{
  "abstract": "mRNA-based therapeutics have emerged as a transformative class of medicines, yet their translation beyond infectious disease vaccines remains challenged by the absence of an integrated pharmacological framework accounting for the tri-component nature of these therapies - the lipid nanoparticle, the mRNA, and the expressed protein. Here, we present a modular, multiscale computational platform integrating two complementary mechanistic models covering the full pharmacological cascade of mRNA-based immunotherapies. The first is a Quantitative Systems Pharmacology (QSP) model describing the immunological response to mRNA vaccines, from antigen expression in antigen-presenting cells through B cell activation and circulating antibody production. The second is a Physiologically Based Pharmacokinetic (PBPK) model tracking whole-body disposition of mRNA-encoded therapeutic antibodies, incorporating a molecular layer resolving LNP uptake, endosomal mRNA escape, and intracellular translation. Both models are informed by a machine learning pipeline that maps IVT-mRNA nucleotide sequences directly onto kinetic parameters, enabling product-specific model simulations. We propose this platform as a step toward the quantitative pharmacological framework that mRNA therapeutics currently lack, and as a practical tool for model-informed design and development of this therapeutic class.",
  "abstract_shown": true,
  "affiliations": [
    "University of Trento"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "name": "E. Pettina"
    },
    {
      "name": "F. A. Chahine"
    },
    {
      "name": "E. Campanile"
    },
    {
      "name": "S. Giampiccolo"
    },
    {
      "affs": [
        0
      ],
      "name": "L. Marchetti"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/2t8yxqxrbm9k2.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.08.25.26361215",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.08.25.26361215v1.full",
  "id": "2t8yxqxrbm9k2",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.08.25.26361215v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "pharmacology and therapeutics"
    ],
    [
      "openalex",
      "1312|RNA Interference and Gene Delivery"
    ]
  ],
  "openalex": "W7204524106",
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.08.25.26361215v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-08-25",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/2t8yxqxrbm9k2.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:30Z",
      "native_id": "10.64898/2026.08.25.26361215",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.08.25.26361215v1"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:pharmacology and therapeutics",
      "subfield": "pharmacology-toxicology"
    }
  ],
  "title": "Towards a ML-powered Multiscale Computational Platform Based on QSP and PBPK Modeling to Support the Development of mRNA-based Therapies",
  "title_text": "Towards a ML-powered Multiscale Computational Platform Based on QSP and PBPK Modeling to Support the Development of mRNA-based Therapies",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:30Z",
  "url": "https://research.draconitic.com/paper/2t8yxqxrbm9k2",
  "venue": "medRxiv",
  "versions": []
}