AIkido Pharma Inc. Announces Key Progress in Computational Approaches to Identify Virus Treatments, Including Coronavirus

Rhea-AI Summary

AIkido Pharma Inc. (Nasdaq: AIKI) announced progress in identifying antiviral compounds aimed at combating COVID-19. Following an April 2020 agreement with the University of Maryland, researchers discovered a human protein complex linked to virus replication. Using a method called SILCS, they found compounds that inhibit various viruses, including COVID-19 and Influenza. CEO Anthony Hayes emphasized the role of machine learning in accelerating drug research, ultimately aiming to develop compounds that effectively treat multiple viral infections.

Positive

• Identified compounds blocking multiple viruses, including COVID-19 and Influenza.
• Utilization of machine learning to accelerate antiviral compound identification.

Negative

• None.

NEW YORK, July 9, 2020 /PRNewswire/ -- AIkido Pharma Inc. (Nasdaq: AIKI) ("AIkido" or the "Company") today provided an update on its effort to identify compounds to potentially address the COVID-19 pandemic. As previously announced, on April 13, 2020, AIkido executed a Master License Agreement with the University of Maryland, Baltimore ("UMB"), covering certain antiviral compounds discovered by UMB.

Recently, the researchers at UMB, including Matthew Frieman, PhD, Associate Professor of Microbiology and Immunology at the University of Maryland School of Medicine (UMSOM),  Alexander MacKerell, PhD, Professor of Pharmaceutical Sciences at the University of Maryland School of Pharmacy, and Stuart Weston, PhD, Postdoctoral Fellow at UMSOM, have identified a human protein complex (called the SKI complex) that is important for replication of several viruses including Influenza, COVID-19, SARS1, MERS, SARS2, Ebola and Marburg.  Using a computer modeling approach called SILCS from SilcsBio LLC, chemical compounds were identified that are predicted to bind to a pocket on a human protein in this complex. These compounds were tested for their ability to block replication of the Influenza virus in human cells, from which several active compounds were found. These compounds were then tested against the other viruses and found to block replication of these as well. Utilizing the information gleaned from this initial research and the power of the SILCS technology combined with machine learning tools, the researchers are currently identifying compounds with chemical structures similar to the active compounds and testing them to find ones that work better at blocking virus replication.

"This is encouraging progress, demonstrating the importance of machine learning to accelerate pharmaceutical research," commented Anthony Hayes, CEO of AIkido. "Legacy processes, involving manually testing potentially thousands of compounds, are slower and potentially more expensive. Utilizing a combination of a physics-based approach and machine learning, our partners are able to significantly narrow the range of potential compounds to test, accelerating efforts and significantly reducing costs. The ultimate goal is to create a new compound that blocks replication of a wide variety of viruses in humans that will be an effective drug for the treatment of known viral infections as well as those that may arise in the future."

About AIkido

AIkido was initially formed in 1967 and is 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 pipeline to treat unmet medical needs in oncology.  The Company is also developing a broad spectrum antiviral platform that may potentially inhibit replication of multiple viruses including Influenza virus, SARS-CoV (coronavirus), MERS-CoV, Ebolavirus and Marburg virus.

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 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.

Contact:
Investor Relations:	Hayden IR
	Brett Maas, Managing Partner
	Phone: (646) 536-7331
	Email: brett@haydenir.com
	www.haydenir.com
AIkido:	Phone: 212-745-1373
	Email: investorrelations@AIkido.com
	www.AIkido.com

 

 

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SOURCE AIkido Pharma Inc.

FAQ

What progress has AIkido Pharma (AIKI) made in antiviral research?

AIkido Pharma announced significant progress in identifying antiviral compounds to address COVID-19, utilizing computational modeling and machine learning.

When did AIkido Pharma execute a Master License Agreement with the University of Maryland?

AIkido Pharma executed a Master License Agreement with the University of Maryland on April 13, 2020.

What method did researchers use to identify antiviral compounds?

Researchers at AIkido utilized a computer modeling approach called SILCS from SilcsBio LLC to identify antiviral compounds.

Which viruses can the identified compounds potentially inhibit?

The identified compounds have potential to inhibit viruses like COVID-19, Influenza, SARS, MERS, Ebola, and Marburg.