Calculating Apparent pKa Values of Ionizable Lipids in Lipid Nanoparticles

Abstract

Creating new ionizable lipids for use in lipid nanoparticles (LNPs) is an active field of research. One of the critical properties for selecting suitable ionizable lipids is the apparent pKa value of the lipid as formulated in an LNP. We have developed a structure-based, computational methodology for the prediction of the apparent pKa value of ionizable lipids within LNPs. This methodology has been validated for the three most successful ionizable lipids to date which are present in the mRNA LNP COVID-19 vaccines COMIRNATY® (Pfizer/BioNTech) and Spikevax® (Moderna), and the siRNA LNP therapeutic Onpattro® (Alnylam). The calculation was also applied to Lipid A, a variant of the ionizable lipid used in COMIRNATY®. We believe that this new technology permits systematic computational prescreening of ionizable lipids to select the most promising candidates for synthesis and experimental testing, accelerating the formulation improvement process and reducing costs.