Modeling the Kinetics of Lipid-Nanoparticle- Mediated Delivery of Multiple siRNAs to Evaluate the Effect on Competition for Ago2

Drug combinations can improve the control of diseases involving redundant and highly regulated pathways. Validating a multi-target therapy early in drug development remains difficult. Small interfering RNAs (siRNAs) are routinely used to selectively silence a target of interest. Owing to the ease of...

Full description

Saved in:
Bibliographic Details
Published in:Molecular therapy. Nucleic acids 2019-06, Vol.16, p.367-377
Main Authors: Mihaila, Radu, Ruhela, Dipali, Galinski, Beverly, Card, Ananda, Cancilla, Mark, Shadel, Timothy, Kang, Jing, Tep, Samnang, Wei, Jie, Haas, R. Matthew, Caldwell, Jeremy, Flanagan, W. Michael, Kuklin, Nelly, Cherkaev, Elena, Ason, Brandon
Format: Article
Language:English
Subjects:
Argonaute 2 protein
combination therapy
Competition
Drug development
Experiments
FDA approval
Gene expression
Kinetics
Laboratory animals
lipid nanoparticles
mathematical modeling
Mathematical models
mRNA
Nanoparticles
Ordinary differential equations
RNA interference
Sensitivity analysis
siRNA
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Drug combinations can improve the control of diseases involving redundant and highly regulated pathways. Validating a multi-target therapy early in drug development remains difficult. Small interfering RNAs (siRNAs) are routinely used to selectively silence a target of interest. Owing to the ease of design and synthesis, siRNAs hold promise for combination therapies. Combining siRNAs against multiple targets remains an attractive approach to interrogating highly regulated pathways. Currently, questions remain regarding how broadly such an approach can be applied, since siRNAs have been shown to compete with one another for binding to Argonaute2 (Ago2), the protein responsible for initiating siRNA-mediated mRNA degradation. Mathematical modeling, coupled with in vitro and in vivo experiments, led us to conclude that endosomal escape kinetics had the highest impact on Ago2 depletion by competing lipid-nanoparticle (LNP)-formulated siRNAs. This, in turn, affected the level of competition observed between them. A future application of this model would be to optimize delivery of desired siRNA combinations in vitro to attenuate competition and maximize the combined therapeutic effect.
ISSN:2162-2531
2162-2531
DOI:10.1016/j.omtn.2019.03.004