MED²ICIN - Medical Data Driving an Integrated Cost-Intelligent Model

About the project:

Just one click to receive the appropriate preventative measure, diagnosis and therapy? This is the vision of the so called, ‘MED2ICIN’ flagship project. The development of a digital patient model has disruptive potential for the healthcare industry, because the more targeted and effective prevention, diagnosis and therapy are, the better and cheaper the treatment becomes.

The MED2ICIN project is dedicated to the goal of creating a holistic digital patient model by merging data which had been previously temporally and physically dispersed with partially unstructured health and disease data from individuals into a single digital image. This offers both enormous potential for improvement of individual treatment and increased cost awareness within society.

The scientific excellence and interdisciplinary competence of the seven participating institutes be only be found here, at the Fraunhofer Gesellschaft. In addition, we provide the technological know-how, especially in the areas of AI and machine learning, knowledge extraction and modelling, data management and visualization, and include the necessary expertise on ‘clinical framework’ conditions and guidelines.

In doing so, Fraunhofer IMW makes a decisive contribution to the anchoring of socio-economic research aspects as well as early joint reflections on the exploitation strategy for the project. Fraunhofer IMW's expertise is used in the modelling of health and economic relationships in the course of data analysis.

A better understanding of the individual in the context of the overall population and statements of prognosis about the temporal course of a disease or therapy offer a wide range of possibilities for intelligent use and control of Health expenditure:

  • Early detection of diseases at the start of therapy when the damage is still minor
  • Identification of those patients who actually benefit from new and costly diagnostic procedures, finding alternative pathways for all others
  • Cost-based and data-based modeling of clinical guidelines and decision-making processes
  • Avoidance of expensive multiple surveys such as MRI scans
  • Selection of the best individual therapy and avoidance of multiple therapies that follow the pattern "Trial & Error"
  • Avoidance of adverse drug reactions
  • Monitoring the effectiveness of the therapy to reduce unnecessary or/ ineffective drug administration
  • Transparent proof of the health benefits of new medicines, medical devices and supply processes
  • Cost minimization by automating manual medical personnel processes

Through interdisciplinary cooperation between seven Fraunhofer institutes, we created the technological prerequisites are created and clinical guidelines-related framework conditions are integrated into the digital patient model. The case studies of gastrointestinal (one of the biggest cost drivers) and oncological diseases demonstrate how such a digital patient model can lead to a smarter use of healthcare costs. A targeted transfer of the, so called ‘Digital Twins,’ already an advanced element of Industry 4.0, into medicine provides a conceptual framework for introducing new sensor- and data-driven supply models. Additionally, these model analyzes, monitors and generates suggestions for prevention, diagnostics, therapy and aftercare.



Project partners:

  • Fraunhofer IGD
  • Fraunhofer IAIS
  • Fraunhofer IIS
  • Fraunhofer IME
  • Fraunhofer IOSB
  • Fraunhofer MEVIS

Project duration:

10/01/2018 – 09/30/2022


MED²ICIN: The right prevention, diagnosis and therapy at a glance