SBIR/STTR Research Award

Rapid Cancer-Treatment Efficacy Monitoring System

Award identifier d66dc64fc2770383c90cec0c887cca2709c389324c862281f6b828e7334c91cdAwarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$99,644

Program and phase

SBIR · Phase I

Award year

2003

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
INSIGHTFUL CORPORATION
Proposal award date
Not reported
Contract end date
Not reported
UEI
Not reported
Solicitation number
Not reported
Topic code
Not reported

Research abstract

DESCRIPTION (provided by applicant): Evaluating cancer therapy efficacy by studying symptomatic improvement in patient condition is a popular practice due to the lack of rapid, reliable and robust quantitative evaluation protocols for routine clinical measurement of cancer therapy efficacy. Reducing time required for arriving at decisions and reducing cost without compromising accuracy could provide potentially improved treatments especially for patients with advanced leukemia of various types. This proposal focuses on rapid quantitative assessment of cancer treatment efficacy for leukemia. The proposed approach is based on quantifying apoptosis (programmed cell death) and has been shown to be one of the most reliable and one of the earliest indicators for assessing anticancer efficacy of a drug. Several other techniques are available to detect apoptosis (Agarose gel electrophoresis, Caspase-3, TUNEL assay, Morphological estimation, Annexin V assays etc). However, these techniques are inaccurate, expensive or time consuming. A recently developed a two stage DNA diffusion assay holds promise to be an accurate, relatively inexpensive and rapid methodology for quantitative apoptosis measurement via the apoptotic index. The two stages are:(1) slide preparation and microscopy imaging, which requires approximately 1.5 hrs and (2) image analysis, which is tedious, and takes approximately 2 hours of additional intensive manual labor leading to errors in categorization of the cells. We propose to fully automate the second stage with the goal to minimize manual effort and there by reduce the human errors. This would also make the procedure more reproducible. Phase I work will involve: (1) segmentation and classification algorithm development for automatic apoptotic index calculation, and (2) characterizing the algorithm performance by inducing apoptosis in leukemia cells in culture using known apoptosis inducing agents.

Technology keywords

Not reported

Agency intelligence

Department of Health and Human Services

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