(M-018) Construction of a Whole-Body Physiologically Based Pharmacokinetic (PBPK) Model to Facilitate the Design of LNP based mRNA Therapeutics for Secreted Protein Targets with Applications to Anti-Viral Therapies
Senior Scientist, Quantitative Systems Pharmacology Moderna, Inc. Malden, Massachusetts, United States
Disclosure(s):
Kenji Miyazawa: No financial relationships to disclose
Objectives: To develop a translational platform whole-body physiologically based pharmacokinetic (PBPK) model for bottom-up prediction of secreted protein dynamics for lipid nanoparticle (LNP)-mRNA therapeutics. The model explores key design factors affecting plasma protein levels and demonstrates application to anti-viral therapy development.
Methods: We previously used rat biodistribution data (Ci et al. 2023) to develop a whole-body PBPK model describing the biodistribution of mRNA and translated protein for an intracellular target (Miyazawa et al, 2024a, Miyazawa et al, 2024b). Building on this, we applied the two-pore formalism (Li et al., 2019) to extend the model to a secreted monoclonal antibody (mAb) encoded by mRNA. The model was scaled to humans, and local and global sensitivity analysis were conducted to identify mRNA design parameters modulating clinical exposure in humans. An HIV viral dynamics model (Stafford et al., 2000) was then integrated into the PBPK model and simulations were performed to explore optimal dosing regimen of the mRNA in inhibiting the viral load. Virtual patients were also generated for trial simulations to evaluate the efficacy of the encoded neutralizing mAb.
Results: The scaled model accurately predicted mRNA and protein PK in humans for the Chikungunya neutralizing mAb (August et al., 2021). Sensitivity analysis revealed that protein translation rate and mRNA/LNP stability in the liver were the most significant parameters for peak plasma protein exposure, while mRNA escape and cellular uptake rates had moderate effects. Interestingly, LNP liver tissue influx rate did not appreciably impact protein exposure. Moreover, mRNA stability in non-liver tissues had minimal impact on the encoded protein exposure. Partial rank correlation coefficient (PRCC)-based global sensitivity analysis confirmed the importance of these parameters. Furthermore, long term durability of mAb exposure was primarily driven by the mRNA translation rate, endosomal escape rate, degradation rate in the liver, and intrinsic vascular endothelial uptake rate of the encoded protein. The integrated PBPK-viral dynamics model demonstrated steep non-linear dose-response curve for the inhibition of the viral load. Sensitivity analysis demonstrated that aside from antibody potency, mRNA translation and LNP cellular uptake rates were the most critical mRNA design parameters for antiviral effect.
Conclusions: The whole-body PBPK model for mRNA encoded secreted proteins serve as a general translational platform for bottom-up prediction of mRNA and protein PK across species. Sensitivity analysis provided mechanistic insights into key mRNA design parameters modulating protein exposure. Application of the model to anti-viral therapeutics highlights the model’s utility in aiding the effective design of mRNA therapeutics for infectious diseases and de novo prediction of the effective dosing regimen for the suppression of viral load.
Citations: [1] Ci L, Hard M, Zhang H, et al. Biodistribution of Lipid 5, mRNA, and Its Translated Protein Following Intravenous Administration of mRNA-Encapsulated Lipid Nanoparticles in Rats. Drug Metab Dispos. 2023;51(7):813-823. doi:10.1124/dmd.122.000980 [2] Miyazawa K, Liu Y and Bazzazi H (2024a) Development of a minimal PBPK-QSP modeling platform for LNP-mRNA based therapeutics to study tissue disposition and protein expression dynamics. Front. Nanotechnol. 6:1330406. doi: 10.3389/fnano.2024.1330406 [3] Miyazawa, K., Ci, L., Bazzazi, H. (2024b, Nov 10-13). Development of a Whole-Body Physiologically Based Pharmacokinetics (PBPK) Model for Predicting Dynamics of mRNA and Protein for LNP-Encapsulated mRNA Therapeutics [Poster presentation]. American Conference on Pharmacometrics (ACoP15), Phoenix, Arizona. [4] Li Z, Shah DK. Two-pore physiologically based pharmacokinetic model with de novo derived parameters for predicting plasma PK of different size protein therapeutics. J Pharmacokinet Pharmacodyn. 2019;46(3):305-318. doi:10.1007/s10928-019-09639-2 Stafford MA, Corey L, Cao Y, Daar ES, Ho DD, Perelson AS. Modeling plasma virus concentration during primary HIV infection. J Theor Biol. 2000;203(3):285-301. doi:10.1006/jtbi.2000.1076 [5] August, A., Attarwala, H.Z., Himansu, S. et al. A phase 1 trial of lipid-encapsulated mRNA encoding a monoclonal antibody with neutralizing activity against Chikungunya virus. Nat Med 27, 2224–2233 (2021). https://doi.org/10.1038/s41591-021-01573-6
