{
  "abstract": "Rare diseases represent a major unmet medical need, yet the development of therapeutics for these diseases is limited by small patient cohorts, fragmented data, and uncertain disease mechanisms. Recent advances that combine patient-derived induced pluripotent stem cell (iPSC) models with multi-omics profiling and artificial intelligence offer a robust approach for phenotype definition and drug target identification that requires only minimal patient material. By integrating transcriptomic, proteomic, and metabolomic data, machine learning can produce disease-relevant molecular signatures, identify convergent pathway drivers, and prioritize druggable targets despite limited sample sizes. This short review highlights emerging in vitro models and AI-enabled workflows, discusses their strengths and limitations, and outlines practical strategies to accelerate drug discovery for rare diseases.",
  "abstract_shown": true,
  "affiliations": [
    "National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD 20892, USA"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Soukaina Amniouel"
    },
    {
      "affs": [
        0
      ],
      "name": "Zeenat A. Shyr"
    },
    {
      "affs": [
        0
      ],
      "name": "Ewy A. Mathé"
    },
    {
      "affs": [
        0
      ],
      "name": "Wei Zheng"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/c3w8vas4ksap7.bib",
  "cited_by": 0,
  "doi": "10.1016/j.drudis.2026.104836",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13714977/",
  "id": "c3w8vas4ksap7",
  "issns": [
    "1359-6446",
    "1878-5832"
  ],
  "landing_url": "https://doi.org/10.1016/j.drudis.2026.104836",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Article"
    ],
    [
      "openalex",
      "1312|Pluripotent Stem Cells Research"
    ]
  ],
  "openalex": "W7222449676",
  "pdf_url": null,
  "pmcid": "PMC13714977",
  "pmid": "42887874",
  "published": "2026-10-16",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/c3w8vas4ksap7.ris",
  "sources": [
    {
      "first_seen": "2026-11-01T12:22:22Z",
      "native_id": "PMC13714977",
      "source": "pmc",
      "url": "https://doi.org/10.1016/j.drudis.2026.104836"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Pluripotent Stem Cells Research",
      "subfield": "molecular-biology"
    }
  ],
  "title": "AI-integrated iPSC multi-omics: advancing phenotype discovery and drug target identification in rare diseases",
  "title_text": "AI-integrated iPSC multi-omics: advancing phenotype discovery and drug target identification in rare diseases",
  "type": "peer-reviewed",
  "updated_at": "2026-11-01T12:22:22Z",
  "url": "https://research.draconitic.com/paper/c3w8vas4ksap7",
  "venue": "Drug discovery today",
  "versions": []
}