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A Screening Test for Alzheimer’s Disease Based on Raman Hyperspectroscopy and Machine Learning

Oct 25, 2023
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About This Webinar
Raman hyperspectroscopy combined with advanced statistics is uniquely suitable for characterizing microheterogeneous systems. Understanding the structure and biochemical composition of samples at the microscopic level is important for many practical applications including material science, pharmaceutical industry, and others. Lednev's team has recently demonstrated the great potential of Raman hyperspectroscopy for disease diagnostics and forensic purposes. In this presentation, Lednev discusses the development of a novel, noninvasive approach for Alzheimer’s disease diagnostics based on Raman spectroscopic analysis of blood, cerebrospinal fluid, and saliva.

NIR Raman hyperspectroscopy coupled with advanced multivariate statistics was utilized for differentiating patients diagnosed with Alzheimer’s disease, other types of dementia, and healthy control subjects with more than 95% sensitivity and specificity. When fully developed, this fast, inexpensive, and noninvasive method could be used for screening at-risk patient populations for application development and progression.

*** This presentation premiered during the 2023 BioPhotonics Conference. For more information on Photonics Media conferences and summits, visit events.photonics.com.

About the presenter

Igor LednevIgor K. Lednev, Ph.D., is the Williams-Raycheff professor in chemistry and a SUNY distinguished professor in the Department of Chemistry at the University at Albany, State University of New York. He is an adjunct professor in the Department of Biological Sciences and a faculty member of the RNA Institute. Lednev is a cofounder of SupreMEtric LLC, commercializing a patented technology for forensic purposes, and Early Diagnostics LLC developing saliva and blood tests for the early diagnostics of Alzheimer’s disease. He has served as an advisory member on the White House Subcommittee for Forensic Science.

Lednev’s research is focused on the development and application of novel laser spectroscopy for forensic purposes, biomedical applications and fundamental biochemistry. His accomplishments include the development of a universal method for the identification and analysis of biological stains for forensic purposes using Raman spectroscopy. Lednev’s laboratory used the combination of Raman hyperspectroscopy and machine learning for developing noninvasive methods for disease diagnostics. They proposed novel methods for RNA vaccine stability and drug discovery. The laboratory introduced novel spectroscopic methods for characterizing the structure and formation mechanism of amyloid fibrils associated with neurodegenerative diseases. A new protein folding-aggregation phenomenon of spontaneous refolding of amyloid fibrils from one polymorph to another was discovered that opened the opportunity for a new therapeutic approach for neurodegenerative diseases.

Lednev has co-authored over 260 publications in peer-reviewed journals and 10 patents reaching the h-index of 73. His work has been covered by the media more than 90 times including 11 TV interviews, and publications in the Wall Street Journal, Chemical & Engineering News, Forensic Magazine, and others. Congressman Tonko has acknowledged Lednev’s research accomplishments at the U.S. House of Representatives’ Hearing on Advancements in Forensic Science in the U.S. in 2019. He was recruited by the United Nations to give a week-long “National Training Course on using vibrational techniques to enhance the forensic analysis” for the National Crime Laboratory of Chile in Santiago, Chile in 2020.

Lednev is a Fellow of the Royal Society, U.K. and the Society for Applied Spectroscopy. He received several prestigious awards including the 2022 Charles Mann Award for Applied Raman Spectroscopy, Gold Medal Award from the Society for Applied Spectroscopy, Guest Professor Fellowship from the Friedrich-Schiller-University, Germany, Research Innovation Award from Research Corporation, Chancellor’s Award for Excellence in Scholarship and Creative Activities, University President Award for Exemplary Public Engagement, and Dean’s Award for Outstanding Achievements in Teaching.
spectroscopyBiophotonicsmachine learningdisease diagnosticsAlzheimers disease
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