Quantum-Inspired Design of Multi-Functional Nanomaterials for Simultaneous Imaging, Diagnosis, and Therapy (Theranostics)

Abstract

The integration of imaging, diagnosis, and therapy into unified theranostic platforms has become a central objective in next-generation nanomedicine. However, the design of multifunctional nanomaterials capable of performing these tasks efficiently remains limited by the complexity of nanoscale interactions, nonlinear structure–property relationships, and the combinatorial nature of material optimization. This study explores a quantum-inspired computational framework for guiding the design of theranostic nanomaterials, leveraging quantum-inspired annealing, tensor network representations, and high-dimensional optimization inspired by quantum mechanics. By applying these techniques, the framework accelerates the discovery of optimal nanostructures, surface chemistries, and functional moieties for enhanced contrast imaging, targeted drug delivery, photothermal and photodynamic therapy, and real-time diagnostic monitoring. Simulation-based experiments demonstrate that quantum-inspired methods outperform classical heuristics in identifying candidate materials with superior energy absorption, signal-to-noise ratios, and therapeutic precision. The results highlight the transformative potential of quantum-inspired design for advancing multifunctional theranostic systems, enabling personalized, high-efficiency medical interventions.