The Hong Kong Polytechnic University (PolyU) reported an AI “Virtual Patient” simulation system that integrates multimodal patient data to personalize cancer monitoring and treatment evaluation. The platform is described as a digital-twin approach, using genomic information and clinical measures to generate patient-specific modeling outputs. The report frames the system as a way to help clinicians interpret disease trajectories more consistently by consolidating disparate datasets into a single simulation layer. For biotech, the key product question is whether the virtual outputs can correlate with response and safety signals robustly across patient subgroups. Validation against prospective cohorts and integration into clinical workflows will likely determine adoption potential. If successful, the system could support more precise treatment adjustments in oncology, reducing reliance on sparse imaging intervals and delayed readouts.