ELRIG Drug Discovery
October 4–5, 2022
Join Genedata experts at the ELRIG Drug Discovery conference in London, UK.
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. You also have the chance to find out more about Genedata Imagence, a high content screening (HCS) image analysis software based on deep learning. To get more information about our software or to arrange a meeting, please contact screener(at)genedata.com or imagence(at)genedata.com, respectively.
Recommended Oral Presentation
Automated Analysis Workflow to Identify Metal Contamination in HTS Outputs
Rachel Moore, Hit Discovery, Discovery Sciences, R&D, AstraZeneca, Alderley Park, UK
Advancements in Screening and Automation
Wednesday, October 5 | 11:20 am – 12:20 pm
Large compound libraries utilised for high throughput screening often include metal contaminated compounds which can interfere with assay signal or target biology, and therefore appear as hits.
Pursuit of these compounds can divert considerable time and resource away from more propitious hits. Within AstraZeneca we have developed and implemented novel high throughput assays utilising Acoustic-Mist Ionisation MS (AMI-MS)1 to identify metal contaminated compounds in high-throughput2. These assays have facilitated rapid delivery of high quality and cleaner hit chemistry to project teams; however, the current analysis process is limited. In collaboration with Genedata we have developed an efficient workflow to aid analysis. Here, we will discuss the use of Genedata Expressionist and Screener to automatically assess metal presence, determine metal identity, and flag contaminated compounds directly from MS spectra.
1. Sinclair, I.; Bachman, M.; Addison, D.; et al. Acoustic Mist Ionization Platform for Direct and Contactless Ultrahigh-Throughput Mass Spectrometry Analysis of Liquid Samples. Analytical Chemistry 2019, 91, 3790-3794.
2. Molyneux, C.; Sinclair, I.; Lightfoot, H. L.; et al. High-throughput detection of metal contamination in HTS outputs. SLAS Discovery 2022.