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Adv."],"published-print":{"date-parts":[[2026,10,23]]},"abstract":"<jats:p>\n                    Digital twin models can accelerate therapeutic development by enabling low-risk testing of candidate interventions. In preterm labor (PTL), a major pregnancy complication where clinical trials face ethical and financial barriers, digital twins are especially valuable for evaluating new therapies targeting immune dysfunctions driving PTL. Yet, current models lack single-cell resolution, limiting detection of cell type\u2013specific mechanisms, off-target effects, and the design of personalized interventions. We present Simulated Immunome Modeling of Clinical Outcomes (SIMCO), a single-cell\u2013level digital twin framework that models immunomodulatory treatment effects on the timing of labor using immunome-wide, single-cell simulations. SIMCO\u2019s digital twins are trained and validated on a newly generated mass cytometry atlas of the pregnant immunome exposed to nine candidate drugs preselected for PTL prevention. Applying SIMCO to an independent cohort of pregnant individuals, we simulate treatment effects on gestational length, screening for candidate drugs that delay labor timing and providing system-level mechanistic insight for each drug candidate. Tetrahydrofolate and the combination of aspirin and lansoprazole emerged as top candidates for PTL prevention, delaying labor onset primarily through enhanced mTOR signaling in innate immune cells and attenuated JAK\/STAT signaling in na\u00efve CD4\n                    <jats:sup>+<\/jats:sup>\n                    T cells.\n                  <\/jats:p>","DOI":"10.1126\/sciadv.aed2741","type":"journal-article","created":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T18:01:42Z","timestamp":1792605702000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark","source":"Crossref","is-referenced-by-count":1,"title":["Single-cell\u2013level digital twins for preterm birth prevention strategies"],"prefix":"10.1126","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3450-4325","authenticated-orcid":true,"given":"Jakob","family":"Einhaus","sequence":"first","affiliation":[{"name":"Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University 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