In the article published in the prestigious scientific journal Science, a group of international researchers, including Gorka Orive, Doctor of Pharmacy and researcher in the UPV/EHU's NanoBioCel group, and Unax Lertxundi of the Bioaraba Institute for Health Research, have issued a warning about the increase in pharmaceutical contamination.

Michigan State University (MSU) researchers are using big data and AI to identify current drugs that could be applied to treat new COVID-19 variants.

Finding new ways to treat the novel coronavirus and its ever-changing variants has been a challenge for researchers, especially when the traditional drug development and discovery process can take years.

Cancer is in Switzerland the second leading cause of death. Among the different types of cancers, non-small cell lung cancer (NSCLC) kills the most patients and remains largely incurable. Unfortunately, even newly approved therapies can extend the life of patients only by a few months and only few survive the metastatic stadium long-term.

An obscure family of viruses, already endemic in wild African primates and known to cause fatal Ebola-like symptoms in some monkeys, is “poised for spillover” to humans, according to new University of Colorado Boulder research published online Sept. 30 in the journal Cell.

A newly identified set of molecules alleviated pain in mice while avoiding the sedating affect that limits the use of opiates, according to a new study led by researchers at UC San Francisco. The molecules act on the same receptor as clonidine and dexmedetomidine - drugs commonly used in hospitals as sedatives - but are chemically unrelated to them and may not be addictive.

Glioblastoma, the most common cancerous brain tumor in adults, is an aggressive disease - patients survive an average of just 15 months once they are diagnosed. Despite more than two decades of research on the causes and treatments of glioblastoma, that prognosis has hardly improved.

Researchers at the University of Michigan Rogel Cancer Center have developed a computational platform that can predict new and specific metabolic targets in ovarian cancer, suggesting opportunities to develop personalized therapies for patients that are informed by the genetic makeup of their tumors. The study appeared in Nature Metabolism.