{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T16:20:07Z","timestamp":1790612407019,"version":"4.1.0"},"reference-count":50,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2025,5,29]],"date-time":"2025-05-29T00:00:00Z","timestamp":1748476800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["ascpt.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Clin Pharma and Therapeutics"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:p><jats:italic>In silico<\/jats:italic> trials, utilizing mathematical models calibrated with clinical data, present a transformative approach to expedite drug development. We propose a virtual trial framework for chronic Hepatitis B, accurately simulating clinical protocols, patient characteristics, and endpoints using a mechanistic mathematical model. Clinical trial simulations with this model successfully captured functional cure with standard\u2010of\u2010care therapies (nucleos(t)ide analogs and pegylated interferon) as well as complex clinical observations, facilitating mechanistic hypothesis generation and suggesting biomarker signatures that may predict treatment outcomes. <jats:italic>In silico<\/jats:italic> trials revealed that responders exhibited enhanced cytotoxic immunity and significant serum\u2010alanine transaminase increases, suggesting a potential response biomarker. However, a higher baseline Hepatitis B surface antigen did not proportionately increase cytotoxic antiviral immune responses, indicating a potential immune ceiling but in the face of increasing systemic antigen burden, therefore culminating in a lower treatment response. Virtual patients enabled the generation of large virology biomarker synthetic datasets, which empowered a machine learning model to predict functional cure in virtual patients with ~\u200995% accuracy. This underscores the potential of <jats:italic>in silico<\/jats:italic> trials in enhancing clinical trials, generating mechanistic hypotheses, and accelerating chronic Hepatitis B drug development.<\/jats:p>","DOI":"10.1002\/cpt.3718","type":"journal-article","created":{"date-parts":[[2025,5,30]],"date-time":"2025-05-30T01:34:27Z","timestamp":1748568867000},"page":"600-612","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Hepatitis B <i>In Silico<\/i> Trials Capture Functional Cure, Indicate Mechanistic Pathways, and Suggest Prognostic Biomarker Signatures"],"prefix":"10.1002","volume":"118","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1501-8081","authenticated-orcid":false,"given":"Javiera","family":"Cort\u00e9s\u2010R\u00edos","sequence":"first","affiliation":[{"name":"Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences State University of New York at Buffalo  USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8483-8676","authenticated-orcid":false,"given":"Tianjing","family":"Ren","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences State University of New York at Buffalo  USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9528-6141","authenticated-orcid":false,"given":"Nathan","family":"Hanan","sequence":"additional","affiliation":[{"name":"Clinical Pharmacology Modelling &amp; 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