HistoloG-IA: Artificial intelligence in digital histology for pre-clinical monitoring of therapeutic agents in renal ciliopathies

His project aims at designing a computer-assisted analysis system based on Artificial Intelligence (AI) for the identification of biological markers of response to treatment in mouse models of orphan kidney diseases. In other words, it will qualify the effect of pharmacological therapeutic agents on pediatric kidney diseases in pre-clinical trials. The analysis will be performed on labeled histological sections, but also on data from other modalities than visual, such as biomarkers from, for example, urine or blood analysis. The project will focus on three objectives:

1) designing algorithms for qualitative and quantitative analysis of kidney damage to assess the effects of the therapeutic agent under study – especially when they are moderate ;

2) to map the histological features in the different regions of the kidney and in time by integrating the available multimodal information

3) to test and validate the performance of the system.

Ultimately, this system will allow the eventual identification of histological biomarkers without bias to determine who, when and how to treat patients. Having preclinical markers of response to therapeutic interventions is a key step in accelerating to the clinic.