R01AG084098
Project Grant
Overview
Grant Description
Automa1. - Project Summary
Alzheimer's Disease (AD) is a severe neurodegenerative illness that destroys cognitive abilities, causing memory impairment, difficulties with speech and language, behavioral changes, functional decline, and significant impairment. AD affects an estimated 13.8 million people in the United States and 50 million worldwide, imposing a significant economic burden and global health crisis.
While many researchers are working towards developing a cure for the disease, there is currently no objective, point-of-care diagnostic test for the early diagnosis of AD, significantly limiting screening efforts for clinical studies and delaying treatment for patients suffering from early AD pathology.
The current standard methods for AD diagnosis involve expensive PET imaging methods that irradiate the patient and cerebrospinal fluid biomarker tests, which are invasive and require a lumbar puncture.
Recently, exosomes (30-150 nm extracellular vesicles) have been identified as a possible tool for AD diagnosis, attributed to their ubiquitous presence in biofluids, their ability to pass through the blood-brain-barrier, and their rich library of AD-relevant physiological information present in the molecular cargo they carry, making them prime candidates for use as biomarkers.
However, the clinical application of exosomes is hindered by slow, inefficient techniques for exosome isolation and the absence of standardized exosomal biomarker detection and analysis.
Thus, an automated, highly sensitive, fast, and efficient system that can isolate exosomes from biofluids and analyze the miRNAs and proteins they contain will significantly improve early-stage AD diagnosis efforts.
In this R01 project, we will develop an automated high-purity exosome isolation-based AD diagnostics system (AHEADX) to address the limitations of current technologies.
The proposed AHEADX platform includes two units: (1) a rapid (<1 min), high-yield (>90%), and high-purity (>90%) acoustic Bessel beam-based separation unit to isolate and enrich exosomes from whole blood, and (2) a rapid (<6 mins), highly sensitive photonic PCR and immunopcr (~1 copy/μL for nucleic acids and ~5 copies/μL for proteins, respectively) utilizing a plasmonic nanopillar array to enable on-chip thermocycling and multiplexed exosomal screening of combined panels of AD-relevant biomarkers.
Our rapid and precise AHEADX platform will provide a simple, minimally invasive liquid biopsy to detect molecular AD biomarkers with ultrahigh accuracy and sensitivity in early-stage AD patients, allowing for an effective diagnostic method of AD screening for earlier treatment before the onset of severe symptoms of the disease and enable long-term studies on AD development and progression.
Additionally, the proposed technology will accelerate the discovery of new exosomal miRNA and protein AD biomarkers and help to elucidate the mechanisms in which exosome trafficking and transport contribute to AD pathology.
With these advantages, our AHEADX platform can potentially exceed current clinical standards in AD diagnostics, addressing a significant need in the field and providing a compelling platform for earlier, accurate, and sensitive detection of AD and long-term studies on the effects of novel AD therapeutics.
Alzheimer's Disease (AD) is a severe neurodegenerative illness that destroys cognitive abilities, causing memory impairment, difficulties with speech and language, behavioral changes, functional decline, and significant impairment. AD affects an estimated 13.8 million people in the United States and 50 million worldwide, imposing a significant economic burden and global health crisis.
While many researchers are working towards developing a cure for the disease, there is currently no objective, point-of-care diagnostic test for the early diagnosis of AD, significantly limiting screening efforts for clinical studies and delaying treatment for patients suffering from early AD pathology.
The current standard methods for AD diagnosis involve expensive PET imaging methods that irradiate the patient and cerebrospinal fluid biomarker tests, which are invasive and require a lumbar puncture.
Recently, exosomes (30-150 nm extracellular vesicles) have been identified as a possible tool for AD diagnosis, attributed to their ubiquitous presence in biofluids, their ability to pass through the blood-brain-barrier, and their rich library of AD-relevant physiological information present in the molecular cargo they carry, making them prime candidates for use as biomarkers.
However, the clinical application of exosomes is hindered by slow, inefficient techniques for exosome isolation and the absence of standardized exosomal biomarker detection and analysis.
Thus, an automated, highly sensitive, fast, and efficient system that can isolate exosomes from biofluids and analyze the miRNAs and proteins they contain will significantly improve early-stage AD diagnosis efforts.
In this R01 project, we will develop an automated high-purity exosome isolation-based AD diagnostics system (AHEADX) to address the limitations of current technologies.
The proposed AHEADX platform includes two units: (1) a rapid (<1 min), high-yield (>90%), and high-purity (>90%) acoustic Bessel beam-based separation unit to isolate and enrich exosomes from whole blood, and (2) a rapid (<6 mins), highly sensitive photonic PCR and immunopcr (~1 copy/μL for nucleic acids and ~5 copies/μL for proteins, respectively) utilizing a plasmonic nanopillar array to enable on-chip thermocycling and multiplexed exosomal screening of combined panels of AD-relevant biomarkers.
Our rapid and precise AHEADX platform will provide a simple, minimally invasive liquid biopsy to detect molecular AD biomarkers with ultrahigh accuracy and sensitivity in early-stage AD patients, allowing for an effective diagnostic method of AD screening for earlier treatment before the onset of severe symptoms of the disease and enable long-term studies on AD development and progression.
Additionally, the proposed technology will accelerate the discovery of new exosomal miRNA and protein AD biomarkers and help to elucidate the mechanisms in which exosome trafficking and transport contribute to AD pathology.
With these advantages, our AHEADX platform can potentially exceed current clinical standards in AD diagnostics, addressing a significant need in the field and providing a compelling platform for earlier, accurate, and sensitive detection of AD and long-term studies on the effects of novel AD therapeutics.
Awardee
Funding Goals
NOT APPLICABLE
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Durham,
North Carolina
277054640
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 290% from $788,817 to $3,077,202.
Duke University was awarded
Automated Exosome-Based AD Diagnostics System for Early Detection
Project Grant R01AG084098
worth $3,077,202
from National Institute on Aging in September 2023 with work to be completed primarily in Durham North Carolina United States.
The grant
has a duration of 4 years 8 months and
was awarded through assistance program 93.866 Aging Research.
The Project Grant was awarded through grant opportunity Research on Current Topics in Alzheimer's Disease and Its Related Dementias (R01 Clinical Trial Optional).
Status
(Ongoing)
Last Modified 5/21/26
Period of Performance
9/1/23
Start Date
5/31/28
End Date
Funding Split
$3.1M
Federal Obligation
$0.0
Non-Federal Obligation
$3.1M
Total Obligated
Activity Timeline
Subgrant Awards
Disclosed subgrants for R01AG084098
Transaction History
Modifications to R01AG084098
Additional Detail
Award ID FAIN
R01AG084098
SAI Number
R01AG084098-3086468666
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Private Institution Of Higher Education
Awarding Office
75NN00 NIH National Insitute on Aging
Funding Office
75NN00 NIH National Insitute on Aging
Awardee UEI
TP7EK8DZV6N5
Awardee CAGE
4B478
Performance District
NC-04
Senators
Thom Tillis
Ted Budd
Ted Budd
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| National Institute on Aging, National Institutes of Health, Health and Human Services (075-0843) | Health research and training | Grants, subsidies, and contributions (41.0) | $788,817 | 100% |
Modified: 5/21/26