Physiologically based modeling of LNP-mediated delivery of mRNA in the vascular system

Abstract

RNA therapeutics are an emerging, powerful class of drugs with potential applications in a wide range of disorders. A central challenge in their development is the lack of clear pharmacokinetic (PK)-pharmacodynamic relationship, in part due to the significant delay between the kinetics of RNA delivery and the onset of pharmacologic response. To bridge this gap, we have developed a physiologically based PK/pharmacodynamic model for systemically administered mRNA-containing lipid nanoparticles (LNPs) in mice. This model accounts for the physiologic determinants of mRNA delivery, active targeting in the vasculature, and differential transgene expression based on nanoparticle coating. The model was able to well-characterize the blood and tissue PKs of LNPs, as well as the kinetics of tissue luciferase expression measured by ex vivo activity in organ homogenates and bioluminescence imaging in intact organs. The predictive capabilities of the model were validated using a formulation targeted to intercellular adhesion molecule-1 and the model predicted nanoparticle delivery and luciferase expression within a 2-fold error for all organs. This modeling platform represents an initial strategy that can be expanded upon and utilized to predict the in vivo behavior of RNA-containing LNPs developed for an array of conditions and across species.

Keywords: MT: Delivery Strategies; drug targeting; lipid nanoparticles; mRNA; nucleic acid delivery; pharmacodynamics; pharmacokinetics; physiologically based pharmacokinetics.

Graphical abstract

Figure 1

Structure of the PBPK model of LNPs (A) Whole body structure of the PBPK model. Venous blood flow is depicted in blue, arterial blood in red. The relative thickness of arrows to explicitly depicted organs is representative of relative blood flow. (B) Tissue-level model structure. LNPs in the tissue vasculature are able to enter the extravascular space either by non-specific uptake (CL_up) or via binding to target (K_D), followed by internalization (k_int). Internalized LNPs were assumed to be eliminated in a first-order process (k_deg). (C) Luciferase expression model. LNP degradation was assumed to drive the release of mRNA into the cytosol. mRNA elimination was assumed to be via a first-order process (k_mRNA). Intact mRNA was assumed to drive production of transgene in a tissue-specific manner (S_tissue) and luciferase signal was assumed to decay in a first-order manner (k_luc).

Figure 2

Model-estimated blood and tissue PK and kinetics of luciferase activity (luciferase assay in organ homogenates) following administration of bare LNPs Symbols represent observed data and lines represent model fitted profiles. PK measurements are depicted in red and luciferase activity is depicted in green. Data depicted as mean ± SEM. n = 3 mice/time point.

Figure 3

Model-estimated blood and tissue PK and kinetics of luciferase activity (BLI of intact organs) following administration of control IgG-LNPs Symbols represent observed data and lines represent model fitted profiles. PK measurements are depicted in red and luciferase activity is depicted in green. Data depicted as mean ± SEM. n = 3 mice/time point.

Figure 4

Model-fitted PK and luciferase expression (luciferase activity in organ homogenates) following administration of PECAM-targeted LNPs PK measurements are depicted in red and luciferase activity is depicted in green. Solid red lines represent model-fitted PK profiles and solid green lines represent model-fitted luciferase expression. Data depicted as mean ± SEM. n = 3 mice/time point.

Figure 5

Model predicted biodistribution (30 min after injection) and luciferase activity in organ homogenates (5 h after injection) of ICAM-targeted LNPs Predictions were made with no fitting of parameters and were able to describe both biodistribution and luciferase expression well. Data depicted as mean ± SEM. n = 3 mice/time point.