I-Corps: Translation Potential of a Living Labs Platform for Accelerating Clinical and Behavioral Research

This I-Corps project is based on the development of a digital software platform for healthcare research. Researchers currently face obstacles that limit innovation including high costs, fragmented tools, and technological complexity when conducting real-world studies. This technology addresses the inefficiencies and technical barriers that hinder traditional clinical studies by providing an integrated, intuitive system that automates data collection, participant engagement, and real-time analysis. The solution is designed to enable research teams to deploy advanced digital health studies without writing a set of instructions (computer code) or building custom infrastructure. In addition, the solution includes wearable sensor technology, behavior-triggered surveys, and artificial intelligence (AI) analytics to support dynamic, adaptive clinical research. The technology may enhance study accuracy, efficiency, and participant adherence, which may lead to faster and more effective healthcare solutions.

This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of a digital research software platform that integrates multimodal data collection, intelligent intervention delivery, and real-time analytics. The technology is a no-code, closed-loop system that utilizes context-aware mobile health technologies, wearable device streams, and advanced machine learning models to facilitate predictive analytics and adaptive study management. Compared with current technology that is often siloed or requires manual integration, this system centralizes control through a unified interface while allowing for complex study design without coding expertise. In addition, the solution includes automated adherence tracking, environmental and behavioral context sensing, and scalable data pipelines that support real-world evidence generation. The technology’s artificial intelligence (AI)-driven insights enable researchers to detect anomalies, monitor trends, and personalize interventions, resulting in more relevant and actionable health data. The technology may be used to advance the scientific understanding of how environmental, physiological, and behavioral data can be harnessed together to inform healthcare interventions and decision-making. This integration may provide an adaptable tool for advancing clinical research and accelerating the translation of scientific discovery into real-world health impact.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Award Number: 2525858
Principal Investigator: Amir Rahmani
Funds Obligated: $50,000
State: CA