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If women are to survive ovarian cancer, we need a way to reliable screen and detect disease early. IES is developing a revolutionary method to tap the innate immune system to identify ovarian cancer before its too late.
What is the critical gap in cancer treatment that you are addressing?
The key to surviving cancer is to find it early, before the disease has had a chance to spread to multiple places of the affected organ or to distant sites in the body. We know that earlier diagnosis of cancer can dramatically improve treatment options, clinical outcomes and survival.
The quest for an early detection test for ovarian cancer has consumed cancer researchers and patient advocacy communities for decades. This is because ovarian cancer is one of the deadliest disease for women worldwide with an overall mortality rate of 75%. However, in 90% of cases, ovarian cancer can be cured if diagnosed while the disease is still limited to the ovaries.
Regrettably, a robust, wide-use early detection test for ovarian cancer has been out of reach. Given the low prevalence of ovarian cancer in the general population, a general screening strategy must be highly sensitive (>75%) and highly specific (99.6%) before it can be implemented. This has yet to be achieved and as a result, 35,000 women worldwide each year, do not survive ovarian cancer beyond 2 months of their diagnosis.
IES Life Sciences (IES) is a Maryland based biotechnology company with a unique diagnostic technology that combines the detection of “interferons,” a set of 21 proteins launched in the blood stream during an immune response, with machine learning and artificial intelligence analysis. Our technology is a simple blood test designed to generate a unique interferon “signature” that indicates the presence of disease, before the appearance of classical symptoms. We believe the exquisite sensitivity our test will enable clinicians to detect stage 0/1 ovarian cancer, when the disease is still curable.
What is the key product development milestone you seek to fund?
Our next critical step is to obtain and test high quality blood samples from women with ovarian cancer and a panel of control samples (without ovarian cancer). The blood samples are expected to yield an ovarian cancer blood “signature” of detected interferons. The identification of this specific and sensitive signature represents the earliest key product development milestone.
Once we have identified an ovarian cancer interferon signature, we can proceed with the development of a diagnostic kit designed to test multiple samples at once from affected and non affected women. From there, we will use of artificial intelligence and machine learning to increase the sensitivity and specificity of our test for ovarian cancer.
If successful, IES will file for worldwide patent protection, will offer the test as a Lab Developed Test (LDT) to start producing revenue and will apply for FDA approval.
How will funds be used?
|Use of Funds||Cost||Number||Total US Dollars ($)|
|Ovarian Cancer and Control Blood Samples||$500||100||50,000|
|Test Components, Calibrators and Controls||$220||125||27,500|
|Development of Diagnostic Kit||$300||400||120,000|
|Machine Learning and Artificial Intelligence Analysis||150,000|
|Worldwide Patent Protection||100,000|
|Apply for FDA Approval||250,000|
What key resources have/will you acquire to facilitate the accomplishment of the above R&D milestone?
IES has developed a number of key relationships that will facilitate our goals for developing a diagnostic tests for ovarian cancer and other unmet diagnostic needs. The original discovery was born through a research agreement with the US FDA and Public Health Services. (A Materials Collaborative Research and Development Agreement.) To date, IES enjoys continued technical support with our FDA co-inventors and the FDA Laboratory of Immunobiology.
Other strategic alliances include The School of Pharmacy and Health Professions at the University of Maryland Eastern Shore (UMES). IES and UMES share resources, equipment (qPCR/ddPCR) and clinical and scientific expertise through a collaborative research agreement and a grant funded through the University System of Maryland (USM), Maryland Industrial Partnerships (MIPS) Program.
The Pathology and Laboratory Department at Beebe Healthcare is also an important collaborator. They help us access patients blood samples and provide clinical and pathology expertise.
Our contracted services with Vertex Laboratories is crucial for enabling machine learning and artificial intelligence automation help us identify the ovarian cancer diagnostic signature.
Support from the Maryland technology community, including the Maryland Technical Council, Startup Maryland and Startup Health have been vital to our process and will be instrumental for our future success.
If your technology were to disappear in the “Valley of Death” funding gap, how might this impact society?
Ovarian cancer is a death sentence. Most women do not survive because diagnosis of their disease is too late and too far gone for modern day treatments to work. The only hope for women is to find ovarian cancer early, but the development of early diagnostics tools has yet to come to fruition.
Compounding the issue, the incidence of ovarian cancer worldwide is increasing annually from 239,000 in 2012 to over 371,000 by 2035. Without an early diagnostic test by 2035, the world will endure the deaths of 254,000 women from ovarian cancer.
IES has a unique opportunity to change these dire statistical predictions. With the combination of artificial intelligence and machine learning algorithms, the IES test can identify the unique signatures of interferons in the blood that signify the presence of disease before symptoms arise.
Hence, the loss of the IES ovarian cancer test due to lack of funding would inevitably perpetuate a failed practice of diagnosing early stage ovarian cancer. However, if the IES technology can be faithfully developed, the concept of ovarian cancer being a treatable and curable condition is within our foreseeable future.