Optimizing Flow Cytometry for Screening and Drug Discovery

Optimizing Flow Cytometry for Screening and Drug Discovery Sample processing speed Workforce Data analysis Multiplexing capabilities with five lasers and 30 detectors 24/7 with a single operator using high-capacity fluidics tanks 100,000 events per sec without data loss or compromised resolution Automate Integrates with laboratory robotics system via a device-agnostic API 96-well plates in < 15 min 384-well plates in < 60 min without data loss or compromised resolution Discover a flow cytometer built for high-throughput screening Unlock the Power of High-Throughput Flow Cytometry with the ZE5 Cell Analyzer Visit: Bio-rad.com/ZE5 COMPOUND LIBRARIES High-throughput screening (HTS) is a key strategy in drug discovery, as it allows for rapid automated testing of large libraries of compounds to assess their effect on specific biological targets. While flow cytometry is ideal for multiparametric analysis of cells, it has traditionally been too slow in processing large libraries to gain widespread use in HTS. However, recent technological advances have removed several process bottlenecks and turned flow cytometry into a powerful high-throughput tool that can be used for many types of assays. This infographic presents recent key innovations – from sample loading through to data analysis – that ensure reliable, high-throughput, automated flow cytometry workflows. The ZE5 Cell Analyzer is an innovative, versatile flow cytometer that allows you to complete reliable, automated high-throughput screening. The first limiting factor of any HTS workflow is the speed at which the instrument can process samples. Increasingly faster flow cytometers can solve this thanks to: High event rate: Cutting-edge instruments can capture up to 100,000 events per second. The cytometer must have an adequate Application Programming Interface (API) library to increase functionality. Low maintenance and minimal downtime: Reliable fluidics with reversible pump and unclog features. Advantages of automation include: Avoid sample carryover: An integrated wash station travels with the probe, cleaning it thoroughly between each sample. High multiplexing capabilities and sample formats. Rapid cycling through samples: Introducing air spaces in the line without destabilizing flow allows samples to be rapidly analyzed sequentially while remaining recognizably distinct. Instruments that allow the integration of Laboratory Information Management Systems (LIMS) can streamline the process even further. As sample processing becomes faster, prepping and loading plates becomes the limiting factor. Flow cytometers with automation capabilities can overcome this hurdle. High volumes of data require new strategies for analysis and interpretation. Data analysis represents a bottleneck due to: Implementation of AI and machine learning techniques offers promise in addressing these challenges and can already be used for: However, many challenges remain including the need for: Continuous operation Improved reproducibility Increased throughput Improved data integrity • High dimensionality • Large data sets • Data heterogeneity • Dimensional reduction (tSNE and UMAP) • Automated cell population identification • Sample classification to predict clinical or biological outcomes • More robust analysis of heterogeneous data sets • Better use and integration of existing biological knowledge into analysis • Greater availability and standardization of data NEW DRUGS 120,000 – 100,000 – 80,000 – 60,000 – 40,000 – 20,000 – 0 – 0 20,000 40,000 60,000 80,000 100,000 120,000 – – – – – – – Expected count, sec Measured count, sec