Autonomy, Trust, and Stewardship: Centering Participants in AI-Enabled Trial Matching.
The article focuses on the ethical considerations and practical implications of using artificial intelligence (AI) as a tool for clinical research recruitment, specifically in trial matching and recruitment processes. It distinguishes between participant-to-trial matching, where individuals or clini...
| Publicado en: | American Journal of Bioethics Vol. 26; no. 8; pp. 49 - 53 |
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| Autores principales: | , , , |
| Formato: | commentary Journal Article |
| Publicado: |
Taylor & Francis Ltd
Aug2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=195895407&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 195895407 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15265161 FKZ jtl: American Journal of Bioethics issn: 15265161 maglogo: N pubinfo: dt: Aug2026 vid: 26 iid: 8 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 195895407 195895407 195895407 10.1080/15265161.2026.2692310 195895407 ppf: 49 ppct: 4 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Autonomy, Trust, and Stewardship: Centering Participants in AI-Enabled Trial Matching. aug: au: Heidelberg, Melissa Kultgen, Benjamin Butler, Kelly K. Bott, Nicholas T. affil: Takeda Pharmaceuticals sug: subj: Research, Medical Clinical Trials Artificial Intelligence Utilization Research Subjects Patient Autonomy Trust Data Security Artificial Intelligence Ethical Issues Research Subject Recruitment Cost Savings Ecosystem Privacy and Confidentiality Digital Health Bioethics ab: The article focuses on the ethical considerations and practical implications of using artificial intelligence (AI) as a tool for clinical research recruitment, specifically in trial matching and recruitment processes. It distinguishes between participant-to-trial matching, where individuals or clinicians seek relevant trials using AI tools, and trial-to-participant matching, where researchers or sponsors identify eligible participants through AI-enabled data analysis. The discussion emphasizes situating AI trial matching within a broader ecosystem involving data stewardship, institutional coordination, participant autonomy, and public trust, highlighting the importance of transparency, meaningful consent, fairness, and oversight. The article also notes the growing role of AI in accelerating trial enrollment, reducing costs, and potentially improving inclusivity in clinical research, while underscoring the need for responsible deployment aligned with bioethical principles and regulatory compliance. pubtype: Academic Journal doctype: commentary Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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