digiSafe
DIGITALISED AI TOOL FOR SAFE ATMPs
The project promotes advanced digitalization in the ATMP sector to improve weaknesses in today’s standard methods for predicting quality problems that can potentially lead to large losses of resources and reduced quality of life for patients. In the project AI models are trained with omics data generated from various stages of the manufacturing of individualized blood vessels, and from data from native blood vessels from the recipient and from the transplants one year after surgery. Siamese Neural Network-models are developed to assess the safety of ATMP and to develop tests to predict transplant success. Variational Autoencoders will be developed and trained on integrated omics data to identify novel safety biomarkers. The validated AI models will be combined in a software package for the safety assessment of ATMPs, and with future integration into commercial software, where the scalability of the manufacturing methods for a large number of ATMPs will be improved.
Coordinator: University of Skövde
Partners: RISE, VERIGRAFT, SciCross
- Project management and dissemination
- Generation of tissue engineered grafts and control samples
- Preparation of material and omics data generation
- Development of SNN for similarity analysis
- Biomarker identification using VAE and OMICS data integration
- Prototype software tool development and exploitation
Contact: Jane Synnergren, University of Skövde
Email: jane.synnergren@his.se
Website: Digitalized AI tool for safe ATMPs – University of Skövde