Secure AI Readiness for Molecular Precision Medicine Supply Chains in Egypt: A Monte Carlo Workflow Simulation

This computational study evaluates four molecular precision-medicine supply chain scenarios: baseline, AI only, traceability and security only, and secure AI integration. Each scenario was replicated 400 times under stochastic workflow complexity and sample volume. Relative to baseline, secure AI integration reduced mean turnaround time by 35.2%, chain-of-custody failures by 63.1%, data-integrity incidents by 68.2%, and the cost index by 11.5%, while increasing diagnostic completion by 12.6%. AI alone shortened turnaround and improved completion but did not reduce custody or data-integrity incidents, illustrating the modeled need for security and traceability. Results validate a workflow-simulation architecture and are not clinical evidence or estimates of Egyptian molecular-medicine capacity. Keywords: precision medicine; artificial intelligence; traceability; cybersecurity; Monte Carlo simulation; Egypt