Tiers lieu PETILLANTe Santé (PEPS)
Supported by Reims University Hospital
The PEPS TLE is a complete ecosystem for supporting innovation projects in artificial intelligence for healthcare towards dissemination and valorization after validation by large-scale experimentation on real data. To achieve this, PEPS relies on the Reims University Hospital, the IIAS and the PETILLANTeS incubator.
The Tiers lieu service offering
The TLE PEPS has 8 main missions:
- Prospecting for new projects and testing grounds.
- Diagnosis and selection of projects.
- Pre-maturation.
- Methodological development and activation of experimental fields.
- Conducting and monitoring experiments, analyzing results.
- Pre-industrialization maturation.
- Accompaniment for commercialization.
- Animation of the ecosystem of digital and AI players in healthcare.
The PEPS project provides 5 initial testing grounds:
- le CHU de Reims (users and professionals),
- the Epernay hospital,
- le CH de Troyes,
- all 63 associations of SOS Médecins France,
- the employees of Axon'Cable and its subsidiaries.
This TLE PEPS aims to cover a vast field of healthcare themes thanks to the broad expertise of the IIAS scientific team and expert partners, but also thanks to a broad set of experimental fields. All pathologies addressed by AI solutions, are considered in this program but are also supported solutions dedicated to care pathways, prevention, improved practices and optimization of healthcare resources.
The TLE PEPS is a cross-thematic device for experimenting with and evaluating AI solutions for healthcare, drawing on expertise in both artificial intelligence at IIAS and healthcare expertise thanks to healthcare professionals at Reims University Hospital and partners including SOS Médecins France. It can also draw on Quest for Health's expertise in business development and support.
Tiers lieu d'expérimentation projects
Project 1: Axodiab
Supplier: Axon'Cable
Solution: AXODIAB is a solution dedicated to diabetes healthcare professionals that enables the management of type 2 diabetic patients on multi-injection regimens (Basal- Bolus).
Need: Determine the optimal insulin dose required to prevent hyper- and hypoglycemic events, particularly in elderly patients, taking into account frailty and their individual therapeutic goals.
Contribution of Reims University Hospital: Validation of the solution through evaluation on a broad spectrum of patients: multiple experimental sites, industrialization.
Project 2: AI4OP
Supplier: SOS Médecins France
Solution: Decision support algorithm for unscheduled outpatient medical assessments, enabling referral to the most appropriate care pathway, in particular whether or not to resort to unscheduled hospitalization.
Need: Optimization of the healthcare system through proper patient referral to hospital emergency departments with regard to the population's need for unscheduled care (SNP).
Reims University Hospital's contribution:
- Evaluation and validation of the module in operational medical tools.
- Evaluation of the tool's place in medical processes for setting up the patient care pathway.
- Formalization of the module's integration standards in the various patient management tools.
- Implementation of infrastructures for wide deployment of the tool.
- Evaluation of resources to ensure operational availability of the tool.