Next-Generation Raman Spectroscopy Utilizing AI: From High-Throughput Platforms to Endoscopic Probes for Clinical Translation

Raman spectroscopy has become a powerful tool in biomedicine, offering label-free molecular insights with direct clinical relevance. To unlock its potential, the focus lies on translating it into deployable systems that provide rapid results at the patient’s side. Artificial intelligence (AI) is key, enabling robust interpretation of complex spectra and turning Raman from a research method into a clinical decision-making technology.

We present three translational Raman approaches. First, a high-throughput Raman blood analysis platform enables rapid molecular fingerprinting of large patient cohorts. Combined with advanced AI, it opens new opportunities for systemic disease monitoring, therapy guidance, and fast detection of infectious agents—crucial for timely treatment in sepsis and other acute infections.

Second, the Raman invaScope, a regulatory-compliant endoscopic system, has been validated intraoperatively for bladder and head and neck cancer. It delivers real-time, AI-assisted measurements in the surgical field, supporting tumor detection and margin assessment, and demonstrating how Raman can complement or replace frozen section analysis.

Third, multimodal endoscopic probes extend Raman from point measurements to morphochemical imaging. By integrating coherent Raman with nonlinear modalities and AI-driven analysis, they generate diagnostic maps at subcellular resolution and, in head and neck surgery, can be coupled with femtosecond-laser ablation for selective tissue removal in a “seek-and-treat” workflow.

Together, these advances highlight a translational roadmap where Raman, empowered by AI, matures into a clinically viable technology for precision diagnostics and therapy.

Acknowledgements
Financial support of the EU, the Thüringer Ministerium für Bildung, Wissenschaft und Kultur, the Thüringer Aufbaubank, the Federal Ministry of Research, Technology and Space, the German Science Foundation, and the Carl-Zeiss Foundation is gratefully acknowledged.