The PredictCan team had published a scientific article describing a new human 3D model to predict drug-induced liver injury based on non-genetic host factors. GenuineSlect-TOX is a powerful and highly sensitive human 3D model that is capable of detecting interindividual differences of drug-induced liver injury.
Our compagny moved to the Cap Sigma and acquired a larger laboratory. This was the opportunity to have new equipment in order to standardize our service offeting.
Our project have been awarded by Bpifrance and received a “Bourse French Tech Emergence”. This funding allows the initiation of our R&D program for precision medicine.
Our project on precision medicine have been valued by Bpifrance on the basis of the breakthrough innovation it offers and received the Deeptech label. Our project aims to develop diagnostic tools for cancers based on a technology that amplifies precancerous signals coupled with artificial intelligence for early detection of carcinogenesis or recurrence. The maturity of our technology on the technology readiness level (TRL) scale is 5-6. PredictCan Biotechnologies is leading this project in collaboration with the CHU of Montpellier.