(Invited) Developing Optical Nanosensors for Biomedical Applications

Abstract

Novel biomedical application technologies have been rapidly improved in the past few decades. Despite recent technological progress, significant challenges persist toward more accessible, precise, inexpensive, rapid, automated, and patient-facing methods. Optical spectroscopic and imaging technologies have multiple advantages to current practices, such as versatility, fast and robust signal, and noninvasive and nondestructive probing techniques that can be easily integrated into current medical devices such as catheters, endoscopes, or biopsy needle channels. Single-walled carbon nanotubes (SWCNTs) have been developed as near-infrared (NIR) fluorescent nanosensors and demonstrated in vitro and in vivo with great interest for using them in biological and clinical applications and the methods designed to probe them. The advantages of SWCNT include resistance to photobleaching and high sensitivity towards biological environments.Gynecologic cancers are challenging to diagnose. Patient prognosis and quality of life are affected substantially by this problem. In this talk, I will present recent work on developing new technologies to improve gynecological cancer detection and grant new research tools for understanding fundamental mechanisms in cancer development using liquid biopsy and in vitro and in vivo sensor approaches. With artificial intelligence algorithms, we harness SWCNTs' unique optical properties and sensitivity to develop intelligent optical sensors. We developed platforms to detect multiple gynecological cancer biomarkers as implantable devices in patient biofluids and the uterine cavity. Applying machine learning algorithms to analyze the optical response of the sensors enabled the precise detection of multiplexed biomarkers. In addition, when implanted in human uteri, the sensors detected the biomarkers and successfully differentiated between benign and malignant cases. These technologies will significantly improve diagnostics and cancer research, leading to robust, point-of-care technologies for early-stage diagnosis.