Multiparametric approach for the evaluation of lipid nanoparticles for siRNA delivery

• Main Authors: Alabi, Christopher A. (Contributor), Sahay, Gaurav (Contributor), Yin, Hao (Contributor), Luly, Kathryn M. (Author), Anderson, Daniel Griffith (Contributor), Love, Kevin T (Author), Langer, Robert S (Author)
• Other Authors: Massachusetts Institute of Technology. Institute for Medical Engineering & Science (Contributor), Harvard University- (Contributor), Massachusetts Institute of Technology. Department of Chemical Engineering (Contributor), Koch Institute for Integrative Cancer Research at MIT (Contributor), Love, Kevin T. (Contributor), Langer, Robert (Contributor)
• Format: Article
• Language: English
• Published: National Academy of Sciences (U.S.), 2014-08-29T11:50:53Z.
• Subjects: Article
• Online Access: Get fulltext

 Nanoparticle-mediated siRNA delivery is a complex process that requires transport across numerous extracellular and intracellular barriers. As such, the development of nanoparticles for efficient delivery would benefit from an understanding of how parameters associated with these barriers relate to the physicochemical properties of nanoparticles. Here, we use a multiparametric approach for the evaluation of lipid nanoparticles (LNPs) to identify relationships between structure, biological function, and biological activity. Our results indicate that evaluation of multiple parameters associated with barriers to delivery such as siRNA entrapment, pK[subscript a], LNP stability, and cell uptake as a collective may serve as a useful prescreening tool for the advancement of LNPs in vivo. This multiparametric approach complements the use of in vitro efficacy results alone for prescreening and improves in vitro-in vivo translation by minimizing false negatives. For the LNPs used in this work, the evaluation of multiple parameters enabled the identification of LNP pK[subscript a] as one of the key determinants of LNP function and activity both in vitro and in vivo. It is anticipated that this type of analysis can aid in the identification of meaningful structure-function-activity relationships, improve the in vitro screening process of nanoparticles before in vivo use, and facilitate the future design of potent nanocarriers.