Discovering lipid nanoparticles for unmet clinical needs relies heavily on the screening of unique formulations incorporating distinct lipids and nucleic acid cargos. This Perspective highlights how automation and parallelization have accelerated the rate of lipid nanoparticle discovery and discusses how coupling these advances with machine learning enable the predictive design of new therapeutic candidates.
- Andrew R. Hanna
- David A. Issadore
- Michael J. Mitchell
