# Screening for Alzheimer's Disease Based on Raman Spectroscopy of Blood

> **NIH NIH R41** · EARLY ALZHEIMER'S DIAGNOSTICS LLC · 2022 · $306,974

## Abstract

Abstract -
Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects an estimated 6.2 million
Americans and the 6th leading cause of death in the U.S. AD is progressive and incurable; dementia symptoms
gradually worsen over a number of years. In its early stages, memory loss is mild, but in late-stage AD, individuals
lose the ability to carry on a conversation and respond to their environment. AD is a devastating condition that
creates vast emotional, financial, and physical challenges for the person and their family. In AD, pathological
changes may arise up to 20 years before the onset of dementia, providing a unique window of opportunity
for interventions aimed at preserving cognitive health and delaying disease progression. However, there is
currently no diagnostic tool that can be widely applied for the detection of preclinical AD. When potentially
effective therapies are initiated late in the underlying disease pathology process (i.e., after cognitive decline is
apparent), the true impact of prevention is not achieved. In response to the critical need for an accessible
diagnostic tool for early and preclinical AD, Early Alzheimer’s Diagnostics proposes to develop a screening
technology based on Raman Spectroscopy combined with machine learning (ML) models trained to
detect spectral signature changes based on the contribution of multiple biomarkers found in the blood.
The proposed technology has the potential to greatly improve outcomes by allowing patients to identify early
signs of AD, and therefore start preventive interventions and active monitoring of disease progression, delaying
the onset of dementia, and preserving brain health for longer. Such a tool would also have significant utility in
clinical trials for critically needed new AD therapies, facilitating recruitment and selection of healthy volunteers
and AD patients at various stages of disease progression. Preliminary results show that the approach can
differentiate the biochemical composition of blood from patients at different stages of AD from healthy controls.
The team has also developed a novel method using automated mapping of solid samples to detect ultra-small
amounts of biomarkers by preventing them from leaving a small volume interrogated by the focused laser light
during spectral acquisition. This Phase I project will provide de-risk key aspects in the process of adapting the
technology into a clinical commercial application and provide proof-of-feasibility via a blind test. The Specific
Aims of this STTR project are: 1) Optimize a scalable, rapid methodology for obtaining and analyzing Raman
spectral data from blood serum; 2) Develop ML algorithm approaches for analyzing Raman spectral data; and
3) Validate the Raman spectroscopy-based approach in a blind test. Successful completion of proposed research
will position Early Alzheimer’s Diagnostics to perform initial clinical trials in Phase II, and advance discussions
with potential industry par...

## Key facts

- **NIH application ID:** 10547295
- **Project number:** 1R41AG078073-01A1
- **Recipient organization:** EARLY ALZHEIMER'S DIAGNOSTICS LLC
- **Principal Investigator:** IGOR K LEDNEV
- **Activity code:** R41 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $306,974
- **Award type:** 1
- **Project period:** 2022-09-30 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10547295

## Citation

> US National Institutes of Health, RePORTER application 10547295, Screening for Alzheimer's Disease Based on Raman Spectroscopy of Blood (1R41AG078073-01A1). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10547295. Licensed CC0.

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