Chronic kidney disease (CKD) is a progressive condition defined by sustained structural or functional abnormalities. Monitoring and predicting the risk of CKD progression is difficult due to fluctuating renal function markers and limited access to the organ itself for structural assessment. The KidneySign project aims to develop a blood- and urine-based multimodal proteomic signature reflecting in situ kidney fibrosis and predictive of CKD progression. Personalised nephroprotection based on the complementarity of patients and drugs proteomic profiles will also be explored. The resulting clinical decision support system providing risk estimates and therapeutic guidance will comply with ethical and societal issues identified at each stage of the project. The project relies on the analysis of Big Data comprising classical, proteomic and peptidomic evaluations of kidney biopsy, urine, serum and plasma samples from existing patient cohorts, biobanks and a KidneySign prospective study.