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Determination of key structure–activity relationships in siRNA delivery with a mixed micelle system()()

Short interfering ribonucleic acids (siRNAs) offer a highly specific and selective form of therapy for diseases with a genetic component; however the poor pharmacokinetic properties of the molecule have impeded its development into a therapeutic for use in vivo. Several different approaches have bee...

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Detalles Bibliográficos
Autores principales: Omedes Pujol, Marta, Coleman, Daniel J.L., Allen, Christopher D., Heidenreich, Olaf, Fulton, David A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Science Publishers 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3898608/
https://www.ncbi.nlm.nih.gov/pubmed/24140749
http://dx.doi.org/10.1016/j.jconrel.2013.10.013
Descripción
Sumario:Short interfering ribonucleic acids (siRNAs) offer a highly specific and selective form of therapy for diseases with a genetic component; however the poor pharmacokinetic properties of the molecule have impeded its development into a therapeutic for use in vivo. Several different approaches have been taken to develop a successful siRNA delivery system but these systems lack the flexibility for easy optimisation. Here, we propose a polymeric nanoparticle (PNP) system consisting of two amphiphilic diblock copolymers which allow for the rapid determination of structure–activity relationships involving gene knockdown and toxicity. The diblock copolymers self-assemble into monodisperse micelles of defined hydrodynamic diameters ranging from 30 to 100 nm dependent on the copolymer ratio. A luciferase-based high throughput assay varying PNP composition, concentration and siRNA concentration allowed the rapid identification of efficient PNP formulations for adherent and suspension cell lines. Optimised PNPs efficiently knocked down a fusion oncogene in hard to transfect human leukaemic cells raising the possibility of targeting malignant cells in a cancer-specific fashion. This approach allows the optimum PNP formulation to be identified for different cell types and conditions.