Find out how self-driving labs utilise data-driven approaches to enhance drug discovery efficiency and innovation.

Explore SLAS Boston 2026 insights on connecting laboratory automation and data infrastructure in drug discovery workflows.

TOKYO--(BUSINESS WIRE)--Elix, Inc. (CEO: Shinya Yuki / Headquarters: Tokyo; hereinafter “Elix”) is pleased to announce that its AI drug discovery platform, Elix ...

Bruker's Acquifer Imaging Machine (IM) is a fully automated widefield microscope with both brightfield and fluorescence imaging capabilities. It is best suited for high-content screening (HCS) and ...

Regina Barzilay is a School of Engineering Distinguished Professor of AI & Health in the department of computer science and the AI faculty lead at MIT Jameel Clinic. She develops machine learning ...

Avner Schlessinger, PhD, right, working with his lab researchers at Mount Sinai AI Small Molecule Drug Discovery Center in New York City. [Mount Sinai] Most breakthrough discoveries are made based on ...

New approach methodologies (NAMs) aim to address the limitations of animal models by assessing drug efficacy and safety in a more ethical, human-relevant way. The term ‘NAMs’ encompasses several ...

AI boosts efficiency in early, high-failure R&D, improving success rates and capital efficiency across biotech and pharma. Biotech uses AI for breakthrough discovery, while large pharma scales it to ...