Making responsible AI and advanced technologies operational in health research: the design and first national application of the Global Ethics and Regulatory Preparedness (GERP) method

Abstract Artificial intelligence and other advanced technologies are entering health research faster than the systems that oversee it can adapt. Two reform movements respond. A global movement runs through the World Health Organization’s action plan for clinical trial ecosystem strengthening and its good reliance practices. A European movement runs through the European Health Data Space and the Artificial Intelligence Act. In 2026 the World Health Organization added a report on the ethics review and oversight of artificial-intelligence-related health research. Guidance is now abundant. Method is scarce. This paper presents the Global Ethics and Regulatory Preparedness method (GERP), a proposed operational method rather than a further set of principles, and reports its first application. GERP has a modular design: a common core, a developed module for artificial intelligence and one for data visitation, and named modules for software as a medical device, genomics and biobanking, and digital twins. Its core components are an auditable evidence base built on a typed source register and mandatory human validation; a two-stage classification that separates legal applicability from research-ethics risk; two parallel preparedness domains, one for ethics oversight and one for regulation, each read against an established World Health Organization benchmark; and operational human oversight with a distributed accountability map. The method was stress-tested in a three-jurisdiction proof-of-method across Belgium, the United States, and Indonesia, which produced binding revisions, and was first appliied at country level in Indonesia, where the draft instruments for ethics committees and the national regulator await national validation. The paper is explicit about what has and has not been shown, and sets ou the validation still required.