The U.S. drug development process for novel therapeutics targeting difficult-to-treat diseases takes an average of 10 to 12 years to complete. For drugs that go into development this year, that ...

The potential of using artificial intelligence in drug discovery and development has sparked both excitement and skepticism among scientists, investors and the general public. “Artificial intelligence ...

A team of researchers at the University of Cambridge have designed a new approach to the preclinical drug development process using machine learning, which has the potential to speed up drug ...

Continuous process improvement can benefit all aspects of life — from personal New Year’s resolutions to complex drug development. In a world where two-thirds of planned improvement initiatives fail, ...

The process of drug development can lengthy and complex, with multiple stages and regulatory requirements to be met. In the United States, the Food and Drug Administration (FDA) is responsible for ...

The shift towards sustainability in drug development focuses on reducing lab waste and enhancing operational efficiency for a ...

Partnership combines AI-powered protein manufacturing with advanced drug delivery technologies to accelerate timelines and improve therapeutic outcomes. Through this collaboration, Axio BioPharma will ...

AI drives decision inputs: In 2025, both big pharma and small pharma use advanced predictive modeling, digital twins, and AI-powered analytics throughout R&D and regulatory processes. This reduces ...

Researchers have applied AI and machine learning to every stage of the drug development process. This includes identifying targets in the body, screening potential candidates, designing drug molecules ...

The U.S. Food and Drug Administration (FDA) announced a new process called “Rare Disease Evidence Principles” (RDEP), under which eligible drugs and biologics for ultra-rare diseases caused by known ...

As drug development enters a new era, Certara is expanding its global team of scientists and technologists to lead the shift toward AI-powered testing methods.