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An Overlooked Formulation Variable: Solvent Reshapes DNA Delivery

delete2026-05-20
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PRE
AI
Y
Yinghao Li
B
Bei Qiu
L
Liang Yao
J
Jiahao Liu
Z
Zishan Li
X
Xinhui Wang
J
Jing Lyu *
W
Wenxin Wang *
DOI:10.1021/acsmacrolett.6c00160delete
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Abstract

Abstract

En 中文
Nonviral polymeric vectors offer a tunable platform for nucleic acid delivery, yet formulation variables beyond polymer structure remain underexplored. Here, we systematically investigate the role of stock solvent in shaping gene delivery performance using end-capped highly branched poly(amino ester) (HPAE) vectors. By combining a structured experimental design with an interpretable machine learning framework, we reveal that transfection efficiency is primarily governed by polymer features, while solvent properties modulate performance through strong polymer–solvent interactions. Descriptor-level analysis identifies key molecular features associated with high-performing formulations, highlighting the importance of polymer size, charge density, and hydrophobic–polar balance. Selected polymer–solvent combinations enable efficient CFTR protein restoration in cystic fibrosis disease cells and achieve robust in vivo transgene expression following systemic administration in mice. Overall, this work establishes stock solvent as a critical and tunable formulation parameter and provides a data-driven framework for optimizing polymeric gene delivery systems.
Keywords:
polymeric vectors
gene delivery
stock solvent
machine learning
formulation optimization

Journal

ACS Macro Letters cover
ACS Macro Letters
IF:
5.2
Papers:
336
Citations:
1.4W

Organization

A
anhui university of science and technology
Scholars:
1.3K
Papers: 465
Citations: 0
U
university college dublin
Scholars:
2.5W
Papers: 2.2W
Citations: 22
S
southwest jiaotong university
Scholars:
7.7K
Papers: 2.8K
Citations: 0
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