Knowledge4COVID-19: A Semantic-based Approach for Constructing a COVID-19 related Knowledge Graph from Various Sources and Analysing Treatments' Toxicities

by   Ahmad Sakor, et al.

In this paper, we present Knowledge4COVID-19, a framework that aims to showcase the power of integrating disparate sources of knowledge to discover adverse drug effects caused by drug-drug interactions among COVID-19 treatments and pre-existing condition drugs. Initially, we focus on constructing the Knowledge4COVID-19 knowledge graph (KG) from the declarative definition of mapping rules using the RDF Mapping Language. Since valuable information about drug treatments, drug-drug interactions, and side effects is present in textual descriptions in scientific databases (e.g., DrugBank) or in scientific literature (e.g., the CORD-19, the Covid-19 Open Research Dataset), the Knowledge4COVID-19 framework implements Natural Language Processing. The Knowledge4COVID-19 framework extracts relevant entities and predicates that enable the fine-grained description of COVID-19 treatments and the potential adverse events that may occur when these treatments are combined with treatments of common comorbidities, e.g., hypertension, diabetes, or asthma. Moreover, on top of the KG, several techniques for the discovery and prediction of interactions and potential adverse effects of drugs have been developed with the aim of suggesting more accurate treatments for treating the virus. We provide services to traverse the KG and visualize the effects that a group of drugs may have on a treatment outcome. Knowledge4COVID-19 was part of the Pan-European hackathon#EUvsVirus in April 2020 and is publicly available as a resource through a GitHub repository ( and a DOI (


page 3

page 5

page 13

page 14

page 22

page 23


Developing a Knowledge Graph Framework for Pharmacokinetic Natural Product-Drug Interactions

Pharmacokinetic natural product-drug interactions (NPDIs) occur when bot...

COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation

To combat COVID-19, both clinicians and scientists need to digest the va...

Analysis of Conflicts between Medication, Adverse Drug Reactions and Diseases

Occurrence of adverse drug reactions (ADRs) is one of the major issues i...

Drugs4Covid: Drug-driven Knowledge Exploitation based on Scientific Publications

In the absence of sufficient medication for COVID patients due to the in...

Adverse effects of vaccinations against the Corona-virus SARS-CoV-2: insights and hindsights from a statistical perspective

Vaccinations against the virus SARS-CoV-2 have proven to be most effecti...

PHEE: A Dataset for Pharmacovigilance Event Extraction from Text

The primary goal of drug safety researchers and regulators is to promptl...

Transformer Query-Target Knowledge Discovery (TEND): Drug Discovery from CORD-19

Previous work established skip-gram word2vec models could be used to min...

Please sign up or login with your details

Forgot password? Click here to reset