Computational technologies are reshaping RNA-targeted drug discovery, enabling researchers to identify promising therapeutic targets with greater confidence and efficiency than ever before. These advances will be showcased at the upcoming RNA-Targeted Drug Discovery & Development Summit.
One of the headline presentations will come from Raphael Townshend, Chief Executive Officer of Atomic AI, who will discuss how AI-enabled structure prediction and functional validation can help researchers prioritize ligandable RNA targets before committing resources to screening campaigns.
Further computational innovation will be explored by Paraskevi Gkeka, Distinguished Scientist and Group Head of Computer-Aided Drug Design at Sanofi. Her presentation will examine modelling approaches that improve understanding of RNA structure, dynamics, and small molecule binding interactions to support target selection and medicinal chemistry efforts.
The session will also highlight tools such as HARIBOSS++, a curated RNA-small molecule binding database, and SHAMAN, a platform designed to assess RNA druggability across diverse conformational states.
As the industry seeks to move beyond trial-and-error screening approaches, these technologies are expected to play an increasingly important role in identifying functionally relevant RNA targets and accelerating the development of selective RNA-targeted therapeutics.
Download the brochure to review the full scientific programme and learn which sessions are focused on AI, machine learning and computational approaches.
Register now to network directly with the teams developing the next generation of RNA-targeted discovery technologies.