More than 73,000 users collaborate on new online platform set up by the European Open Science Cloud Initiative, where scientists share COVID-19 data and accelerate our understanding of the virus to help develop treatments and vaccines quicker.

A new website that allows scientists to share difficult-to-find SARS-CoV-2 data from clinical trials, research centres, hospitals and national healthcare systems, has seen thousands of users collaborating to help beat the novel coronavirus.

Researchers at UC San Francisco have developed a "digital biomarker" that would use a smartphone's built-in camera to detect Type 2 diabetes - one of the world's top causes of disease and death - potentially providing a low-cost, in-home alternative to blood draws and clinic-based screening tools.

An international task force, including two University of Massachusetts Amherst computer scientists, concludes in new research that mobile health (mHealth) technologies are a viable option to monitor COVID-19 patients at home and predict which ones will need medical intervention.

Scientists at the University of California, Riverside, have used machine learning to identify hundreds of new potential drugs that could help treat COVID-19, the disease caused by the novel coronavirus, or SARS-CoV-2.

"There is an urgent need to identify effective drugs that treat or prevent COVID-19," said Anandasankar Ray, a professor of molecular, cell, and systems biology who led the research.

Engineers at the UCLA Samueli School of Engineering and their colleagues at Stanford School of Medicine have demonstrated that drug levels inside the body can be tracked in real time using a custom smartwatch that analyzes the chemicals found in sweat. This wearable technology could be incorporated into a more personalized approach to medicine - where an ideal drug and dosages can be tailored to an individual.

Biomedical engineers at Duke University have shown that different strains of the same bacterial pathogen can be distinguished by a machine learning analysis of their growth dynamics alone, which can then also accurately predict other traits such as resistance to antibiotics.

About 50% of people who take the drug infliximab for inflammatory bowel diseases, such as Crohn's disease, end up becoming resistant or unresponsive to it.

Scientists might be able to catch problems like this one earlier in the drug development process, when drugs move from testing in animals to clinical trials, with a new computational model developed by researchers from Purdue University and Massachusetts Institute of Technology.