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Semi-Automated Prental Screening Using Maternal Blood

Award Information

Agency:
Department of Health and Human Services
Branch:
N/A
Award ID:
66146
Program Year/Program:
2003 / SBIR
Agency Tracking Number:
HD037308
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
Advanced Digital Imaging Research, LLC
Advanced Digital Imaging Res 2450 S Shore Blvd, Ste 305 League City, TX 77573 0299
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2003
Title: Semi-Automated Prental Screening Using Maternal Blood
Agency: HHS
Contract: 2R44HD037308-02
Award Amount: $0.00
 

Abstract:

DESCRIPTION (provided by applicant): Scientists have documented the phenomenon of fetal ceils in maternal blood, and envisioned using them for noninvasive prenatal screening. A key limiting factor is the small number of fetal cells in the maternal circulation, making fetal cell isolation difficult and limiting the accuracy of genetic analysis. Current emphasis is on simple, practical and reproducible methods for enrichment and genetic testing of fetal cells. The goal of this project is to develop simple semi-automated methods for enrichment, detection, and diagnosis of fetal cells in maternal blood. This project combines recent advances in fetal progenitor cell research, with a novel enrichment approach, and speedy automated cell detection for prenatal genetic analysis. In the Phase I study we evaluated the feasibility of automatically detecting May-Giemsa stained nucleated red blood cells (NRBCs) using transmitted light microscopy, followed by fetal gender and/or aneuploidy detection via fluorescent in-situ hybridization (FISH). Our results demonstrated that NRBCs are present in the maternal blood stream during pregnancy, and can be effectively enriched to proportions that are conducive to automated cell detection. We also observed that these cells may not be the ideal target cell, because most of these cells are at late stages of differentiation and undergoing apoptosis. Moreover, we found that the suitability of NRBCs for FISH analysis was highly variable as it is related to its state of differentiation. Consequently, we evaluated the potential of fetal progenitor cells as an alternative cell type for prenatal screening. For separation and enrichment, we employed a more simple isolation method that would allow for detection of more that one fetal progentior cell type. We adopted the Rosette Method (StemCell Technologies, Inc) to achieve the selective enrichment of hematopoietic progenitor cell types from whole blood with reduced cell loss. The enriched samples were then successfully processed via FISH to identify male fetal cells in maternal blood. In the Phase II study, we will (i) evaluate automated analysis for detection efficiency of fetal cells based on the presence of FISH signals in the clinical environment, and (ii) relocate fetal cells identified in aim 1 and record fetal cell descriptors based on cellular shape, density, and size. This information will then be used to further develop automated parameters for morphological identification of progenitor fetal cells, and (iii) based on the results of aim 1 and 2, we will implement the final modifications and/or optimizations to fully develop a semi-automated imaging system for the detection and analysis of fetal cells in maternal blood using transmitted and fluorescence microscopy. The ultimate goal of much of the current research in medical cytogenetics is to make low-cost, low-risk prenatal genetic screening widely available. This project will develop instrumentation that will be vital in the realization of this goal. The innovative technological approach presented here has the potential to revolutionize the future of prenatal diagnosis.

Principal Investigator:

Fatima Merchant

Business Contact:

Kenneth Castleman
2815351889
CASTLEMAN@ADIRES.COM
Small Business Information at Submission:

ADVANCED DIGITAL IMAGING RESEARCH, LLC
ADVANCED DIGITAL IMAGING RES 2450 S SHORE BLVD, STE 305 LEAGUE CITY, TX 77573

EIN/Tax ID: 752791864
DUNS: N/A
Number of Employees: N/A
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No