OPP002 📄 Overview A dynamic, virtual representation (digital twin) of an individual patient's physiological and health state, continuously updated with real-time data from wearables, EHRs, and patient-reported outcomes. This SaMD-enabled platform would simulate the effects of various treatment adjustments, lifestyle changes, or interventions, providing personalized, predictive decision support for both patients and clinicians to optimize chronic disease management. Key technologies: 👤 Target users: 👍 Benefits Optimized and personalized treatment regimens • Reduced trial-and-error in medication dosing/lifestyle changes • Empowered patient self-management through 'what-if' scenarios • Improved clinician decision-making & reduced workload • Better control of disease progression & fewer complications Use bullets or new lines. 👎 Challenges Complexity of data integration and interoperability across systems • Computational power required for real-time simulations • Clinical validation of simulation accuracy and predictive power • Ethical considerations around AI-driven treatment recommendations • Achieving regulatory clearance as a high-risk SaMD 📋 Regulatory & Validation Likely Class II or III SaMD due to diagnostic/treatment decision support. • Rigorous validation required for predictive models and simulations. • Clear documentation of model limitations and intended use cases.