Traditional drug development methods involve identifying a target protein (e.g., a cancer cell receptor) that causes disease, ...

The novel drug candidate has the potential to restore the effectiveness of a potent antibiotic against deadly drug-resistant ...

In a significant step forward in the global fight against antibiotic resistance, IIT-Roorkee researchers have developed a new ...

Organoids paired with nanoparticles could offer new insights into cancer treatment, improving predictions of drug efficacy ...

Before the drug development process commences, scientists conduct computational studies, cellular assays, and genomic and proteomic research to identify a specific target molecule, such as an RNA ...

Targeted drug delivery to tumors is crucial for effective and safe treatment of cancer. In a recent breakthrough, researchers ...

One of the projects supported by that funding is showing real promise: a new drug discovered by Ohio State University ...

Orr Inbar, CEO and co-founder of QuantHealth, unpacks the growing frustration over drug prices and the misperceptions fueling distrust in the pharmaceutical industry. With clinical trials now more ...

A major challenge in using AI for drug development is the need for high-quality data. AI models require consistent, comprehensive and well-annotated data to make accurate predictions.

The company, which was developing a drug for children with an unspecified rare disease, presented its plan for a Phase 3 efficacy trial. Opler says, “The FDA attendees asked why the sponsor was ...