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Updated: Mar 31, 2026

Testing the In Vitro and In Vivo Efficiency of mRNA-Lipid Nanoparticles Formulated by Microfluidic Mixing
Published on: January 20, 2023
Efficiency and safety of five different agents for in vivo delivery of novel bioengineered RNAi molecules
Su Guan1, Mei-Juan Tu1, Yan-Ju Li1
1Department of Biochemistry and Molecular Medicine, School of Medicine, University of California at Davis, Sacramento, CA, United States.
Abstract:
RNA molecules have emerged as an addition to existing entities for therapy and vaccination, whose success may be hindered by inefficient in vivo delivery or induction of excessive toxicities, such as severe cytokine release syndrome. In this study, we used a novel, bioengineered RNA (BioRNA) bearing payload siRNA against green fluorescent protein (GFP) (BioRNA/GFP-siRNA) and a GFP-transgenic mouse model to compare the efficiency and safety of five commercial agents, namely lipid nanoparticles (LNP) and Invivofectamine, as well as Nanoparticle, LIPID-, and PEG-Liposome based In Vivo Transfection Reagents. The results showed that all products provided effective delivery of BioRNA/GFP-siRNA into mouse livers to elicit RNA interference (RNAi) effects. Among them, the LNP, Invivofectamine, and nanoparticle formulations showed relatively greater efficacy, as manifested by higher siRNA accumulation or lower GFP mRNA levels and fluorescence intensity. However, the MC3-based LNP-BioRNA treatment led to an 8% decrease in body weights and obvious hepatosplenomegaly, as well as statistically significant changes in liver and kidney function biomarkers and elevation of multiple pro-inflammatory cytokines, while all other formulations were generally well tolerated. In addition, delivery efficiency of these in vivo transfection agents determined in cells in vitro were not proportional to their performance in mice in vivo. These findings highlight the differences among these RNA delivery systems examined herein and underscore the importance of rigorous evaluation of both efficacy and safety when selecting appropriate platforms for RNA agents.
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