Data-driven Design of Polymeric Vehicles for Gene Editing
Rational polymer design is impeded by the “curse of dimensionality” since elucidation of the mechanistic roles played by numerous design variables such as polymer composition, architecture, length and formulation parameters is confounded by non-linearities. Intuition-based methods of pattern recognition and traditional hypothesis-testing statistical frameworks cannot alleviate challenges arising from a complex multidimensional design space.