When structural sophistication becomes a translational barrier: the complexity trap in DNA nanocarrier design
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Folding and Characterization of a Bio-responsive Robot from DNA Origami
Published on: December 3, 2015
Cansu Umran Tunc1, Sushanto Kumar Saha2, Siva S Panda3,4,5
1Utah Center for Nanomedicine, Department of Molecular Pharmaceutics, University of Utah, Salt Lake City, UT, USA.
Abstract:
DNA nanotechnology has emerged as a highly programmable platform in nanomedicine, enabling the fabrication of precise nanoscale architectures for drug delivery, biosensing, gene regulation, immunotherapy, and theranostics. DNA-based nanocarriers offer distinctive advantages, including structural programmability, molecular recognition, multifunctionality, biocompatibility, and stimuli responsiveness. These capabilities have driven the development of DNA origami, tetrahedra, nanocages, hydrogels, aptamer-based systems, and dynamic nanomachines for biomedical applications. Despite compelling proof-of-concept demonstrations and promising preclinical studies, however, clinical translation remains limited. Key barriers include nuclease-mediated instability, immune recognition, biomolecular corona formation, endosomal trapping, unfavorable biodistribution, manufacturing complexity, scalability limitations, regulatory uncertainty, and high production costs. Moreover, the field remains largely driven by engineering innovation and structural sophistication rather than translational practicality. This Perspective critically examines the structural, engineering, and biological barriers restricting the development of DNA nanocarriers into clinically viable systems, while briefly addressing regulatory and commercialization challenges. Emerging strategies, including chemical stabilization, hybrid and biomimetic platforms, AI-assisted optimization, and simplified nanostructure designs, are discussed in the context of overcoming these barriers. We argue that successful clinical translation will require a shift from complexity-driven nanoscale engineering toward clinically oriented platforms that are biologically robust, scalable, manufacturable, and economically sustainable.
