Developing RNA-based Therapeutics

Accurately predicting mRNA secondary structures is a notoriously difficult combinatorial optimisation problem, crucial for RNA-based drug design. Classical methods struggle with the vast number of configurations, hindering efficient drug development.

The complex biological challenge of predicting mRNA secondary structures can be modelled as a binary optimisation problem, solvable on utility-scale quantum computers using algorithms like CVaR-VQE. This approach efficiently finds minimum free energy structures, overcoming classical limitations.

This offers valuable insights into RNA folding, enabling rapid identification of functional RNA structures and revolutionising healthcare through advanced drug development.