Machine learning makes magnificent macromolecules for medicine

Veronica Cunitz; Evan Stacy; Penelope Jankoski; Tristan Clemons

doi:10.1016/j.matt.2022.07.008

Machine learning makes magnificent macromolecules for medicine

Matter. 2022 Aug 3;5(8):2558-2561. doi: 10.1016/j.matt.2022.07.008. Epub 2022 Aug 5.

Authors

Veronica Cunitz^{1

2

3}, Evan Stacy^{1

3}, Penelope Jankoski^{1

3}, Tristan Clemons¹

Affiliations

¹ School of Polymer Science and Engineering, The University of Southern Mississippi, Hattiesburg, MS 39406, USA.
² Department of Chemical Engineering, The University of Mississippi, Oxford, MS 38677, USA.
³ These authors contributed equally.

Abstract

At the University of Minnesota, scientists explore the application of machine learning to screen a multiparametric library of polymers to investigate the relationship between polymer attributes, payload type, and biological outcomes to optimize polymeric vector development for delivery of nucleic acid payloads.

Abstract

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