2415309
Project Grant
Overview
Grant Description
Sttr phase i: aav qc using sane sensor -the broader impact/commercial potential of this small business technology transfer (sttr) phase i project is it will demonstrate a plasmonic nanopore sensor device for all-in-one dna loading characterization of adeno-associated viruses (aavs) used for gene therapy. In the longer-term, the company anticipates that it will extend uses of this device to accurately test the drug or dna/rna loading consistency of soft nanoparticles such as exosomes, other viruses, and liposomes, to make this quality control (qc) technology applicable to all nanoparticles with biological applications and beyond.
This project has inextricable interests in biochemistry, nanoengineering, photonics, and resistive pulse sensing which would be beneficial to encourage more students to pursue stem degree through its outreach program. The pi will lead the company?s outreach in the dallas county community college district, whose mission is to build up the local workforce to today?s market needs, with nanosensor demonstrations and discussion of broad applications. The proposed technology also has the potential to drastically reduce the time and resource demands of aav qc processes and increase success rates in early-phase gene therapy trials, accelerating fda approvals for desperately needed treatments.
This small business technology transfer (sttr) phase i project will demonstrate a plasmonic nanopore sensor device that will outperform existing analytical techniques by capturing multiple optical-electrical data types per aav particle to enable, for the first time, unambiguous payload classification (single-stranded dna versus double-stranded dna, or empty) at low, pre-scale-up concentrations to optimize formulations in small batches, enabling significant savings in subsequent large-volume production. The proposed work will show feasibility of the proposed device to be nanofabricated in a scalable manner by electron beam lithography, namely optimize sensor nanofabrication protocol for accuracy and production reproducibility of the 3d plasmonic trap, and ensure accurate laser source alignment with bonded optics, and a photodetector collecting optical signals transmitted through the sensor.
In addition, this work will optimize machine learning-based sensor discrimination between empty versus partly and fully loaded aavs by optimizing the spectrum of ac pulse frequencies that scan each particle during trapping. Once successfully tested, the prototype?s nanofabrication and machine-learning workflows will be ready for further development into the company?s first commercial device after a subsequent phase ii. This award reflects nsf's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are planned for this award.
This project has inextricable interests in biochemistry, nanoengineering, photonics, and resistive pulse sensing which would be beneficial to encourage more students to pursue stem degree through its outreach program. The pi will lead the company?s outreach in the dallas county community college district, whose mission is to build up the local workforce to today?s market needs, with nanosensor demonstrations and discussion of broad applications. The proposed technology also has the potential to drastically reduce the time and resource demands of aav qc processes and increase success rates in early-phase gene therapy trials, accelerating fda approvals for desperately needed treatments.
This small business technology transfer (sttr) phase i project will demonstrate a plasmonic nanopore sensor device that will outperform existing analytical techniques by capturing multiple optical-electrical data types per aav particle to enable, for the first time, unambiguous payload classification (single-stranded dna versus double-stranded dna, or empty) at low, pre-scale-up concentrations to optimize formulations in small batches, enabling significant savings in subsequent large-volume production. The proposed work will show feasibility of the proposed device to be nanofabricated in a scalable manner by electron beam lithography, namely optimize sensor nanofabrication protocol for accuracy and production reproducibility of the 3d plasmonic trap, and ensure accurate laser source alignment with bonded optics, and a photodetector collecting optical signals transmitted through the sensor.
In addition, this work will optimize machine learning-based sensor discrimination between empty versus partly and fully loaded aavs by optimizing the spectrum of ac pulse frequencies that scan each particle during trapping. Once successfully tested, the prototype?s nanofabrication and machine-learning workflows will be ready for further development into the company?s first commercial device after a subsequent phase ii. This award reflects nsf's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are planned for this award.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE I", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF23515
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Arlington,
Texas
76010-1511
United States
Geographic Scope
Single Zip Code
Adavance Nanolytics was awarded
Project Grant 2415309
worth $275,000
from National Science Foundation in July 2024 with work to be completed primarily in Arlington Texas United States.
The grant
has a duration of 1 year and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
The Project Grant was awarded through grant opportunity NSF Small Business Innovation Research / Small Business Technology Transfer Phase I Programs.
SBIR Details
Research Type
STTR Phase I
Title
STTR Phase I: AAV QC using SANE Sensor
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is it will demonstrate a plasmonic nanopore sensor device for all-in-one DNA loading characterization of adeno-associated viruses (AAVs) used for gene therapy. In the longer-term, the company anticipates that it will extend uses of this device to accurately test the drug or DNA/RNA loading consistency of soft nanoparticles such as exosomes, other viruses, and liposomes, to make this quality control (QC) technology applicable to all nanoparticles with biological applications and beyond. This project has inextricable interests in biochemistry, nanoengineering, photonics, and resistive pulse sensing which would be beneficial to encourage more students to pursue STEM degree through its outreach program. The PI will lead the company’s outreach in the Dallas County Community College District, whose mission is to build up the local workforce to today’s market needs, with nanosensor demonstrations and discussion of broad applications. The proposed technology also has the potential to drastically reduce the time and resource demands of AAV QC processes and increase success rates in early-phase gene therapy trials, accelerating FDA approvals for desperately needed treatments.
This Small Business Technology Transfer (STTR) Phase I project will demonstrate a plasmonic nanopore sensor device that will outperform existing analytical techniques by capturing multiple optical-electrical data types per AAV particle to enable, for the first time, unambiguous payload classification (single-stranded DNA versus double-stranded DNA, or empty) at low, pre-scale-up concentrations to optimize formulations in small batches, enabling significant savings in subsequent large-volume production. The proposed work will show feasibility of the proposed device to be nanofabricated in a scalable manner by electron beam lithography, namely optimize sensor nanofabrication protocol for accuracy and production reproducibility of the 3D plasmonic trap, and ensure accurate laser source alignment with bonded optics, and a photodetector collecting optical signals transmitted through the sensor. In addition, this work will optimize machine learning-based sensor discrimination between empty versus partly and fully loaded AAVs by optimizing the spectrum of AC pulse frequencies that scan each particle during trapping. Once successfully tested, the prototype’s nanofabrication and machine-learning workflows will be ready for further development into the company’s first commercial device after a subsequent Phase II.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Topic Code
BM
Solicitation Number
NSF 23-515
Status
(Complete)
Last Modified 6/20/24
Period of Performance
7/1/24
Start Date
6/30/25
End Date
Funding Split
$275.0K
Federal Obligation
$0.0
Non-Federal Obligation
$275.0K
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
2415309
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
GVL5CSKS4EW5
Awardee CAGE
9LE43
Performance District
TX-33
Senators
John Cornyn
Ted Cruz
Ted Cruz
Modified: 6/20/24