Title |
Degradable lipid nanoparticles with predictable in vivo siRNA delivery activity
|
---|---|
Published in |
Nature Communications, June 2014
|
DOI | 10.1038/ncomms5277 |
Pubmed ID | |
Authors |
Kathryn A. Whitehead, J. Robert Dorkin, Arturo J. Vegas, Philip H. Chang, Omid Veiseh, Jonathan Matthews, Owen S. Fenton, Yunlong Zhang, Karsten T. Olejnik, Volkan Yesilyurt, Delai Chen, Scott Barros, Boris Klebanov, Tatiana Novobrantseva, Robert Langer, Daniel G. Anderson |
Abstract |
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 EC50 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. |
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Ireland | 1 | 14% |
Portugal | 1 | 14% |
Unknown | 2 | 29% |
Demographic breakdown
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Scientists | 2 | 29% |
Science communicators (journalists, bloggers, editors) | 2 | 29% |
Members of the public | 2 | 29% |
Practitioners (doctors, other healthcare professionals) | 1 | 14% |
Mendeley readers
Geographical breakdown
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United States | 3 | <1% |
Germany | 2 | <1% |
Canada | 2 | <1% |
Unknown | 515 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 137 | 26% |
Researcher | 71 | 14% |
Student > Master | 53 | 10% |
Student > Bachelor | 38 | 7% |
Student > Doctoral Student | 27 | 5% |
Other | 64 | 12% |
Unknown | 132 | 25% |
Readers by discipline | Count | As % |
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Chemistry | 71 | 14% |
Biochemistry, Genetics and Molecular Biology | 66 | 13% |
Engineering | 50 | 10% |
Agricultural and Biological Sciences | 47 | 9% |
Pharmacology, Toxicology and Pharmaceutical Science | 41 | 8% |
Other | 90 | 17% |
Unknown | 157 | 30% |