10171314Development of a Quantum AI Probabilistic Simulation Engine for use in conjunction with a mobile application for Forecasting Long term Health TrajectoriesClosedFast Start ResponseInnovate UKThis project will develop a probabilistic simulation engine capable of forecasting changes in individual health profiles over time, based on early trends in routinely collected physiological data. Rather than relying on fixed medical thresholds or reactive symptom tracking, the proposed system will model health as a dynamic, evolving process capturing gradual changes that may indicate increased risk well before a clinical diagnosis is made. The innovation lies in the project's emphasis on _longitudinal forecasting_. Health data such as lab tests, wearables, or lifestyle metrics are often collected over months or years. However, most current systems analyse these data points in isolation. This project will instead create a framework for analysing how a biomarker change over time within an individual, identifying subtle patterns that invariably precede health deterioration or resilience. The simulation engine will be designed to produce non-diagnostic, personalized health forecasts that offer probabilistic insight into potential future outcomes. These forecasts will be accompanied by explanatory trends and scenario-based projections to help users and practitioners explore how different factors such as improved sleep, physical activity, or nutrition may alter a person's future health trajectory. The tool is being developed for wellness, research, and preventative health use cases. It will not make clinical decisions or provide treatment advice. Instead, it is intended to support proactive health planning, digital monitoring programs, and early-stage risk awareness initiatives. The engine will be designed to integrate securely with anonymized or consent-based data streams, including wearables, periodic blood tests, and other validated health data sources. This work contributes to the emerging field of preventative digital health, where the goal is to shift the focus from late-stage treatment to early understanding and long-term well-being. The platform developed through this project will aim to support applications in chronic disease prevention, aging and longevity strategies, remote care pathways, and population-level analytics. No proprietary methods or commercially sensitive implementation details are disclosed in this public description. By making health trajectories more visible, navigable, and individually meaningful, this project aims to empower individuals and systems alike to move from reaction to foresight in healthcare.