Amplifying missing voices in healthcare research: an AI framework for co-production of PPIE

Patient and Public Involvement and Engagement (PPIE) is essential for high-quality healthcare research, yet significant challenges persist in achieving diverse input. Traditional PPIE panels can struggle with recruitment limitations, geographical constraints, and resource intensity, resulting in panels that may not reflect population diversity or lived experiences. In order to address these challenges, we developed Panelyze, an AI-powered co-production system to augment existing PPIE approaches. Panelyze follows a five-step workflow: (1) programmatic generation of synthetic personas and panels based on census data and lived experiences; (2) semantic analysis of research proposals; (3) generation of the synthetic panel's discussions; (4) generation of PPIE co-production artefacts (e.g., Plain English Summaries, Infographics); and (5) generation of the Panelyze Score, a novel algorithmic metric evaluating healthcare proposals against UK Standards for Public Involvement. We validated the system using the CAPRIE-2 cardiovascular research proposal. Results demonstrated the system's capacity to simulate qualitative dialogue, identifying critical socio-economic barriers (e.g., wage loss from clinic visits) and validating terminology choices (e.g., drug naming conventions). Critically, the system functions as an augmentation tool, enabling research leads to stress-test and refine their proposals against a synthetic audience. This process amplifies missing voices rarely heard in physical meetings and generates accessible materials that facilitate easier adoption and higher-quality engagement for subsequent human panels.