In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of drug discovery.

Industrial sustainability advances with better recycled metals, AI-sorted plastics, clean energy labs, energy-harvesting ...

Discover how researchers are overcoming the limitations of the undruggable target in drug discovery using novel approaches ...

Scholars warn that replacing animal testing too quickly may threaten drug safety. As the FDA promotes AI and organoids, ...

Researchers at the Museum für Naturkunde Berlin, together with data scientists, have developed a new method to largely ...

The field of infectious disease epidemiology is continually challenged by the emergence and re-emergence of pathogens, which can have profound societal, ...

India is urged to adopt cruelty-free, science-driven drug testing methods to boost its pharmaceutical industry. A new report ...

The University of Liverpool has partnered with Boston-based BPGbio, Inc. to use artificial intelligence to accelerate the discovery of new medicines through its Civic HealthTech Innovation Zone, ...

Evolving toxicity assessments for engineered nanoparticles underline the importance of predictive models and life-cycle risk ...

Researchers at the Department of Energy's Oak Ridge National Laboratory have developed a deep learning algorithm that ...

Two Princeton professors, Molly Crockett and Sebastian Seung, have been named recipients of National Academy of Sciences awards for their work in moral cognition and computational neuroscience, ...

Leaders across research, clinical care, industry, and patient advocacy convene to accelerate rare disease breakthroughs from discovery to real-world patient impact NORWELL, Mass., Feb. 5, 2026 ...