Developing Optical Sensors for Applications in Biochemistry and Cancer Research

05.01.2021
15:30
https://meetmsk.zoom.us/j/91239232677?pwd=NWtac05PN0s3Ullvb3RrcVJWSFdqUT09; passcode: 727960
Dr. Zvi Yaari; Molecular Pharmacology, Memorial Sloan Kettering Cancer Center New York, NY

Real time sensing of biological processes in diseases is critical for many fields, especially cancer. Optical sensors enable fast, reliable, and highly sensitive detection of various states. Among many materials, the physical and optical properties of single-walled carbon nanotubes (SWCNTs) set them apart as indispensable sensors and offer unique applications in biology, biotechnology and medicine. During my postdoctoral work I have developed both in vitro and in vivo biosensors for detecting diseases, monitoring biological processes in both the micro and macro scale, and integrating machine learning algorithms to create robust sensing platforms. I engineered a sensor that tracks a specific enzymatic pathway that leads to irreversible enzyme inactivation. This sensor can be used to screen novel molecules such as enzyme inhibitors. Furthermore, I designed an array of biosensors to develop an optical platform for detection of multiple ovarian cancer biomarker-based proteins without using a specific binding moiety (such as an antibody or aptamer), but rather by harnessing machine learning technology. I trained models with several classification and regression algorithms to predict biomarker presence and create a molecular perceptron technology. In addition, I have developed a clinical implantable biosensor for early ovarian cancer detection. The biosensor is comprised of an ovarian cancer biomarker antibody conjugated to DNA-wrapped SWCNTs. This technology has the potential to increase patient survival by rapidly informing and improving patient diagnosis and treatment regimens. Integrating my background in nanotechnology, personalized medicine, and optical biosensors, I plan to develop novel analytical and diagnostic platforms for early detection of inflammatory diseases.

 

Abstract