IMMUVisionChallenges in the Management of Complex Immune Diseases
The course of chronic inflammatory systemic diseases such as psoriatic arthritis, inflammatory bowel disease (IBD), or inflammatory dermatoses varies from person to person. These diseases are characterized by marked clinical heterogeneity: they affect various organ systems, involve numerous overlaps between medical specialties, and progress at varying rates. The response to targeted immunomodulatory therapies also varies considerably.
This diversity means that uniform disease phenotypes can only be defined to a limited extent, which has made systematic investigation and comparability difficult. At the same time, the complex and often overlapping manifestations require closely coordinated, interdisciplinary treatment concepts as well as increasingly personalized therapeutic approaches.
A key challenge is that the data required for this purpose has often been fragmented: clinical information is recorded in different systems, and a common, standardized documentation system is lacking.
To better understand and effectively leverage the heterogeneity of these diseases, it is therefore crucial to bundle data in a structured manner and make it comparable.
What is a Digital Twin?
A digital twin is an individualized, data-driven model of a patient.
It forms a dynamic, digital representation that integrates medically relevant information and continuously updates the disease progression over time.
This includes:
- Clinical data: diagnoses, disease scores, medication, laboratory values, and findings
- Imaging and histology: endoscopy, MRI, CT, and ultrasound findings
- Progress data: longitudinal documentation of disease activity and response to therapy
- Contextual factors: comorbidities, lifestyle, socioeconomic aspects
- Cohort reference: Comparative data from studies and other patient groups
By structurally synthesizing this data, the Digital Twin can reveal complex relationships and enable comparative analyses. Individual disease courses can be viewed in relation to similar cases and contextualized using evidence-based information, such as clinical guidelines.
Why is this so relevant for inflammatory medicine?
Patients with complex immune disorders are often cared for by multiple specialties simultaneously—particularly rheumatology/immunology, dermatology (e.g., inflammatory skin conditions), and gastroenterology (e.g., chronic inflammatory bowel diseases).
In clinical practice, this often leads to information silos: data is fragmented across different systems, findings are documented differently, and a clear, comprehensive overview of the patient is lacking.
The digital twin can serve as a shared, standardized database here. It enables all treating physicians to access consistent, up-to-date information, better coordinate treatment decisions, and identify potential gaps in care at an early stage.
What does this mean in concrete terms for patient care?
- Earlier and more precise classification of clinical presentations through structured, comparable data across disciplinary boundaries
- More targeted use of modern therapies—e.g., potentially earlier and more needs-based use of biologics
- Transparent disease progression—response to and failure of therapy can be identified early
- Improved interdisciplinary coordination – all treating physicians work from a common data foundation
From theory to practice: IMMUVision
As part of the IMMUVision project, Fraunhofer ITMP is collaborating with Fraunhofer IGD and partners from clinical practice, research, and industry to develop a digital patient model for patients with immune disorders affecting multiple organ systems.
At the heart of the project is a digital platform based on standardized data collection and structuring that specifically integrates the digital twin into everyday clinical care.
It is used:
- in outpatient clinics at inflammatory disease centers
- in specialized practices
- embedded in existing clinical workflows
- connected via an interdisciplinary network of experts
The overarching goal: patient-centered, data-driven care that has the potential to identify gaps in care, improve the quality of treatment, and generate new insights into complex immune disorders.