Framework for Review of Clinical Research Involving AI: Advancing Ethical Oversight in Clinical Research

Artificial intelligence is rapidly reshaping clinical research, but it also demands a more nuanced approach to ethical and regulatory review. In human participant research, AI introduces considerations that extend beyond traditional guidance, including algorithmic bias, shifting model behavior, questions of data identifiability, transparency, and the importance of ongoing human oversight. 

The Framework for Review of Clinical Research Involving AI helps address those questions by giving Institutional Review Boards (IRBs), sponsors, investigators, and research institutions a practical, structured approach to the ethical oversight of AI in clinical research.  

WCG contributed to this collaborative effort alongside the MRCT Center and a multi-stakeholder group with expertise in bioethics, clinical research, regulatory science, and AI technology. By bringing together a broad range of perspectives, the group developed a resource that supports consistent, transparent, and risk-informed review grounded in established ethical principles. 

What the AI Clinical Research Framework Provides for IRBs and Research Teams 

At its core, the framework is designed to help IRBs apply ethical and regulatory standards consistently across the AI lifecycle. It also serves as a practical resource for sponsors, investigators, and institutions designing or conducting clinical research involving AI. 

To support real-world review, it provides: 

• Decision pathways to guide ethical analysis. 

• Stage-specific review considerations across the research life cycle. 

• Clearly defined ethical domains to support risk-appropriate review. 

Together, these tools create a more consistent, practical approach to reviewing AI-driven clinical research, helping teams navigate emerging risks that don’t always fit neatly within traditional study designs while supporting sound, ethically grounded decision-making. 

WCG played an important role in ensuring that the process stayed grounded in real-world application. Drawing on direct experience reviewing complex protocols, WCG contributed practical insights into study design variability, evolving AI use cases, and the need for consistency across organizations. 

Overall, this effort reflects a collaborative, consensus-driven approach to strengthening ethical oversight as AI becomes more deeply integrated into clinical research. It gives IRBs, sponsors, investigators, and institutions a clearer way to apply established standards, helping innovation move forward while protecting participants, scientific integrity, and trust.