Nonclinical Pharmacokinetics Study of OLX702A-075-16, N-Acetylgalactosamine Conjugated Asymmetric Small Interfering RNA (GalNAc-asiRNA).

ABSTRACT

In this study, the nonclinical pharmacokinetics of OLX702A-075-16, an RNA interference therapeutic currently in development, were investigated. OLX702A-075-16 is a novel N-acetylgalactosamine conjugated asymmetric small-interfering RNA (GalNAc-asiRNA) used for the treatment of an undisclosed liver disease. Its unique 16/21-mer asymmetric structure reduces nonspecific off-target effects without compromising efficacy. We investigated the plasma concentration, tissue distribution, metabolism, and renal excretion of OLX702A-075-16 following a subcutaneous administration in mice and rats. For bioanalysis, high-performance liquid chromatography with fluorescence detection was used. The results showed rapid clearance from plasma (0.5 to 1.5 hours of half-life) and predominant distribution to the liver and/or kidney. Less than 1% of the liver concentration of OLX702A-075-16 was detected in the other tissues. Metabolite profiling using liquid chromatography coupled with high-resolution mass spectrometry revealed that the intact duplex OLX702A-075-16 was the major compound in plasma. The GalNAc moiety was predominantly metabolized from the sense strand in the liver, with the unconjugated sense strand of OLX702A-075-16 accounting for more than 95% of the total exposure in the rat liver. Meanwhile, the antisense strand was metabolized by the sequential loss of nucleotides from the 3'-terminus by exonuclease, with the rat liver samples yielding the most diverse truncated forms of metabolites. Urinary excretion over 96 hours was less than 1% of the administered dose in rats. High plasma protein binding of OLX702A-075-16 likely inhibited its clearance through renal filtration. SIGNIFICANCE STATEMENT This study presents the first comprehensive characterization of the in vivo pharmacokinetics of GalNAc-asiRNA. The pharmacokinetic insights gained from this research will aid in understanding toxicology and efficacy, optimizing delivery platforms, and improving the predictive power of preclinical species data for human applications.