This might be pretty significant - it looks like a pretty broad patent:
Press Release Source: Correlogic Systems, Inc.
Correlogic Systems' 'Hidden Patterns' Awarded US Patent Protection
Monday August 15, 11:06 am ET
Novel Approach to Disease Detection and Other Applications Covered Under Broad Approval
BETHESDA, Md., Aug. 15 /PRNewswire/ -- Correlogic Systems, Inc. today announced that the invention, A Process for Distinguishing between Biological States Based on Hidden Patterns from Biological Data ("Hidden Patterns") has been awarded U.S. Patent No. 6,925,389 by the US Patent and Trademark Office. The patent is based on the concept that subtle patterns of changes occurring in the body, including those reflected in serum, urine, and secretions such as saliva and perspiration, can be used to identify disease and other biological conditions.
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Correlogic's pattern recognition approach can be used as a highly effective means of identifying the presence of certain types of cancer and other diseases, as well as monitoring drug toxicity and efficacy. In addition to medical applications, the patent also covers the wide range of other biological "Hidden Patterns" applications.
"We believe that hidden pattern recognition will play an important role in diagnostic testing, and we are pleased that Correlogic has been granted this patent," said Surya N. Mohapatra, Ph.D., Chairman and CEO of Quest Diagnostics Incorporated (NYSE: DGX - News), which retains an option to commercialize specified diagnostic tests Correlogic is currently developing for certain disease states.
Correlogic's first application of "Hidden Patterns" has been to the early detection of disease including ovarian, prostate, and pancreatic cancers. "Hidden Patterns" has also been used successfully to distinguish recurrence/remission of Wegener's disease, and has been used in drug toxicity and other non-disease applications. Correlogic's research on biological applications of "Hidden Patterns" has been published in peer-reviewed scientific journals, including The Lancet, Journal of the National Cancer Institute, Endocrine-Related Cancer, Journal of Urology, Arthritis and Rheumatism, Cancer Cell, Toxicologic Pathology, and Analytical Chemistry.
"'Hidden Patterns' has the potential to transform disease detection, enabling it to be earlier and more accurate, less invasive and less costly," said Peter J. Levine, president and CEO of Correlogic Systems, Inc. "Correlogic is moving quickly to take the technology from the research lab into the hands of health care providers."
The patent is co-owned by Correlogic and the Public Health Service which has licensed its commercialization rights exclusively to Correlogic.
About Correlogic Systems, Inc.
Correlogic Systems, Inc. is a Bethesda, Maryland-based clinical proteomics company that has developed proprietary technology and processes with a wide variety of applications for biomarker discovery, disease detection, and new drug discovery. The technology's first application has been in the field of proteomics -- the study of human proteins. OvaCheck®, a blood test for the early detection of ovarian cancer, is Correlogic's first diagnostic test using "Hidden Patterns." The test is undergoing the final stages of its extensive validation process. Correlogic has entered into licensing agreements with Quest Diagnostics, Inc., and Laboratory Corporation of America for the North American market development and commercialization of OvaCheck.
Correlogic is also conducting research on the application of "Hidden Patterns" to breast and colon cancer. Visit Correlogic Systems at correlogic.com.
Here's a relevant chunk:
1. A method of determining whether a biological sample taken from a subject indicates that the subject has a disease by analyzing a data stream that is obtained by performing an analysis of the biological sample, comprising:
abstracting the data stream to produce a sample vector that characterizes the data stream in a predetermined vector space containing a diagnostic cluster, the diagnostic cluster being a disease cluster, the disease cluster corresponding to the presence of the disease;
determining whether the sample vector rests within the disease cluster; and
if the sample vector rests within the diseased cluster, identifying the biological sample as indicating that the subject has the disease, and displaying the result.
2. The method of claim 1, wherein the data stream is data describing an expression of molecules in the biological sample.
3. The method of claim 2, wherein the molecules are proteins.
[snip]
I. FIELD OF THE INVENTION
The field of the invention concerns a process for determining a biological state through the discovery and analysis of hidden or non-obvious, discriminatory biological data patterns. The biological data can be from health data, clinical data, or from a biological sample, (e.g., a biological sample from a human, e.g., serum, blood, saliva, plasma, nipple aspirants, synovial fluids, cerebrospinal fluids, sweat, urine, fecal matter, tears, bronchial lavage, swabbings, needle aspirantas, semen, vaginal fluids, pre-ejaculate, etc.), etc. which is analyzed to determine the biological state of the donor. The biological state can be a pathologic diagnosis, toxicity state, efficacy of a drug, prognosis of a disease, etc.
Specifically, the invention concerns analytical methods that a) discover hidden discriminatory biological data patterns (e.g., patterns of protein expression in a serum sample that classify the biological state of an organ) that are subsets of the larger data stream, said discrimination implying the ability to distinguish between two or more biological states in a learning set of data and b) the application of the aforementioned patterns to classify unknown or test samples. More specifically, the invention concerns a method for analysis of a data stream, which is derived from a physical or chemical analysis of molecules (e.g., proteins, peptides, DNA, RNA, etc.) in the biological sample (e.g., a mass spectrum analysis of the sample).
These patterns are defined as "hidden" because they are often buried within a larger highly complex data set and are not obvious or apparent to the eye or other current classification systems. The pattern itself can be defined as the combination of three or more values such that the position of the vectors in an n-dimensional space is discriminatory between biological states even when individual values may not be discriminatory. The discriminatory patterns of the invention are novel because they can be defined without any knowledge of the identity or relationship between the individual data points in the biological data or any knowledge of the identity or relationship between the molecules in the biological samples.
One analytical method to discover such biological states comprises the application of two related heuristic algorithms, a learning algorithm and a diagnostic algorithm, wherein the parameters of the diagnostic algorithm are set by the application of the learning algorithm to a learning set of data such that two or more biological states may be distinguished. Such biological states may be the presence or absence of a disease, efficacy or non-efficacy of a drug, toxicity or non-toxicity of a drug, etc. Although the invention is generic, specific implementations for diagnosis of various cancers (including, but not limited to carcinomas, melanomas, lymphomas, sarcomas, blastomas, leukemias, myelomas, neural tumors, etc., and cancers of organs like the ovary, prostate, and breast.), presence of a pathogen, and toxicity are disclosed. The preferred embodiment of the invention is the discovery and use of molecular patterns that reflect the current or future biological state of an organ or tissue. Another embodiment of the invention is the combination of data describing the molecular patterns of a biological state with other non-biological or clinical data (e.g., psychiatric questioning) to yield a classification describing the health of a patient.
Peter |
