London: The integration of artificial intelligence (AI) into clinical trials has transformed healthcare by improving data analysis, predicting outcomes and accelerating drug development. However, this innovation comes with significant legal and ethical challenges, as AI systems rely heavily on vast clinical trial data sets, raising concerns about consent, data origin, and ethical standards, he says. GlobalData.
Transparency regarding data collection methods and anonymization is essential, especially when the data comes from third parties. While consent forms help describe the use of data during trials, ambiguity remains around the reuse of such data for AI purposes after trials have concluded.
Medical analysts at the 2024 Medtech Conference session, ‘Unlocking Health Data: Navigating the Legal Landmines for Innovation’, highlighted the pressing need for viable solutions. They emphasized that data ownership remains a gray area, often causing disputes between clinical trial sponsors, healthcare providers and AI developers.
Elia García, medical analyst at GlobalData, commented: “A clear ownership framework would not only promote transparency but also reduce conflicts over data sharing practices. Analysts also noted the importance of simplifying complex regulatory language to help healthcare providers understand and align with AI development goals.”
Cybersecurity is a major concern, as health data is highly susceptible to breaches, which could result in identity theft, fraud, and other serious risks. Ethical issues further complicate the picture; Misuse of health data can provoke negative public reactions and decrease trust in health care providers and artificial intelligence technologies.
Garcia concluded: “Addressing legal and ethical challenges in AI-powered clinical trials requires collaborative efforts between policymakers, healthcare providers, and AI developers. By adopting clear data ownership frameworks, improving communication and educating the public, the industry can address concerns while continuing to innovate. These measures, along with risk-based regulations, pave the way for a safe, ethical and progressive healthcare landscape powered by AI.”>
