SBIR/STTR Research Award

FASTCOUNT Next generation stereology platform for fast accurate D cell counting

Award identifier f839f535eff237ecd0341a55444a8fdbe2e3920e7bfe4305ee0643ddbb144b68Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$1,797,336

Program and phase

SBIR · Phase II

Award year

2015

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
MICROBRIGHTFIELD, LLC
Proposal award date
2015-09-01
Contract end date
2018-07-31
UEI
L5XGENY3LNN7
Solicitation number
PA11-134
Topic code
101

Research abstract

DESCRIPTION provided by applicant Stereologic cell counting has revolutionized the field of neuroscience over the last years and numerous studies highlighting the impact of stereologic cell counting in basic neuroscience and pharmaceutical and biotechnology research continue to be published A single study however may take months since investigators must decide by visual inspection whether or not to count each cell according to three dimensional D stereologic counting rules within thousands of microscopic fields of view Because of this reliance on manual inspection stereologic cell counting has remained very labor intensive and time consuming to perform As a result faster automated though less accurate non stereologic cell detection approaches have remained in widespread use despite their known disadvantages and biased results In response to this challenge this project aims to develop an innovative microscope system for fully automated stereologic cell counting andquot FASTCOUNTandquot building upon technology implemented in the FARSIGHT toolkit for automated D cell detection created by our collaborator Dr Badri Roysam and his team and combining it with technology developed for our Stereo Investigator R software used in approximately laboratories worldwide This project is fully in line with the NIMH program titled Lab to Marketplace Tools for Brain and Behavioral Research FASTCOUNT will allow investigators for the first time to perform automated stereologic cell counting The benefit for the neuroscience research community and society in general will be increased research throughput i e at least ten times faster in basc neuroscience and pharmaceutical and biotechnology research Increased throughput will make possible new kinds of studies currently not feasible due to the labor intensive nature of the existing methods thus leading to new discoveries Our project will be implemented in two phases During Phase I we will create a prototype FASTCOUNT application incorporating cell detection learning and editing We will then benchmark its performance in automated D cell detection on tissue sections for various combinations of species tissue processing cell staining labeling imaging and image pre processing During Phase II we will i improve and optimize the algorithms for automated stereologic D cell detection used in FASTCOUNT ii develop a Software Development Kit as interface between FASTCOUNT and third party software applications to allow development of new automated D cell detection methods iii develop novel image data management functionality for automated stereologic cell counting on tissue specimens processed with recent tissue clearing procedures such as CLARITY and iv develop recommended operating procedures for FASTCOUNT addressing tissue preparation labeling imaging and pre processing Together with experienced academic collaboration partners we will perform extensive product validation studies of FASTCOUNT throughout development to demonstrate its superiority over both manual stereologic cell counting and biased profile counting PUBLIC HEALTH RELEVANCE This project will create a much needed innovative system for performing high throughput accurate automated stereologic D cell counting thereby increasing the pace of research and enabling the design of new studies not currently feasible with existing methodologies Because stereologic cell counting is currently a very time consuming method increasing the throughput is critical for the development of new treatments for Alzheimerandapos s Parkinsonandapos s and many other neurological conditions and diseases This project embraces the goals of the NIMH program Lab to Marketplace Tools for Brain and Behavioral Research by leveraging a collaboration with academic researchers in automated D cell detection Dr Badri Roysam at the University of Houston Texas to translate a technology for brain research from the academic research sector to the marketplace and further developing this technology into a high impact robust and user friendly commercial product

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

42 SBIR/STTR records share this UEI (1989–2023). Reported award amounts total $42,106,779. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Health and Human Services, Department of Defense, National Science Foundation

Agency intelligence

Department of Health and Human Services

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