Degradable lipid nanoparticles with predictable in vivo siRNA delivery activity

One of the most significant challenges in the development of clinically viable delivery systems for RNA interference therapeutics is to understand how molecular structures influence delivery efficacy. Here, we have synthesized 1,400 degradable lipidoids and evaluate their transfection ability and st...

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Published in:Nature communications Vol. 5; no. 1; p. 4277
Main Authors: Whitehead, Kathryn A., Dorkin, J. Robert, Vegas, Arturo J., Chang, Philip H., Veiseh, Omid, Matthews, Jonathan, Fenton, Owen S., Zhang, Yunlong, Olejnik, Karsten T., Yesilyurt, Volkan, Chen, Delai, Barros, Scott, Klebanov, Boris, Novobrantseva, Tatiana, Langer, Robert, Anderson, Daniel G.
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 27-06-2014
Nature Publishing Group
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Summary:One of the most significant challenges in the development of clinically viable delivery systems for RNA interference therapeutics is to understand how molecular structures influence delivery efficacy. Here, we have synthesized 1,400 degradable lipidoids and evaluate their transfection ability and structure–function activity. We show that lipidoid nanoparticles mediate potent gene knockdown in hepatocytes and immune cell populations on IV administration to mice (siRNA EC 50 values as low as 0.01 mg kg −1 ). We identify four necessary and sufficient structural and pKa criteria that robustly predict the ability of nanoparticles to mediate greater than 95% protein silencing in vivo . Because these efficacy criteria can be dictated through chemical design, this discovery could eliminate our dependence on time-consuming and expensive cell culture assays and animal testing. Herein, we identify promising degradable lipidoids and describe new design criteria that reliably predict in vivo siRNA delivery efficacy without any prior biological testing. Robust and reliable structure–function relationships are valuable for the development of potent drug delivery systems. Here, the authors use a library of lipid-like materials to predict in vivo siRNA delivery efficacy without any biological testing.
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Current address: Department of Chemical Engineering, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA, 15217.
ISSN:2041-1723
2041-1723
DOI:10.1038/ncomms5277