HVH Precision Analytics announced a proprietary artificial intelligence and machine learning platform used to predict patterns and provide insights to help make informed critical business decisions.
AstraZeneca topped the first annual Pharmaceutical Invention Index, released by IDEA Pharma.
Researchers at the University of Strathclyde in Glasgow, Scotland, potentially developed a blood test for brain cancer using high-throughput attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy with machine learning.
AstraZeneca struck a deal to use Schrödinger’s advanced computing platform to help accelerate drug discovery efforts.
LabTwin’s AI-powered Digital Assistant Now Talks Back and Connects Data Sources in the Lab with New Open API
LabTwin GmbH, the world’s first voice and AI-powered digital lab assistant, announced the company’s new open API that will connect scientists with data sources both inside and outside of the lab.
Gilead Sciences Inc. will partner with privately held insitro to develop therapies for a fatty liver disease called NASH.
Oxford BioMedica announced a two-year research-and-development collaboration with Microsoft Research. The goal is to improve the yield and quality of next-generation gene therapy vectors – typically viruses – using artificial intelligence (AI) and machine learning.
Machine learning and artificial intelligence (AI) may resoundingly improve on traditional methods of drug development by biopharmaceutical companies.
If you are a clinical researcher or scientist, you are well-aware of the inefficiencies of current search processes that require hours of time wading through data to find hidden nuggets of valuable info.
Vertex and Genomics plc Establish Collaboration to Use Human Genetics and Data Science to Advance Discovery of Precision Medicines
Vertex Pharmaceuticals Incorporated and Genomics plc announced a three-year collaboration (extendable to five years) to use human genetics and machine learning to improve discovery of targets for precision medicines, and to advance understanding of the clinical impact of human genetic variation and patient stratification in diseases with significant unmet need.