Speaker
Description
mRNA-encoded therapeutics are emerging as a promising strategy for cancer treatment, yet the quantitative link between lipid nanoparticle (LNP) delivery, intracellular mRNA processing, and systemic protein exposure remains poorly defined. We present a multiscale physiologically based pharmacokinetic (PBPK) model that integrates a parsimonious LNP–mRNA trafficking and translation layer with a mechanistic antibody PBPK framework based on \cite{S19}, including FcRn recycling and two-pore tissue exchange \cite{C25}.
The model was calibrated and validated in mice using five literature datasets covering multiple mRNA-encoded anticancer therapeutics with diverse molecular weights, Fc properties, and LNP-mRNA formulations. It accurately reproduced plasma concentration-time profiles across single- and multi-dose regimens, while structural identifiability analysis supported robust estimation of the mRNA-related parameters \cite{C11}.
These results support the use of the model as a general platform to compare mRNA-LNP systems, investigate delivery and expression kinetics, and optimize dose scheduling for mRNA-encoded therapeutics.
The talk will present the model, its validation across diverse case studies, and will address the opportunities and current limitations of extending this parsimonious preclinical framework to non-human primates and humans, toward predictive tools for optimizing therapeutic kinetics and supporting individualized mRNA treatment strategies \cite{M09}.
Bibliography
@article{S19,
author = {Armin Sepp and Guy Meno-Tetang and Andrew Weber and Andrew Sanderson and Oliver Schon and Alienor Berges},
doi = {10.1007/s10928-019-09640-9},
issn = {15738744},
issue = {4},
journal = {Journal of Pharmacokinetics and Pharmacodynamics},
keywords = {AlbudAbTM,Albumin,Antibody,Domain antibody,Physiologically based pharmacokinetics},
month = {8},
pages = {339-359},
pmid = {31079322},
publisher = {Springer New York LLC},
title = {Computer-assembled cross-species/cross-modalities two-pore physiologically based pharmacokinetic model for biologics in mice and rats},
volume = {46},
year = {2019}
}
@article{C11,
author = {Oana Chiş and Julio R. Banga and Eva Balsa-Canto},
doi = {10.1093/bioinformatics/btr431},
issn = {1367-4811},
issue = {18},
journal = {Bioinformatics},
month = {9},
pages = {2610-2611},
title = {GenSSI: a software toolbox for structural identifiability analysis of biological models},
volume = {27},
year = {2011}
}
@article{C25,
author = {Elio Campanile and Elisa Pettinà and Stefano Giampiccolo and Lorena Leonardelli and Luca Marchetti},
doi = {10.64898/2025.12.20.695667},
issn = {2692-8205},
institution = {bioRxiv},
journal = {bioRxiv},
month = {12},
pages = {2025.12.20.695667},
publisher = {Cold Spring Harbor Laboratory},
title = {Physiologically Based Pharmacokinetic Modeling of mRNA-Encoded Therapeutics: A Multiscale Framework for LNP and Antibody Trafficking in Mice},
url = {https://www.biorxiv.org/content/10.64898/2025.12.20.695667v1 https://www.biorxiv.org/content/10.64898/2025.12.20.695667v1.abstract},
year = {2025}
}
@article{M09,
author = {Donald E. Mager and Sukyung Woo and William J. Jusko},
doi = {10.2133/DMPK.24.16},
issn = {1347-4367},
issue = {1},
journal = {Drug Metabolism and Pharmacokinetics},
keywords = {Allometric scaling,Cell life span models,Mechanism-based modeling,Pharmacodynamics, PD,Pharmacokinetics, PK,Receptor occupancy,Recombinant human erythropoietin, rHuEpo,Target-mediated drug disposition, TMDD},
month = {1},
pages = {16-24},
pmid = {19252333},
publisher = {Elsevier},
title = {Scaling Pharmacodynamics from In Vitro and Preclinical Animal Studies to Humans},
volume = {24},
url = {https://www.sciencedirect.com/science/article/abs/pii/S1347436715300793?via%3Dihub},
year = {2009}
}
