Sep 2026· American Medical Writers Association AMWA journal· Vol 41· 0 citations
TL;DR
Five integrated competencies define the evolving role: technology and risk assessment, workflow design, systematic quality assurance, data literacy, and extended cross functional leadership and accountability in regulatory medical writing.
Abstract
Concerns that artificial intelligence (AI) will displace regulatory medical writers or reduce their role to prompt engineering persist in the field, but emerging enterprise deployments and regulatory developments suggest a more nuanced trajectory. Early enterprise implementations show AI accelerating drafting while increasing demand for validation and oversight expertise. Regulatory signals, including the Food and Drug Administration’s (FDA’s) 2025 credibility framework, joint FDA European Medicines Agency (EMA) principles, and the European Union AI Act, place account ability for AI-assisted content on sponsors and their teams. Five integrated competencies define the evolving role: technology and risk assessment, workflow design, systematic quality assurance, data literacy, and extended cross functional leadership and accountability. As routine drafting is increasingly automated, professional value in regulatory medical writing shifts toward governance, validation, and strategic oversight. These build on, rather than replace, traditional medical writing foundations.
The RACP advocates for physicians to engage in AI development and implementation using an agile human-in-the-loop approach that prioritises patient safety, clinical governance, professional training and collaboration with stakeholders.
Ian A. Scott, Christian White, Tim Shaw et al.· Internal medicine journal (P...· 0 citations
The integration of artificial intelligence (AI) models into clinical trials has accelerated significantly over the past decade, offering substantial potential to optimise patient recruitment, endpoint analysis, and pharmacovigilance. However, this integration also introduces a complex web of regulatory and ethical risk...
Filip Radonić· ZBORNIK RADOVA UNIVERZITETA...· 0 citations
Background Artificial intelligence (AI) is increasingly integrated into medical imaging and radiology research, improving image acquisition, interpretation, workflow efficiency, and decision support. However, its rapid adoption has introduced complex legal and regulatory challenges involving patient privacy, data gover...
Umamaheswara Reddy V., Susmitha S. L. N.· Indian Journal of Radiology...· 0 citations
This review addresses the primary ethical principles relevant to AI in medicine - including respect for patient autonomy, beneficence, non-maleficence, and justice - alongside key legal frameworks with respect to liability, data protection, regulatory compliance, and algorithmic transparency.
Sebastian Schleidgen, O. Friedrich· European journal of internal...· 0 citations
A compliance-by-design framework is proposed that translates overlapping legal requirements into a set of auditable governance artefacts covering system classification, regulatory mapping, data governance, validation, human oversight, conformity assessment, post-market monitoring, and change control.
Qaiser Khan, A. Saeed· Frontiers in Digital Health· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.