Find out how industry leaders are using Genedata Imagence® deep learning-based software to make better decisions.
AstraZeneca Accelerates Drug Discovery with Deep Learning.
At ELRIG Drug Discovery 2021, James Robinson of AstraZeneca, detailed how deep learning can effectively be applied to high content image analysis. In his presentation, he gave real-life examples where deep learning has been applied to projects at AstraZeneca, with benefits such as:
Development of assays previously not feasible
Increased assay data robustness
Time savings due to automated analysis
Identification of novel phenotypes
Watch James' presentation to learn how deep learning helps automate image analysis and truly accelerates drug discovery.
A Recognized Real Solution for HCS Analysis.
There’s a lot of buzz about AI-based approaches, but industry leaders everywhere recognize that Genedata Imagence is not hype: it’s a real-world, enterprise-quality solution that you can apply today to get real results out of your HCS analysis.
Genedata Imagence empowers biologists to immediately explore and interpret data for a wide array of assays with comparable or better results than traditional workflows—at faster and more efficient rates
Customer Kudos for Genedata Imagence.
Through our Genedata Imagence Pilot Program, many forward-thinking pharma biopharmaceutical companies and screening centers have experienced the power of the solution. They’ve learned that Genedata Imagence demonstrates high performance across a range of assays, unveiling new insights and enabling assay biologists to systematically and rapidly explore their data. Learn for yourself what scientists have to say about Genedata Imagence.
The real impact was being able to apply deep learning to classify phenotypes from images, and being able to do it in a way that was part of sort of a “business-as-usual” workflow… as a more accessible technology for biologists.
James Pilling Associate Principal Scientist
The tool offers real advantages for working biologists.