February 2–6, 2019
Washington, DC, USA
Meet Genedata Screener experts at the SLAS 2019 - 8th Annual Conference & Exhibition in Washington, DC. Ask for a demonstration of Genedata Screener 16.0 at booth #1317.
To get more information about Genedata Screener, please contact firstname.lastname@example.org.
Development of high-throughput data analysis methods to bridge high-throughput APC assay with ion channel research and drug discovery
Tianbo Li, Scientist, Genentech
Automation and High-Throughput Technologies | Automating Target-based and Complex Phenotypic Drug Discovery
Tuesday, February 5 | 12:00–12:30
Ion channels regulate a variety of physiological processes and represent the second largest class of known drug targets. Among the known methods to study ion channels, patch clamp electrophysiology remains the gold standard with its unsurpassable precision in all ion channel functional assays. The automated patch clamp (APC) screening technology has emerged to meet the challenge of scaling up this gold-standard method. However, due to the complexity of electrophysiological data, the fast-increasing APC throughput is facing a major challenge when it comes to robustly analyzing the data. Here I will discuss our recent breakthrough in this challenge by co-developing high-throughput screening data analysis methods with Genedata. To match our daily throughput of ~8,000 Nav channel recordings from the Nanion SyncroPatch 768PE, a data reduction stategy was used to reduce the original recording 1st level data size by ~1,000 times. Then the 2nd level data with more than 100,000 recordings can be analyzed by Genedata Screener® as one experiment. To ensure high data quality, an automated quality control method was developed by optimizing four key parameters: seal resistance, peak current, capacitance, and series resistance. Additionally, a customized SyncroPatch data analysis method was developed for Screener® to directly handle the 1st level raw data for kinetic characterization of Nav channel currents. Overall, the fast advancing APC high-throughput technologies together with the robust and high-throughput data analysis methods will have a significant impact on ion channel research and drug discovery.
A new enterprise solution for efficient processing of biosensor data (SPR/BLI) for large-molecule screening, antibody characterization and Epitope Binning
Evan Mulligan, Scientific Account Manager, Genedata
Tutorial | Monday, February 4 | 2:00 pm - 2:45 pm | room 150A
Biolayer Interferometry (BLI) and Surface Plasmon Resonance (SPR) technologies are invaluable for high-precision determination of biomolecular interaction parameters. These parameters are critical for timely selection and optimization of the best antibody candidates and thus crucial for success. Novel instrumentation (e.g., PALL FortéBio Octet HTX, Sierra Sensors SPR-32 , GE Biacore 8K) allows measurements at unprecedented throughput and enable the larger screening campaigns. However, rapidly and consistently analyzing the acquired data creates a challenge.
In this tutorial we present Genedata Screener® for Biopharma, a unique software solution for data analysis in Biopharma research and exemplified here for the analysis of SPR and BLI data. We highlight two use cases:
We will conclude the tutorial by showing how this solution embeds in an enterprise infrastructure, exemplifying with its integration into the Genedata Biopharma platform. The platform manages raw and processed data in a centralized environment, making the measured results available to the entire organization and ensuring an efficient and scalable process, ultimately leading to higher productivity.
Genedata Imagence: A new deep learning-based enterprise solution dramatically increases efficiency in HCS image analysis
Stephan Steigele, Head of Science, Genedata
Tutorial | Tuesday, February 5 | 9:30 am - 10:15 am | room 151A
Image analysis for High Content Screening (HCS) is a labor-intensive and error prone process, with multiple data hand-overs and operational complexity. As early drug discovery increasingly relies on complex phenotypic assays as biologically relevant model systems, the consequences of employing a time-consuming and repetitive analysis process are magnified.
During this tutorial, we show the future of HCS image analysis enabled by Genedata Imagence, and how this solution efficiently automates HCS image analysis. An outstanding feature of this new solution is that it does not require technical expertise beyond that of an assay biologist to annotate images, and our deep learning-based workflow makes this an extremely efficient process enabling higher throughput and improved quality. We show how one can, unhindered by IT-related issues, rapidly detect and define all cellular phenotypes in a high-content screen, with the final goal to precisely quantify relevant pharmacology.
The software dramatically reduces the time and costs usually associated with manually optimizing the image analysis to produce quality results for a new screening experiment, going from weeks to just hours or minutes. Genedata Imagence fully automates HCS image analysis, enabling organizations to focus on the pharmacology and biology of their research rather than on technical details and ultimately increase their ROI with a much more cost-efficient drug screening.
Compound Combination Special Interest Group (SIG)
Rajarshi Guha and Oliver Leven, chairs
Wednesday, February 6 | 8:00 am - 9:00 am |
The mission of the SLAS Compound Combination Screening SIG is to create a knowledge-sharing forum for screening practitioners active in the field of compound combinations. As such, the goal is to mature the field of compound combination screening, aimed at better science that accelerates the pace of drug discovery.