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Emerging AI/ML Technologies for Drug Discovery

It is widely known that the traditional drug discovery and development process is extremely time-consuming, expensive and challenging; taking an […]

An Overview of AI/ML for CNS Drug Discovery

Due to the complex nature of central nervous system diseases and the presence of the blood-brain barrier (among other factors), […]

Characterising Multi-Target Compounds Using ML

A recent study, published in Scientific Reports, designed a test system using machine learning to systematically examine the structural features […]

Rapid ML Screening Identifies Potential Drug Compounds For SARS-CoV-2

At the time of writing, there have been 137 million cases and nearly 3 million deaths from COVID-19. Although some targets […]

Epigenetic Target Fishing Using ML

Epigenetic targets are of significant importance in drug discovery research, and there is increasing availability of chemogenomic data related to […]

DRUML: Using ML to Rank Cancer Drugs in Order of Efficacy

Researchers at Queen Mary University of London have developed a machine learning algorithm – DRUML – that ranks drugs based […]

Using ML to identify responders vs non-responders

We summarise a recent study, published as preprint in medrxiv, that explored the hypothesis that a data-driven analysis of a […]

ML framework predicts anti-cancer drug efficacy

Researchers have developed a machine-learning (ML) framework to identify robust drug biomarkers and thereby, predict anti-cancer drug efficacy. Biomarker identification […]

Predicting near-term COVID-19 mortality using an ML-based approach

A team of researchers have developed a machine learning (ML)-based algorithm to analyse electronic health record (EHR) data and reliably […]

The role of EMR and ML in drug development

Here, we summarise a chapter in Artificial Intelligence in Oncology Drug Discovery and Development, which explored the role of electronic […]