Antibody-based therapeutics has revolutionized disease treatment, and recent advances in messenger RNA (mRNA) technologies have opened new opportunities for their intracellular production. In particular, in vitro-transcribed mRNA encapsulated in lipid nanoparticles (LNPs) enables targeted delivery to specific cells, where it can enable the synthesis of therapeutic antibodies with prolonged half-lives in a cost-effective manner. Despite rapidly growing experimental data, a modeling framework that integrates mRNA delivery, intracellular expression kinetics, and whole-body antibody disposition remains unavailable. To address this gap, we extended a physiologically based pharmacokinetic model with a novel multiscale layer describing mRNA trafficking, cellular uptake, translation, and degradation. The integrated model was calibrated and validated using five datasets of mRNA-based cancer therapeutics, demonstrating strong predictive performance for the biodistribution of mRNA-encoded antibodies. The newly introduced mRNA layer, while minimally parameterized, effectively represents complex intracellular and systemic processes, enabling quantitative investigation of antibody biodistribution, optimization of dose scheduling, and providing an initial framework for future exploration of how LNP-mRNA formulation influences delivery and pharmacokinetics.

Physiologically based pharmacokinetic modeling of mRNA therapeutics: A multiscale framework for LNP and antibody trafficking in mice / Campanile, E., Pettinà, E., Giampiccolo, S., Leonardelli, L., Marchetti, L.. - In: MOLECULAR THERAPY NUCLEIC ACIDS. - ISSN 2162-2531. - 37:3(2026), pp. 10300201-10300213. [10.1016/j.omtn.2026.103002]

Physiologically based pharmacokinetic modeling of mRNA therapeutics: A multiscale framework for LNP and antibody trafficking in mice

Campanile, Elio;Pettinà, Elisa;Giampiccolo, Stefano;Leonardelli, Lorena;Marchetti, Luca
2026-01-01

Abstract

Antibody-based therapeutics has revolutionized disease treatment, and recent advances in messenger RNA (mRNA) technologies have opened new opportunities for their intracellular production. In particular, in vitro-transcribed mRNA encapsulated in lipid nanoparticles (LNPs) enables targeted delivery to specific cells, where it can enable the synthesis of therapeutic antibodies with prolonged half-lives in a cost-effective manner. Despite rapidly growing experimental data, a modeling framework that integrates mRNA delivery, intracellular expression kinetics, and whole-body antibody disposition remains unavailable. To address this gap, we extended a physiologically based pharmacokinetic model with a novel multiscale layer describing mRNA trafficking, cellular uptake, translation, and degradation. The integrated model was calibrated and validated using five datasets of mRNA-based cancer therapeutics, demonstrating strong predictive performance for the biodistribution of mRNA-encoded antibodies. The newly introduced mRNA layer, while minimally parameterized, effectively represents complex intracellular and systemic processes, enabling quantitative investigation of antibody biodistribution, optimization of dose scheduling, and providing an initial framework for future exploration of how LNP-mRNA formulation influences delivery and pharmacokinetics.
2026
3
Campanile, Elio; Pettinà, Elisa; Giampiccolo, Stefano; Leonardelli, Lorena; Marchetti, Luca
Physiologically based pharmacokinetic modeling of mRNA therapeutics: A multiscale framework for LNP and antibody trafficking in mice / Campanile, E., Pettinà, E., Giampiccolo, S., Leonardelli, L., Marchetti, L.. - In: MOLECULAR THERAPY NUCLEIC ACIDS. - ISSN 2162-2531. - 37:3(2026), pp. 10300201-10300213. [10.1016/j.omtn.2026.103002]
File in questo prodotto:
File Dimensione Formato  
Campanile2026.pdf

accesso aperto

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Creative commons
Dimensione 3.3 MB
Formato Adobe PDF
3.3 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/502731
Citazioni
  • ???jsp.display-item.citation.pmc??? 1
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
  • OpenAlex ND
social impact