Drug repurposing (or repositioning) is the process of finding new therapeutic uses for drugs already approved by drug regulatory authorities (e.g., the Food and Drug Administration (FDA) and Therapeutic Goods Administration (TGA)) for other diseases. This involves analyzing the interactions between different biological entities, such as drug targets (genes/proteins and biological pathways) and drug properties, to discover novel drug-target or drug-disease relations. Artificial intelligence methods such as machine learning and deep learning have successfully analyzed complex heterogeneous data in the biomedical domain and have also been used for drug repurposing. This study presents a novel unsupervised machine learning framework that utilizes a graph-based autoencoder for multi-feature type clustering on heterogeneous drug data. The dataset consists of 438 drugs, of which 224 are under clinical trials for COVID-19 (category A). The rest are systematically filtered to ensure the safety and efficacy of the treatment (category B). The framework solely relies on reported drug data, including its pharmacological properties, chemical/physical properties, interaction with the host, and efficacy in different publicly available COVID-19 assays. Our machine-learning framework reveals three clusters of interest and provides recommendations featuring the top 15 drugs for COVID-19 drug repurposing, which were shortlisted based on the predicted clusters that were dominated by category A drugs. The anti-COVID efficacy of the drugs should be verified by experimental studies. Our framework can be extended to support other datasets and drug repurposing studies, given open-source code and data availability.

The decisions that we make now and in the near future will set the tone for the rest of the decade including how artificial intelligence (AI) may develop and how we will use it. It will require enlightened leadership to maximise the benefit for human society. This article is focused on providing a moment of reflection in terms of where we are and where we are going from a policy and philosophical perspective and to serve as a prelude to a more technical article on the next generation of AI that will follow. Positive use case potential for AI includes the fight against Covid -19. For example The Lancet published an article authored by Zhou et al. entitled "Artificial Intelligence in COVID-19 drug repurposing" and state that " In this Review, we introduce guidelines on how to use AI for accelerating drug repurposing or repositioning, for which AI approaches are not just formidable but are also necessary. We discuss how to use AI models in precision medicine, and as an example, how AI models can accelerate COVID-19 drug repurposing."

The decisions that we make now and in the near future will set the tone for the rest of the decade including how artificial intelligence (AI) may develop and how we will use it. It will require enlightened leadership to maximise the benefit for human society. This article is focused on providing a moment of reflection in terms of where we are and where we are going from a policy and philosophical perspective and to serve as a prelude to a more technical article on the next generation of AI that will follow. Positive use case potential for AI includes the fight against Covid -19. For example The Lancet published an article authored by Zhou et al. entitled "Artificial Intelligence in COVID-19 drug repurposing" and state that " In this Review, we introduce guidelines on how to use AI for accelerating drug repurposing or repositioning, for which AI approaches are not just formidable but are also necessary. We discuss how to use AI models in precision medicine, and as an example, how AI models can accelerate COVID-19 drug repurposing."

INDIANAPOLIS--When Covid-19 struck, drug companies around the world began racing to find vaccines and treatments. One factor has gummed up their efforts: They have to work in an environment transformed by the very problem they are trying to tackle. At Eli Lilly & Co., the chief of a laboratory, quarantining at home after he contracted Covid-19, had to use a robot equipped with an iPad to patrol his lab. When shipping constraints threatened to delay testing of an experimental drug, Lilly repurposed its corporate jet to get vials...

The year of 2020 has proved to be a challenging year defined mostly across the world by a global pandemic and as a result an increasing shift towards digital. The decisions that we make now and in the near future will set the tone for the rest of the decade including how AI may develop and how we will use it. It will require enlightened leadership to maximise the benefit for human society. This article is focused on providing a moment of reflection in terms of where we are and where we are going from a policy and philosophical perspective and to serve as a prelude to a more technical article on the next generation of AI that will follow. Positive use case potential for AI includes the fight against Covid -19.

In the big data era, artificial intelligence (AI) and network medicine offer cutting-edge application of information science to defining disease, medicine, …

In a short period, many research publications that report sets of experimentally validated drugs as potential COVID-19 therapies have emerged. To organize this accumulating knowledge, we developed the COVID-19 Drug and Gene Set Library (https://amp.pharm.mssm.edu/covid19/), a collection of drug and gene sets related to COVID-19 research from multiple sources. The platform enables users to view, download, analyze, visualize, and contribute drug and gene sets related to COVID-19 research. To evaluate the content of the library, we compared the results from the six in-vitro drug screens for COVID-19 repurposing candidates. Surprisingly, we observe low overlap across screens while highlighting overlapping candidates that should receive more attention as potential therapeutics for COVID-19.