Founding offer · lifetime membership for a single £24, exclusive to our first members · closes 20 June Claim your place →
Global Research Partnerships £24 Lifetime Log inCreate free account

Funded Projects › HORIZON

RatInhalRNA · Rational and Simulation-Supported Design of Inhalable RNA Nanocarrier

HORIZONStatus: SIGNED1 April 202331 March 2028EU funding €2,000,000Call ERC-2022-COG

The overarching goal of RatInhalRNA is to computationally predict and develop efficient formulations for pulmonary RNA therapy. New RNA formulations are imperative for clinical RNA delivery beyond the liver. The lung offers undruggable targets which could be treated with RNA therapeutics. However, approved siRNA formulations are not suited for pulmonary delivery due to instability in lung surfactant and during nebulization. Hence, it is my aim to rationally design inhalable and biocompatible polymer-based siRNA formulations for efficient siRNA delivery to the lung. While biomaterials are commonly optimized empirically via one-variable-at-a-time experimentation, I am the first to combine Design-of-Experiments (DoE) with Molecular Dynamics (MD) Simulations and Machine Learning (ML) to accelerate the discovery and optimization process of siRNA nanocarriers towards the metrics of gene silencing efficacy and biocompatibility at reduced wet-lab resources. In RatInhalRNA, I will synthesize amphiphilic polyspermines and will prepare siRNA-loaded nanoparticles by microfluidic assembly for experimental assessment of physico-chemical parameters as well as in vitro and in vivo gene silencing efficacy in coronavirus infection models. I will assess siRNA binding of the polyspermines via MD simulations and will analyze the contribution of the nanoparticle design factors on experimental and computational readout responses of the DoE. I will train a support vector machine for supervised ML and will generate models to identify areas of interest. Based on the predictions, I will test additional formulations to obtain a validation dataset for the assessment the ability of the ML algorithm to identify design properties of efficient siRNA nanoparticles for pulmonary delivery. RatInhalRNA will enable me to predict favorable siRNA nanoparticle characteristics in the future prior to polymer synthesis thereby reducing experimental work and improving sustainability and animal welfare.

Consortium · 1 organisation

coordinator

LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN

DE · €2,000,000

Research fields

View the official record on CORDIS →

← Find collaborators and more funded projects

Source: CORDIS, Publications Office of the European Union. Global Research Partnerships surfaces open EU research data to help you find collaborators; we are not affiliated with the European Union.