📋 Tender Overview
Start date
1 September 2026
End date
31 August 2031
Objective
Metastasis research is one of the greatest challenges in the medical field. The nanoengineering of inorganic/organic nanoparticles (NPs) with natural signaling carriers such as extracellular vesicles (EVs) is a promising tool to address the lack of treatment efficiency of currently available therapies, blamed on the insufficient accumulation of the antitumoral molecules in the metastasis tissues. Despite several years of intense efforts, therapeutic EVs are still far away from clinical practice. Recent studies have evidenced that this failure is due to the lack of knowledge on how EVs behave in biological environments and how their therapeutic cargo affects the metastasis targeting moieties present on their membranes. Seven believes that the lack of attention on the unknown biomolecular corona (BC) and on its role governing the EVs’ biological identity may well be behind such uncertainties. Understanding EVs’ BC formation will improve the rational EV-inspired nano-therapy design. SEVEN has been designed to generate substantial understating of the NPs-loaded therapeutic EVs behavior, the BC identity and its surface topography to generate new vectors with a much improved accumulation in metastasis target tissues. SEVEN will validate BC’s influence in the EVs metastasis targeting properties in a conceptually and operational ground-breaking experimental design to modify the BC’s surfactome composition for tailoring their therapeutic action. In addition, SEVEN will use supercritical fluid technology as a new scalable and reproducible strategy to create high yield loading of therapeutic NPs-loaded EVs-inspired therapies, maintaining their natural metastasis signaling properties and overcoming the main limitations that have prevented their successful translation to the clinic. All this will allow SEVEN to screen most promising metastasis targeting tailored EVs (loaded with therapeutic NPs) in patient-derived orthotropic xenograft (PDOXs) models.
