{
  "abstract": "Abractst\n\nExtracellular vesicles (EVs) are promising therapeutic and diagnostic platforms, yet their clinical translation remains constrained by population heterogeneity, limited target-site retention, uncertain biodistribution, and variable potency. These persistent limitations have motivated the convergence of artificial intelligence (AI), biomaterials, synthetic biology, and advanced validation systems into what we describe as a next-generation EV framework. The evidence supporting these enabling technologies is, however, uneven. AI methods have demonstrated clear value for retrospective classification and feature discovery but have rarely been prospectively validated for therapeutic design; biomaterial carriers provide measurable gains in local retention and release control yet show inconsistent reporting of EV integrity, dose normalization, and controls; and programmable or trigger-responsive EV systems remain largely preclinical. A similar pattern is evident in the clinical landscape, where trial activity in EV-based interventions continues to grow but most studies remain in early or exploratory phases and no FDA-approved EV therapy is currently available. We therefore present next-generation EVs as an evidence-weighted translational agenda with future progress contingent on validated potency assays, reproducible manufacturing, predictable biodistribution, and a clear separation of demonstrated systems from longer-term concepts.",
  "abstract_shown": true,
  "affiliations": [
    "Clinical Research Center for Obstetrics and Gynecology, Key Laboratory of Maternal & Fetal Medicine of National Health Commission of China, Shandong Provincial Maternal and Child Health Care Hospital Affiliated to Qingdao University, Jinan, 250001, China.",
    "School of Public Health, North China University of Science and technology, Tangshan, 063200, China.",
    "School of Public Health, Shandong First Medical University, Jinan, 250001, China.",
    "Clinical Research Center for Obstetrics and Gynecology, Key Laboratory of Maternal & Fetal Medicine of National Health Commission of China, Shandong Provincial Maternal and Child Health Care Hospital Affiliated to Qingdao University, Jinan, 250001, China. zhanglin8901@sdu.edu.cn.",
    "Shandong Provincial Key Medical and Health Laboratory of Women's Occupational Exposure and Fertility Preservation, Jinan, 250001, China. zhanglin8901@sdu.edu.cn.",
    "Jinan (Preparatory) Key Laboratory of Women's Diseases and Fertility Preservation, Jinan, 250001, China. zhanglin8901@sdu.edu.cn."
  ],
  "article_type": "review article",
  "arxiv": null,
  "author_total": 9,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Jiaqi Tian"
    },
    {
      "affs": [
        0
      ],
      "name": "Qiang Li"
    },
    {
      "affs": [
        0
      ],
      "name": "Ning Li"
    },
    {
      "affs": [
        0
      ],
      "name": "Dandan Song"
    },
    {
      "affs": [
        1
      ],
      "name": "Zengfeng Li"
    },
    {
      "affs": [
        2
      ],
      "name": "Xiaotan Shi"
    },
    {
      "affs": [
        0
      ],
      "name": "Huiyu Sun"
    },
    {
      "affs": [
        2
      ],
      "name": "Shuyin Duan"
    },
    {
      "affs": [
        3,
        4,
        5
      ],
      "name": "Lin Zhang",
      "orcid": "0000-0002-5269-9728"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/0h1v7bq8wcznh.bib",
  "cited_by": 1,
  "doi": "10.1186/s12951-026-04831-2",
  "fulltext_url": "https://europepmc.org/articles/PMC13685389",
  "id": "0h1v7bq8wcznh",
  "issns": [
    "1477-3155"
  ],
  "landing_url": "https://europepmc.org/article/MED/42902374",
  "language": "eng",
  "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": [
    [
      "lcc",
      "R855-855.5"
    ],
    [
      "lcc",
      "TP248.13-248.65"
    ],
    [
      "openalex",
      "1312|Extracellular vesicles in disease"
    ]
  ],
  "openalex": "W7171159126",
  "pdf_url": "https://europepmc.org/articles/PMC13685389?pdf=render",
  "pmcid": "PMC13685389",
  "pmid": "42902374",
  "published": "2026-07-01",
  "publisher": "BMC",
  "ris": "https://research.draconitic.com/paper/0h1v7bq8wcznh.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:41Z",
      "native_id": "MED:42902374",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42902374"
    },
    {
      "first_seen": "2026-10-30T13:46:27Z",
      "native_id": "e0e0a998b42c40d091ec8d1b40637c20",
      "source": "doaj",
      "url": "https://doi.org/10.1186/s12951-026-04831-2"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Extracellular vesicles in disease",
      "subfield": "molecular-biology"
    }
  ],
  "title": "AI-guided design and biomaterial integration for next-generation extracellular vesicle therapeutics: an evidence-weighted translational framework.",
  "title_text": "AI-guided design and biomaterial integration for next-generation extracellular vesicle therapeutics: an evidence-weighted translational framework.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:46:27Z",
  "url": "https://research.draconitic.com/paper/0h1v7bq8wcznh",
  "venue": "Journal of nanobiotechnology",
  "versions": []
}