With the dual threats of antibiotic resistance and emerging pandemics, finding new drugs becomes even more urgent. A trove of medicines may be lying under our nose.
Many approved drugs work on the body in ways that researchers still aren’t entirely clear about. Seeing this as an opportunity instead of a flaw may lead to better treatments for complex conditions.
Drug discovery research in Africa receives modest but essential international funding through philanthropic foundations and selected pharmaceutical companies.
While technological advancements have quickened the drug discovery process, some chemical compounds remain a common thorn in a researcher’s side.
Regulatory loopholes for research conducted off US soil allow for questionable trials and misleading data to slip under the FDA’s radar.
If no action is taken to address antibiotic resistance, infections from multidrug-resistant bacteria could cause 10 million deaths each year by 2050.
The path to using old drugs for COVID is full of potholes. So why are we using the same old flawed methods when we actually know what works?
Machine learning is great at finding patterns but doesn’t know what those patterns mean. Combine it with knowledge gained from genetic research and you have a powerful view into the workings of cells.
Artificial cells on tiny microfluidic chips can provide early insight into how new cancer drugs behave in cells, and why certain kinds of cancer are more resistant to chemotherapy treatment.
The coronavirus pandemic has driven a lot of scientific progress in the past year. But just as some of the social changes are likely here to stay, so are some medical innovations.
Scanning through billions of chemicals to find a few potential drugs for treating COVID-19 requires computers that harness together thousands of processors.
Researchers at the University of California, San Francisco, identified nine existing drugs that show promise to treat COVID-19. The proteins they target haven’t been tried before.
Among the more than 20,000 drugs approved by the FDA, there may be some that can treat COVID-19. A team at the University of California, San Francisco, is identifying possible candidates.
Pathogens rapidly evolve resistance to antibiotics. AI could keep us a step ahead of deadly infections.
As antibiotic resistance increases globally, the heat is on to find new alternatives to treat infections. Chemists can get a head start by looking at compounds produced in nature by fishes’ microbes.
Mental health is impacted by both genetic and environmental factors. But new research reveals that many mental health disorders may flow from early disturbances in fetal development.
Using a large number of computers to screen TB drugs reduces the cost and time.
People with Down syndrome are at much higher risk of dementia than the general population. Knowing when cognitive changes start is critical for developing new drugs.
Small-batch brewers are starting to tinker with biologic drugs to meet their own medical needs. A side effect of their success would be a disruption to how big pharma makes and distributes drugs.
There’s a common, popular and well-studied method to ensure new technologies are safe and effective for public use – even if researchers don’t fully understand how they work.