PROJECT SUMMARY
Liquid biopsy modalities that can non-invasively detect disease-associated biomarkers from biofluids can enable
early cancer detection and patient monitoring with implications for improved survival rates. However, current
methods have not achieved critical sensitivity and accuracy to be approved for population screening programs.
New spectrochemical liquid biopsy methods, such as Raman and infrared spectroscopy, coupled with machine
learning models are emerging as next-generation diagnostic modalities. Yet, fundamental physical limitations of
light-matter interactions using conventional optical setups hinder the analytical performance of molecular
spectroscopy techniques. Here, we propose to employ novel electromagnetic metasurfaces that can advance
the analytical sensitivity and chemical selectivity of infrared absorption spectroscopy enabling its real-world
applications in the biomedical field. Moreover, our innovative laser-based spectral imaging approach can achieve
on-chip spectrometer-less chemical fingerprint retrieval eliminating clinically incompatible, complex, and bulky
instrumentation requirements.
The long-term goal of this project is to develop a rapid, label-free, portable, and non-invasive cancer detection
platform based on sensitive and accurate chemometric liquid biopsy and machine learning-aided discrimination
modalities. The overall objectives in this application are to (i) determine a potent metasurface design that can
robustly extract chemical fingerprint information from a complex biosample matrix, (ii) identify optimized design
parameters for spectral imaging-based on-chip fingerprint retrieval (iii) establish measurement protocols and
data processing pipeline (iv) identify a machine learning model by which sensitive and accurate sample
discrimination can be achieved. In the short term, we will pursue two specific aims: 1) develop novel engineered
metasurfaces for sensitive and specific spectrochemical biofluid analysis and demonstrate spectrometer-less
on-chip chemical fingerprinting 2) Test and validate the platform using biofluids from an ovarian cancer patient
cohort and non-cancer controls. Our proposed approach is innovative because it catalyzes the state-of-the-art
laser-based infrared spectral imaging technology with powerful nanophotonic tools to enable its impact in
biomedical diagnostics and address an unmet medical need. In addition, the proposed interdisciplinary project
is significant because it is expected to develop a non-invasive and accessible health screening platform that can
ultimately impact the clinical management of cancer and the survival outcomes equitably among diverse
populations.