ReviewJournal of patient-reported outcomes2026
Use of AI within COA linguistic validation and eCOA migration processes: analysis and good practice recommendations.
Review in Journal of patient-reported outcomes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWhile there has been much discussion around the use of Artificial Intelligence (AI) for multilingual translations in other areas, recommendations pertaining specifically to the use of AI in the context of Clinical Outcome Assessment (COA) translation, linguistic validation, and electronic migration within clinical trials are lacking. Without published recommendations or guidelines, stakeholders involved in the COA translation process may be hesitant to explore or include AI. To address this gap, the AI Working Group of the ISOQOL TCA-SIG conducted a study to assess the landscape of AI in this specific context aimed at proposing recommendations for potential implementation of AI in COA translation, linguistic validation and electronic migration processes. METHODOLOGY: The study consisted of three parts: (1) a literature review targeting studies using AI in COA translation; (2) a survey among relevant stakeholders assessing perceptions of AI use in COA translation; and (3) interviews with AI subject matter experts (SMEs).
resultsSurvey responses were received from a total of 50 individuals from a wide variety of stakeholder groups, including COA copyright holders, representatives from pharmaceutical company COA/HEOR teams, respondents holding roles associated with the COA translation, eCOA, and AI industries, and authors of the 2005 ISPOR task force article on linguistic validation methodology. Survey data provided detailed feedback regarding the appropriateness of using AI during all reviewed process steps. Results of the literature review and AI expert interviews provided additional depth and nuance, allowing for the generation of detailed recommendations covering the use of AI within linguistic validation and eCOA migration processes.
conclusionsWhen assessing the potential use of AI tools within the linguistic validation process, it is important to consider not only the capabilities of the technology, but also the degree to which use of AI may or may not align with the spirit and intent of existing linguistic validation guidelines. The recommendations included in this manuscript are designed to balance considerations of technological capability and improved efficiency with concerns related to intellectual property protection, data privacy/security, and the goal of keeping patients at the center of outcomes research.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.