{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T06:47:55Z","timestamp":1774594075278,"version":"3.50.1"},"reference-count":61,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T00:00:00Z","timestamp":1774569600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Digit. Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Artificial intelligence (AI)-driven paediatric trials pose novel challenges for institutional review boards (IRBs), as traditional annual continuing review frameworks are often inadequate for evolving algorithmic and data-related risks. International and national regulations provide only limited guidance on how to design proactive, risk-sensitive interim oversight mechanisms for such research.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To develop and illustrate a risk-sensitive interim review model that strengthens participant protection and procedural fairness in AI-enabled paediatric research.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A conceptual normative analysis was conducted, integrating four ethical principles\u2014protection, proportionality, respect for autonomy and assent, and procedural justice\u2014with international guidelines [International Conference on Harmonisation\u2013Good Clinical Practice ICH-GCP, Council for International Organizations of Medical Sciences (CIOMS), and the Declaration of Helsinki] and Taiwanese regulations. From this synthesis, a five-component proactive interim review model was developed. To illustrate the model's practical application and feasibility, a Taiwanese IRB-mandated interim review of an AI-assisted pediatric speech-therapy trial (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009100, aged 3-7 years) is presented as a worked example rather than empirical data collection.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The model comprises five interlocking components: (1) scheduled, risk-based interim reviews and audits; (2) structured deviation-triggered response procedures; (3) mechanisms for re-consent and ongoing communication; (4) continuous ethics and protocol training; and (5) transparent, auditable documentation and IRB-investigator communication. Application of the proposed model to the Taiwanese worked example illustrates how a structured, risk-sensitive interim review process can support the identification of informed-consent and eligibility-screening deviations, facilitate targeted corrective training, and promote routine documentation monitoring.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>A proactive, risk-sensitive interim review model can support IRBs in shifting from reactive annual oversight to continuous, adaptive governance aligned with AI-specific risk profiles. The model offers a transferable, principle-based template for strengthening ethical oversight of AI-driven pediatric trials across diverse regulatory and cultural settings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fdgth.2026.1782692","type":"journal-article","created":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T05:19:22Z","timestamp":1774588762000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Ethical oversight of AI-driven paediatric trials: a proactive, risk-sensitive interim review model"],"prefix":"10.3389","volume":"8","author":[{"given":"Chih-Shung","family":"Wong","sequence":"first","affiliation":[{"name":"Department of Anesthesiology, Cathay General Hospital","place":["Taipei, Taiwan"]},{"name":"Department of CGHIRB, Cathay General Hospital","place":["Taipei, Taiwan"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tsui-Wen","family":"Hsu","sequence":"additional","affiliation":[{"name":"Institute of Medicine, Superintendent Office and CGHIRB, Cathay General Hospital","place":["Taipei, Taiwan"]},{"name":"School of Nursing, College of Medicine, Yuanpei University of Medical Technology","place":["Hsinchu, Taiwan"]},{"name":"School of Nursing, College of Medicine, Chang Jung Christian University","place":["Tainan, Taiwan"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2026,3,27]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1093\/bmb\/ldac038","article-title":"Children and bioethics: clarifying consent and assent in medical and research settings","volume":"145","author":"Spriggs","year":"2023","journal-title":"Br Med Bull"},{"key":"B2","doi-asserted-by":"publisher","first-page":"680","DOI":"10.5863\/1551-6776-28.8.680","article-title":"Ethics challenges in pediatric research","volume":"28","author":"Blake","year":"2023","journal-title":"J Pediatr Pharmacol Ther"},{"key":"B3","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1038\/s41746-025-01541-1","article-title":"Ethical considerations in AI for child health and recommendations for child-centered medical AI","volume":"8","author":"Chng","year":"2025","journal-title":"NPJ Digit Med"},{"key":"B4","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1038\/s41746-023-00898-5","article-title":"Recommendations for the use of pediatric data in artificial intelligence and machine learning ACCEPT-AI","volume":"6","author":"Muralidharan","year":"2023","journal-title":"NPJ Digit Med"},{"key":"B5","doi-asserted-by":"publisher","first-page":"636","DOI":"10.1038\/s41746-025-02000-7","article-title":"Toward governance of artificial intelligence in pediatric healthcare","volume":"8","author":"Richter","year":"2025","journal-title":"NPJ Digit Med"},{"key":"B6","doi-asserted-by":"publisher","first-page":"7","DOI":"10.2147\/AHMT.S185553","article-title":"Assent and consent in pediatric and adolescent research: school children\u2019s perspectives","volume":"10","author":"Al-Sheyab","year":"2019","journal-title":"Adolesc Health Med Ther"},{"key":"B7","doi-asserted-by":"publisher","first-page":"871","DOI":"10.3390\/healthcare9070871","article-title":"Children\u2019s understanding of informed assents in research studies","volume":"9","author":"Cotrim","year":"2021","journal-title":"Healthcare"},{"key":"B8","doi-asserted-by":"publisher","first-page":"106053","DOI":"10.1016\/j.clsr.2024.106053","article-title":"Assessing trustworthy AI: technical and legal perspectives of fairness in AI","volume":"55","author":"Kattnig","year":"2024","journal-title":"Comput Law Secur Rev"},{"key":"B9","doi-asserted-by":"publisher","first-page":"641","DOI":"10.3345\/cep.2025.00962","article-title":"Artificial intelligence in pediatric healthcare: current applications, potential, and implementation considerations","volume":"68","author":"Park","year":"2025","journal-title":"Clin Exp Pediatr"},{"key":"B10","doi-asserted-by":"publisher","first-page":"44432","DOI":"10.1038\/s41598-025-25266-z","article-title":"A validated framework for responsible AI in healthcare autonomous systems","volume":"15","author":"Alelyani","year":"2025","journal-title":"Sci Rep"},{"key":"B11","first-page":"78493","article-title":"Guidance on E11 clinical investigation of medicinal products in the pediatric population; availability. 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