Sialic Acid Mediated Endothelial and Hepatic Uptake: A Mechanism based Mathematic Model Elucidating the Complex Pharmacokinetics and Pharmacodynamics of Efmarodocokin Alfa, a Variably Glycosylated Fusion Protein

Abstract

Sialic acid (SA) is crucial for protecting glycoproteins from clearance. Efmarodocokin alfa (IL-22Fc), a fusion protein agonist that links IL-22 to the crystallizable fragment (Fc) of human IgG4, contains 8 N-glycosylation sites and exhibits heterogeneous and variable terminal sialylation biodistribution. This presents a unique challenge for Pharmacokinetic (PK) and Pharmacodynamic (PD) analysis and cross-species translation. In this study, we sought to understand how varying SA levels and heterogeneous distribution contribute to IL-22Fc's complex PKPD properties. We initially used homogenous drug material with varying SA levels to examine PKPD in mice. Population PKPD analysis based on mouse data revealed that SA was a critical covariate simultaneously accounting for the substantial between subject variability (BSV) in clearance (CL), distribution clearance (CLd), and volume of distribution (Vd). In addition to the well-established mechanism by which SA inhibits ASGPR activity, we hypothesized a novel mechanism by which decrease in SA increases the drug uptake by endothelial cells. This decrease in SA, leading to more endothelial uptake, was supported by the neonatal Fc receptor (FcRn) dependent cell-based transcytosis assay. The population analysis also suggested in vivo EC50 (IL-22Fc stimulating Reg3β) was independent on SA, while the in-vitro assay indicated a contradictory finding of SA-in vitro potency relationship. We created a mechanism based mathematical (MBM) PKPD model incorporating the decrease in SA mediated endothelial and hepatic uptake, and successfully characterized the SA influence on IL-22Fc PK, as well as the increased PK exposure being responsible for increased PD. Thereby, the MBM model supported that SA has no direct impact on EC50, aligning with the population PKPD analysis. Subsequently, using the MBM PKPD model, we employed 5 subpopulation simulations to reconstitute the heterogeneity of drug material. The simulation accurately predicted the PKPD of heterogeneously and variably sialylated drug in mouse, monkey and human. The successful prospective validation confirmed the MBM's ability to predict IL-22Fc PK across variable SA levels, homogenous to heterogeneous material, and across species (R2=0.964 for clearance prediction). Our model prediction suggests an average of 1 mol/mol SA increase leads to a 50% increase in drug exposure. This underlines the significance of controlling sialic acid levels during lot-to-lot manufacturing.