Spherix Executes Machine Learning Scientific Research Agreement

Research Agreement Will Use Machine Learning to ID Genetic Markers for Pancreatic Cancer

NEW YORKMarch 3, 2020 /PRNewswire/ — Spherix Incorporated (Nasdaq: SPEX) today announced it has executed a Scientific Research Agreement with The University of Texas Southwestern Medical Center with the goal of using machine learning to find genetic markers in people that indicate an increased risk of developing pancreatic cancer.

Spherix Logo. (PRNewsFoto/Spherix Incorporated)

As with many cancers, early detection is vital, but in pancreatic cancer, surgical intervention is currently the only effective treatment for the extension of life. Unfortunately, only 20% of individuals are diagnosed with pancreatic cancer early enough to be surgical candidates. Reliable markers for early detection will expand the number of patients who are eligible for life-extending surgery.

The goal of the machine learning is to develop panels of markers to rapidly identify patients who have initiated early events in pancreatic cancer. Moreover, it is the goal of the machine learning protocols to identify which individuals are at risk for slow or rapid progression of the disease and catalyze the development of better early detection methods. Finally, Spherix management hopes that the machine learning approach will help identify drugs best suited for individual patient treatment.

“We believe machine learning and artificial intelligence will be an important part of the future of oncology drug development and treatment,” commented Anthony Hayes, CEO of Spherix. “We hope that this machine learning will identify a list of genetic and expression markers that reveal when aggressive pancreatic cancer has commenced in high risk patients, which may lead to the extension of life for these patients. As a company, we are very excited to support this research.”

About Spherix

Spherix Incorporated, a Delaware corporation (the “Company”), was initially formed in 1967 and is currently a biotechnology company with a diverse portfolio of small-molecule anti-cancer therapeutics. The Company’s platform consists of patented technology from leading universities and researchers and we are currently in the process of developing an innovative therapeutic drug platform through strong partnerships with world renowned educational institutions, including The University of Texas at Austin and Wake Forest University.  Our diverse pipeline of therapeutics includes therapies for pancreatic cancer, acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL). In addition, we are constantly seeking to grow our pipe to treat unmet medical needs in oncology.

Forward-Looking Statements

Certain statements in this press release constitute “forward-looking statements” within the meaning of the federal securities laws. Words such as “may,” “might,” “will,” “should,” “believe,” “expect,” “anticipate,” “estimate,” “continue,” “predict,” “forecast,” “project,” “plan,” “intend” or similar expressions, or statements regarding intent, belief, or current expectations, are forward-looking statements. While the Company believes these forward-looking statements are reasonable, undue reliance should not be placed on any such forward-looking statements, which are based on information available to us on the date of this release. These forward-looking statements are based upon current estimates and assumptions and are subject to various risks and uncertainties, including without limitation those set forth in the Company’s filings with the SEC, not limited to Risk Factors relating to its patent business contained therein. Thus, actual results could be materially different. The Company expressly disclaims any obligation to update or alter statements whether as a result of new information, future events or otherwise, except as required by law.


Investor Relations: 

Hayden IR

Brett Maas, Managing Partner

Phone: (646) 536-7331

Email: brett@haydenir.com



Phone: 212-745-1373

Email: investorrelations@spherix.com



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SOURCE Spherix Incorporated

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