It is discovered that incorporating TriGalNAc-lipid into LNPs containing DSPE-PEG350 increased hepatic luciferase expression 4–6-fold over TriGalNAc-conjugated or unconjugated DMG-PEG2000 LNPs, and 60-fold over TriGalNAc-conjugated or unconjugated DSPE-PEG2000 LNPs in vivo.
Abstract
Active targeting can improve the efficacy of mRNA therapeutics, but ligand-mediated targeting with lipid nanoparticles (LNPs) remains challenging. Here, we studied the impact of polyethylene glycol (PEG)-lipid composition and triantennary N-acetylgalactosamine (TriGalNAc)-modification on the hepatic delivery efficiency of mRNA-LNPs. Incorporating TriGalNAc-lipid into LNPs containing dimyristoyl glycerol (DMG)-PEG2000 or distearoylphosphatidylethanolamine (DSPE)-PEG2000, excipients used in FDA-approved RNA-LNPs or liposomes, did not further improve hepatic mRNA delivery. We discovered that incorporating TriGalNAc-lipid into LNPs containing DSPE-PEG350 increased hepatic luciferase expression 4–6-fold over TriGalNAc-conjugated or unconjugated DMG-PEG2000 LNPs, and 60-fold over TriGalNAc-conjugated or unconjugated DSPE-PEG2000 LNPs in vivo. Despite its relatively low molecular weight PEG, unconjugated DSPE-PEG350 LNP showed moderately extended blood circulation but only moderately reduced cellular uptake in vitro, potentially providing a balanced platform for adding TriGalNAc ligands and improving the overall hepatic delivery efficiency in vivo. The pairing of TriGalNAc-lipid and DSPE-PEG350 in LNPs containing adenine base editor RNAs against PCSK9 lowered plasma cholesterol in wild-type mice, while conventional DMG-PEG2000 LNP was ineffective at the same dose. This study highlights the importance of redesigning the LNP surface to potentiate ligand-mediated active targeting to the liver.
Antibody–oligonucleotide conjugates (AOCs) enable targeted delivery of small interfering RNAs (siRNAs) by coupling them to antibodies for receptor-mediated uptake, enhancing tissue specificity and therapeutic potential. A key determinant of AOC performance is the drug-to-antibody ratio (DAR), which influences pharmacok...
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Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.