OPP002 📄 Overview An AI-driven SaMD that analyzes a patient's multi-omics data (genomic, proteomic, metabolomic), medical history, and baseline imaging to predict the likelihood of positive response to specific regenerative cell therapies and anticipate potential adverse reactions. The tool provides a personalized risk-benefit profile to guide clinician decision-making. Key technologies: 👤 Target users: 👍 Benefits Improves treatment success rates by optimizing patient selection • Reduces costs associated with non-responders and adverse events • Accelerates clinical trial recruitment for specific patient profiles • Enhances patient safety through proactive risk assessment • Personalizes treatment strategies Use bullets or new lines. 👎 Challenges Availability and quality of large, diverse multi-omics datasets • Ethical considerations regarding AI-driven patient selection and bias • Explainability and interpretability of AI predictions for clinicians • Regulatory approval for a diagnostic/prognostic SaMD 📋 Regulatory & Validation Likely Class IIb or III SaMD due to its prognostic/diagnostic claims impacting treatment decisions. • Requires extensive clinical validation with diverse patient cohorts. • Focus on transparency, explainability, and bias mitigation in AI algorithms will be critical for approval.