NeoGenomics, a provider of cancer-focused genetic testing services, today announced that it has developed and is now using new proprietary software for reading and interpreting Fluorescent in Situ Hybridization (“FISH”) digital data acquired manually or by an automated system.
The software is based on Support Vector Machine (SVM), which allows users to read and interpret specific types of FISH images more accurately and more quickly, and is a result of the company’s licensing agreement with Health Discovery Corp. It was through this agreement that NeoGenomics obtained exclusive worldwide rights to use SVM technology for all types of laboratory-developed tests in hematopoietic and solid tumor cancers.
NeoGenomics reports that it has confirmed and is currently implementing a laboratory-developed test using the new software to read ALK rearrangement FISH tests, which is a key component in selecting appropriate therapy for lung cancer patients. The company also intends to expand its use for other FISH probes.
“Development of this software is a result of our commitment to offer innovative solutions and uncompromising quality for cancer testing …,” Douglas VanOort, NeoGenomics chairman and CEO, stated in the press release. “We expect SVM technology will help us to automate certain manual testing processes, provide more accurate results for those tests that were previously dependent on subjective interpretations, and increase the productivity of our lab operations. To our knowledge, we are the first laboratory in the world to use SVM technology to assist in reading and interpreting ALK FISH data.”
Dr. Maher Albitar, NeoGenomics’ chief medical officer and director of research and development, noted the value that the system provides to lab technicians, in that they can train varying algorithms for specific types FISH images. Additionally, users have access to a library of files for reading and interpreting various FISH probes, which can be compiled for general use in any FISH laboratory that has a sublicense to the SVM technology.
“The science around using pattern recognition and computer-aided algorithms has improved significantly in the past few years. Our use of algorithms to interpret FISH digital data is just one step in a series of planned activities to adapt the SVM technology to cancer genetics testing. We believe these types of algorithms will be instrumental in helping to answer complex clinical questions and reducing the dependence on subjective interpretations,” Dr. Albitar stated.
NeoGenomics has applied for a utility patent on this methodology and the related software.
For more information visit www.neogenomics.com
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