Integration of Biophotonics with Bone-on-Chip Technology for Continuous, Non-Invasive Monitoring of Bone Regeneration

Abstract

The need for non-invasive, real-time, continuous monitoring tools in bone regeneration is essential to improve early diagnosis and therapeutics. Bone-on-chip (BOC) platforms which replicate physiological microenvironments are a useful component within this context. Their integration with biophotonics-based imaging techniques marks a significant advancement in preclinical bone research. For the first time, this review explores how biophotonics can be utilised to improve the accuracy and efficiency of BOC-based studies. As the demand for predictive models that closely mimic bone healing increases, BOCs offer a robust alternative to traditional in-vitro and in-vivo models by combining microfluidics and advanced biomaterials to mimic native bone physiology. We discuss a range of optical methods; including Raman spectroscopy, optical coherence tomography (OCT), second harmonic generation (SHG), and diffuse correlation spectroscopy (DCS), which improve the spatiotemporal resolution of osteogenic processes. Additionally, photoacoustic imaging and near-infrared spectroscopy (NIRS) facilitate deep tissue penetration and vascular assessment. Incorporation of artificial intelligence (AI) and machine learning (ML) within BOC platforms enable automated, high-throughput analysis of real-time datasets, for optimised bone regeneration. Collectively, this review highlights how biophotonics, advanced biomaterials and computational modelling improves the translational potential of BOCs. By establishing multimodal, data-driven monitoring methods, these platforms offer strong potential for advancements in preclinical research and therapeutics development.