Photonics-integrated and AI-enhanced medical sensing: From molecular diagnostics to real-time cell therapy monitoring

Over the past two decades, photonic sensing has transitioned from laboratory concepts to clinically relevant tools for disease detection and treatment guidance, driven by the convergence of nanotechnology, artificial intelligence (AI), and advanced fabrication. Unlike recent reviews that focus narrowly on individual technologies, this Perspective synthesizes advances across silicon photonics, nanophotonics, and quantum platforms, highlighting their accelerating clinical translation. We present a unified framework showing how optical imaging, photoacoustic techniques, and quantum sensing address critical challenges in quality control, cell tracking, and toxicity monitoring-with particular emphasis on CAR-T cell therapy. The integration of microfluidics, AI-driven data analysis, and closed-loop therapeutic systems is enabling real-time, personalized interventions. However, we also provide a balanced assessment of the significant practical limitations of quantum and other emerging platforms, acknowledging that classical photonics remains sufficient and often more practical for most near-term applications. We further identify key translational barriers-including biocompatibility, regulatory pathways, system-level integration, surface fouling, reimbursement, and data integration-and propose strategies to overcome them. We conclude by defining four Grand Challenges for the next decade and presenting a technology roadmap with explicit timelines. The coming decade will likely see widespread clinical deployment of photonic sensors for point-of-care diagnostics, continuous monitoring, and image-guided interventions, including cell therapy workflows, ultimately improving patient outcomes.