Using real-world data from a hospital in China, the UC Riverside-led study found that individual characteristics, including age, weight, and additional illness determine which drug combinations most effectively reduce recurrence rates.
In recent years, researchers have begun using computational methods to screen those libraries in hopes of speeding up drug discovery.
The peer-reviewed journal Cell Reports Physical Science published research showing the efficacy of her AI-detection method, along with sufficient source code for others to replicate the tool.
Today, most drug discovery is carried out by human chemists who rely on their knowledge and experience to select and synthesize the right molecules needed to become the safe and efficient medicines we depend on.