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SLAS Europe 2021 Digital Conference and Exhibition

Virtual Conference
June 23–25, 2021

Join Genedata experts at the SLAS Europe 2021 Digital conference.

Don't miss the opportunity to see how Genedata Screener® analyzes, visualizes, and manages screening data from in-vitro screening assay technologies across the enterprise, including very complex as well as ultra-high throughput experiments. Its screening-oriented business logic enables rapid processing and comprehensive analysis of complete campaigns.

If you would like to schedule a meeting in advance for our virtual booth or receive more information on Genedata Screener, please contact screener(at)genedata.com.

You also have the chance to find out more about our new solution, Genedata Imagence®, a high content screening (HCS) image analysis software based on deep learning. To get more information about Genedata Imagence or to arrange a meeting, please contact imagence(at)genedata.com.

Recommended Oral Presentations

The rise of high-throughput mass spectrometry for cellular profiling of early drug candidates
Martin Bachman, Medicines Discovery Catapult, United Kingdom

Technology
Wednesday, June 23 | 11:10–11:30 am CEST

Cell based assays are an important part of early drug discovery. Compared to biochemical enzyme activity assays, they present a great rise in sample complexity and come with high attrition in the numbers of candidate compounds. An ideal assay would directly reveal whether a compound has made its way to the cell, show inhibition or activation of the target enzyme, point at any downstream and off-target effects and highlight unexpected compound metabolism. High-throughput is vital due to relatively high numbers of conditions to be tested (multiple compounds, concentration points and time points). Using real-life examples, I will discuss how recent advances in high-throughput mass spectrometry get us closer to the ideal type of cellular assays, making it possible to focus on real hits very early on in the drug discovery pipeline.

Fueling Drug Discovery with AI-ready Data: Running Automated Assay Cascades in the Digital Lab
Cameron Scott, Scientific Account Manager, Genedata

Exhibitor Tutorial
Wednesday, June 23 | 12:10–13:00 pm CEST

Drug discovery is an expensive, long and uncertain endeavor. Following its successive industrialization during the past three decades, it is now undergoing a digital transformation, with the goals of better leveraging scientific creativity, distributing experience across teams, and preserving institutional knowledge while favorably tipping the cost-success balance of discovery. An important part of this process is data workflow automation, by the introduction and automation of digital lab workflows.

In many instances, the process driving the discovery cascade is compound screening. As such, robotic process automation has been pioneered in small molecule and—increasingly—biologics discovery. In this tutorial, we show how the corresponding data workflow is being realized and automated, enabling fast and rich assay cascades to fuel project team decisions and in silico predictions.

We will guide you through the automation of assay registration and experiment design, data capture, data processing, QC, analysis, and hit selection. We will touch on the required semantic annotation, quality assurance, standardization and experiment-adaptive business logic to produce FAIR data in the process. 

The results are concise, deep bioactivity result sets, where decision-ready summaries efficiently enable the scientist to plan the next experiment, and AI-ready, fully structured and annotated multivariate data sets that can inform automated in-silico predictions. A corresponding case study will be presented.

Recommended Poster Presentations

Optimizing the training step in deep learning-automated high-content analysis at sustained result quality