Issue 96, 2023

Frontiers in nonviral delivery of small molecule and genetic drugs, driven by polymer chemistry and machine learning for materials informatics

Abstract

Materials informatics (MI) has immense potential to accelerate the pace of innovation and new product development in biotechnology. Close collaborations between skilled physical and life scientists with data scientists are being established in pursuit of leveraging MI tools in automation and artificial intelligence (AI) to predict material properties in vitro and in vivo. However, the scarcity of large, standardized, and labeled materials data for connecting structure–function relationships represents one of the largest hurdles to overcome. In this Highlight, focus is brought to emerging developments in polymer-based therapeutic delivery platforms, where teams generate large experimental datasets around specific therapeutics and successfully establish a design-to-deployment cycle of specialized nanocarriers. Three select collaborations demonstrate how custom-built polymers protect and deliver small molecules, nucleic acids, and proteins, representing ideal use-cases for machine learning to understand how molecular-level interactions impact drug stabilization and release. We conclude with our perspectives on how MI innovations in automation efficiencies and digitalization of data—coupled with fundamental insight and creativity from the polymer science community—can accelerate translation of more gene therapies into lifesaving medicines.

Graphical abstract: Frontiers in nonviral delivery of small molecule and genetic drugs, driven by polymer chemistry and machine learning for materials informatics

Article information

Article type
Highlight
Submitted
22 sep 2023
Accepted
02 nov 2023
First published
06 nov 2023

Chem. Commun., 2023,59, 14197-14209

Frontiers in nonviral delivery of small molecule and genetic drugs, driven by polymer chemistry and machine learning for materials informatics

J. M. Ting, T. Tamayo-Mendoza, S. R. Petersen, J. Van Reet, U. A. Ahmed, N. J. Snell, J. D. Fisher, M. Stern and F. Oviedo, Chem. Commun., 2023, 59, 14197 DOI: 10.1039/D3CC04705A

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