Conclusion
This strategy has the potential for preparing custom LNPs with endless varieties of structures and final pKa values, and would have poten tial applications in drug delivery and ionic-based tissue targeting.
Methods
We report herein on optimizing the targeting efficiency of a lipid nanoparticle (LNP) by manipulating the acid dissociation constant (pKa) value of its membrane, which reflects its ionization status. Instead of changing the chemical structure of the lipids to achieve this, we used a mixture of two types of pH-sensitive cationic lipids that show different pKa values in a single LNP. We mixed various ratios of YSK05 and YSK12-C4 lipids, which have pKa values of 6.50 and 8.00, respectively, in one formulation (referred to as YSK05/12-LNP).
Results
The pKa of the YSK05/12-LNP was dependent not only on the molar ratio of each lipid but also on the individual contribution of each lipid to the final pKa (the YSK12-C4 lipid showed a higher contribution). Furthermore, we succeeded in targeting and delivering short interfering RNA to liver sinusoidal endothelial cells using one of the YSK05/12-LNPs which showed an optimum pKa value of 7.15 and an appropriate ionization status (~36% cationic charge) to permit the particles to be taken up by liver sinusoidal endothelial cells.