COVID-19 Drug Repurposing Datasets Now Available in Collaboration with Vectorspace AI, Amazon & Microsoft


SAN FRANCISCO, March 26, 2020 /PRNewswire/ — Vectorspace AI (VXV), a Natural Language Processing and Understanding (NLP/NLU) company, announces the availability of real-time COVID-19 (Coronavirus SARS-CoV-2) drug repurposing datasets in collaboration with Amazon and Microsoft in connection with the United States Office of Science and Technology Policy (OSTP). “One of the most immediate and impactful applications of AI is in the ability to help scientists, academics, and technologists find the right information in a sea of scientific papers to move research faster. We applaud the OSTP, WHO, NIH and all organizations that are taking a proactive approach to use the most advanced technology in the fight against COVID-19,” said Dr. Oren Etzioni, Chief Executive Officer of the Allen Institute for AI.

Every 24 hours, thousands of bioscientific research papers are published around the world through the National Library of Medicine (NLM) and other sources including the COVID-19 Open Research Dataset (CORD-19) composed of scientific literature directly related to COVID-19, SARS-CoV-2, and the Coronavirus group along with LitCovid, a curated literature hub for tracking up-to-date scientific information about the 2019 novel Coronavirus.

Using these and other related data sources, Vectorspace AI generates real-time updating correlation matrix datasets. These are designed to extract context-controlled hidden relationships between genes, proteins, phytochemicals, drug compounds and infectious diseases such as COVID-19, designed for drug repurposing (repositioning). The first dataset available includes a focus on the following approved drug compounds: Alvesco, Ampicillin, Arbidol, Azilsartan, Azithromycin, Candesartan, Clindamycin, Daraprim, Favipiravir, Fimasartan, Galidesivir, Hydroxychloroquine, Interferon α2b, Interferon β, Irbesartan, Kevzara, Lopinavir, Losartan , Mefloquine, Olmesartan, Primaquine, Pyrimethamine, Qualaquin, Remdesivir, Ribavirin, Ritonavir, Saprisartan, Telmisartan, Valsartan, and Zithromax.

“Our team and community are eager to join the fight against SARS-CoV-2 and any future viral threats by offering free subscriptions and VXV token credits granting free access to our wallet-enabled APIs which generate these kinds of datasets,” stated Kasian Franks, founder, CEO and Chief Visionary Officer of Vectorspace AI.

Currently, datasets are made available through the Vectorspace wallet-enabled API free VXV token credits located here: https://vectorspace.ai/api-covid-19.html

Research institutions and individuals are encouraged to contact Vectorspace AI via [email protected] or by visiting https://vectorspace.ai for additional information on how to acquire customized context-controlled correlation matrix datasets connected to data sources in the area of infectious diseases and associated therapeutics. Datasets can be used to augment any other extant datasets or be used on their own to generate graph networks to visualize hidden relationships.

About Vectorspace AI (vectorspace.ai)

Vectorspace AI focuses on context-controlled NLP/NLU (Natural Language Processing/Understanding) and feature engineering for hidden relationship detection in data for the purpose of powering advanced approaches in Artificial Intelligence (AI) and Machine Learning (ML). Our platform powers research groups, data vendors, funds and institutions by generating on-demand NLP/NLU correlation matrix datasets. We are particularly interested in how we can engineer machines to trade information with one another or exchange and transact data in a way that minimizes a selected loss function. Our objective is to enable any group analyzing data to save time by testing a hypothesis or running experiments with higher throughput. This can increase the speed of innovation, novel scientific breakthroughs and discoveries. For a little more on who we are, see our latest reddit AMA on r/AskScience. Vectorspace AI offers NLP/NLU services and alternative datasets consisting of correlation matrices, context-controlled sentiment scoring and other automatically engineered feature attributes. These services are available utilizing the VXV token and VXV wallet-enabled API. Vectorspace AI is a spin-off from Lawrence Berkeley National Laboratory (LBNL) and the U.S. Dept. of Energy (DOE). The team holds patents in the area of hidden relationship discovery.

SOURCE Vectorspace AI

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