In silico prediction of siRNA ionizable-lipid nanoparticles In vivo efficacy: Machine learning modeling based on formulation and molecular descriptors

In silico prediction of the in vivo efficacy of siRNA ionizable-lipid nanoparticles is desirable as it can save time and resources dedicated to wet-lab experimentation. This study aims to computationally predict siRNA nanoparticles in vivo efficacy. A data set containing 120 entries was prepared by...

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Detalles Bibliográficos
Autores principales: Metwally, Abdelkader A., Nayel, Amira A., Hathout, Rania M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Molecular Biosciences
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9811823/
https://www.ncbi.nlm.nih.gov/pubmed/36619167
http://dx.doi.org/10.3389/fmolb.2022.1042720

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9811823/
https://www.ncbi.nlm.nih.gov/pubmed/36619167
http://dx.doi.org/10.3389/fmolb.2022.1042720

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