Sepsis is a major public health challenge, with increasing incidence driven by an aging population, immunosuppression, and the rise of multidrug-resistant pathogens and antibiotic resistance. It remains the leading cause of mortality in most hospital intensive care units.
Early detection and prompt initiation of treatment are critical to improving patient outcomes. However, there are currently no effective tools for early diagnosis, prognosis, or comprehensive clinical management of sepsis and septic shock. This highlights the need for advanced solutions capable of identifying patients at high risk and supporting timely clinical decision-making.
In this context, researchers from the INCLIVA Health Research Institute, Universidad de Valencia and EpiDisease (spin-off of both institutions) have developed a platform based on three AI models that allows sepsis patients to be identified using clinical history and background data, immediately collected physiological variables in real time, and analytical results that are progressively incorporated. This allows for sequential assessment and monitoring of the risk of developing sepsis in hospitalized patients as new clinical information becomes available.
The software has been developed and validated using real clinical data from 440 patients admitted to the Intensive Care Unit at the University Clinical Hospital of Valencia and other hospitals. Tests must be carried out in a real environment to improve the diagnostic and prognostic software.
Benefits:
- Real-time assessment and monitoring based on multiple variables.
- Early identification of patients at high risk of developing sepsis.
- Ability to identify patients at greatest risk.
- Personalized, rapid, and accurate treatment.
- Predicting the progression of the disease.
- AI-based diagnostic system for automatic decision-making based on the integration of clinical, analytical, and physiological data.
- Risk stratification that allows for the optimization of clinical resources.
Diagnostic medical device companies interested in signing a license agreement to market the software or an agreement to collaborate in the implementation of this technology.
Institution: INCLIVA Instituto de Investigación Sanitaria, Universidad de Valencia (UV) y EpiDisease
TRL: 5
Protection Status: Software registered under number SWF2025_02 on October 23, 2025
Contacto: Elisa Sáenz | e.saenz@viromii.com