OPP001 📄 Overview A comprehensive, continuously updated digital representation of an individual's health, integrating data from wearables, EHRs, genomics, environmental factors, and lifestyle inputs. AI/ML algorithms analyze this 'digital twin' to predict future health risks (e.g., onset of chronic disease, acute exacerbations, mental health decline) and proactively recommend hyper-personalized preventative interventions (e.g., specific dietary adjustments, exercise routines, stress management techniques, virtual coaching, early screening reminders). This SaMD would provide personalized risk scores and actionable insights for prevention. Key technologies: 👤 Target users: 👍 Benefits Significant reduction in chronic disease incidence • Personalized preventative care at scale • Empowered individuals with actionable health insights • Improved population health and reduced healthcare burden Use bullets or new lines. 👎 Challenges Data privacy and security at scale • Interoperability across disparate data sources • Clinical validation of predictive accuracy and intervention efficacy • User adoption and sustained engagement with personalized recommendations • Addressing algorithmic bias in diverse populations 📋 Regulatory & Validation Likely Class II SaMD for risk prediction and personalized recommendations • Robust data governance and privacy compliance (HIPAA, GDPR) • Transparency requirements for AI algorithms