Advancing Synthetic R&D Through Scenarios: Integrating Science, Technology, and Stakeholder Needs

Bridging the gap between scientific knowledge and practical application remains a central challenge in research and development (R&D). Analytical R&D generates factual knowledge through established methodologies, whereas synthetic R&D integrates this knowledge with technological and practical insights to produce artifacts and solutions. Despite its importance, synthetic R&D has lacked a coherent methodological foundation, limiting its broader recognition and systematic practice. We develop and demonstrate a scenario-based methodology that provides a structured framework for synthetic R&D. A scenario is defined as a development pathway that systematically links scientific understanding to clearly defined application objectives. By defining internal and external scenario structures, the framework enables systematic planning, execution, and evaluation of projects. Scenarios also serve as boundary objects, facilitating collaboration and communication across different disciplines and organizations. The originality of this study lies in transforming previously implicit or fragmented practices into a systematic, reproducible, and evaluable process. The methodology is validated through empirical case studies: nanomaterials standardization, deployment of ear thermometers during public health emergencies, and geochemical mapping for environmental policy. These cases illustrate how structured scenarios support knowledge integration, enhance adaptability across technical domains, and generate outcomes with demonstrable industrial and societal value. These findings suggest that scenario-based approaches provide a robust, generalizable foundation for advancing synthetic R&D in parallel with analytical R&D.