A research team led by Professor Olivia Merkel, Chair of Drug Delivery at Ludwig-Maximilians-Universität Munich (LMU) and co-spokesperson of the Cluster of Excellence for Nucleic Acid Therapeutics Munich (CNATM), has developed the first integrated computational platform that combines molecular dynamics (MD) simulations with machine learning (ML) to accelerate the discovery of new polymeric materials for delivering therapeutic RNA. This innovative framework enables researchers to predict the performance of polymer candidates in encapsulating and protecting RNA molecules, while also optimizing their ability to release the cargo inside target cells. By leveraging MD simulations to model molecular interactions at atomic resolution and using ML algorithms to analyze vast datasets and identify promising material properties, the platform significantly reduces the time and cost traditionally associated with experimental screening. The approach allows for the rapid identification of polymers with tailored characteristics such as biocompatibility, stability, and endosomal escape efficiency—key factors in the success of RNA-based therapies. The team’s work represents a major step forward in the rational design of next-generation nanocarriers, paving the way for more effective treatments for genetic disorders, cancer, and infectious diseases. The platform is already being applied within CNATM to advance multiple RNA therapeutic projects, demonstrating its potential to transform the development pipeline from concept to clinical application.