OPP001 📄 Overview A SaMD leveraging multimodal data (wearables, EHR, genomics, environmental) to create a personalized 'digital twin' that predicts individual health risks and suggests proactive, evidence-based interventions or alerts clinicians, aiming to prevent disease onset or progression. Key technologies: 👤 Target users: 👍 Benefits Early disease detection and intervention • Personalized preventative care strategies • Reduced healthcare burden and costs • Improved patient engagement and self-management • Enhanced clinical decision support Use bullets or new lines. 👎 Challenges Data privacy and security across diverse datasets • Model explainability and interpretability for clinical trust • Regulatory clearance for predictive diagnostics and interventions • Seamless integration with existing clinical workflows • Preventing alert fatigue for both patients and clinicians • Addressing data bias and ensuring equitable outcomes 📋 Regulatory & Validation Class II/III SaMD depending on predictive claims (e.g., diagnosis vs. risk assessment) • Need for robust clinical validation and performance metrics • Compliance with 'AI as a medical device' specific guidance (e.g., FDA AI/ML Action Plan) • Data governance and cybersecurity requirements (HIPAA, GDPR)