Science team at Fraunhofer ITMP in Hamburg focuses on AI and data science methodologies for digital health in drug discovery, preclinical and clinical research. The medical data science is centered around the four major domains Drugs, Devices, Data, and Diagnostics (4D) of health research. It handles and analyses various kinds of medical data, such as data from clinics and clinical trials, OMICS, electronic health records, medical imaging, and wearables. The core competencies include machine learning, knowledge graphs & federated learning, and FAIR (Findable, Accessible, Interoperable, Reusable) handling of medical data.

A special focus lies on the investigation of immune-mediated diseases in cooperation with clinicians, pharmaceutical companies and academic partners. Cutting-edge machine learning algorithms are leveraged for the diagnosis, prognosis and precision medicine therapy for immune-mediated diseases. To facilitate this, high performance software and hardware platforms (including its high-throughput laboratories) enable exploration and validation of digital health research concepts. An integrated approach of the five Fraunhofer ITMP sites is expected to accelerate incisive data analysis and development of innovative solutions for the pharmaceutical industry.

Service offering:

• Machine learning for 4D (Drugs, Devices, Data, and Diagnostics)
• FAIR (Findable, Accessible, Interoperable, Reusable) medical data management
• Establishment of decentralized data spaces
• Cohorts as well as tools and platforms for the analysis of complex data
• Knowledge graphs development
• Federated learning infrastructure and medical data platform
• Real-world evidence (RWE) and synthetic medical data
• Biostatistical support of clinical and preclinical studies