You are invited to attend our exhibitor tutorial “An advanced flow cytometry solution for screening an immunomodulatory-based SAR compound library harnessing turnkey software analysis for rapid data visualization".
Presenter: John O’Rourke, Head of Product Development, Cell Analytics
Date: Tuesday, January 28, 2020
Time: 2:00 PM - 2:45 PM
Visit our booth at SLAS to learn about our innovative platforms and products.
- Intellicyt iQue®3 - The most advanced flow cytometry platform with a focus on speed from setup, to acquisition, and analysis. To get you from samples to actionable results in record time. The iQue3 combines a patented sampling method which allows for the fastest sample acquisition in the industry. It has the ability to handle 96, 384 well plates and enables continuous plate loading through connection with any automation system.
- IncuCyte® S3 Live-Cell Analysis System - real-time quantitative live-cell imaging and analysis platform that enables visualization and quantification of cell behavior over time by automatically gathering and analyzing images around the clock within a standard laboratory incubator.
- Sartorius Lab Essentials Product Range - including industry-leading lab balances plus a range of pipettes, consumables, lab water and lab filtration systems.
- CompacT SelecT - Automated cell culture system for high quality cells and assay ready plates suitable for small & medium throughput laboratories..
- ambr® 250 modular - innovative, easy-to-use, expandable benchtop system that incorporates from 2 to 8 fully integrated single-use 100 – 250 mL mini bioreactors for microbial fermentation and mammalian cultures.
Exhibitor Tutorial Description: Efficient execution of large drug screens requires innovation in instrumentation and data analysis to more rapidly identify potential drug candidates. In this presentation, we will demonstrate how the Intellicyt®iQue3 advance flow cytometer uses walkaway automation tools such as plate loading, calibration, cleaning and intelligent reagent level sensing to simplify your drug screening studies. Using a structure activity relationship (SAR) compound library screen on PBMCs, we measured multiple parameters including cell viability, immunophenotyping and cytokine secretion in a miniaturized assay format on the iQue3. We overcame the data analysis bottleneck associated with screening experiments using our integrated ForeCyt Software tools. Compounds that promote cytokine and T cell activation were identified by rapid, multiparametric data analysis and novel data visualization, including multiplate data analysis using our Panorama feature. In summary, the Intellicyt iQue platform offers automated set up, acquisition and data analysis to collect and interpret 18,000 data points quickly and reliably, resulting in faster time to actionable results.
The time spent analyzing the current experiment and correlating that to previous experiments can take up valuable time which could be better spent on planning for the follow up or report out of the data. The ultimate goal is to reach some actionable answer as quickly as possible and to be able to communicate the outcome to others by exporting the data in a meaningful way.
Visit our poster “Automating Pattern Recognition in High Content Screening and Biomarker-dependent Patient Stratification with Advanced Flow Cytometry and Machine Learning”
The search for innovative therapies via candidate drug screening requires a funnel of biological assays to characterize drug signatures and move candidates into clinical trials. In addition, patient stratification is critical in bio-therapeutic drug discovery, including chimeric antigen receptor T (CAR-T) cell therapy, to stratify patients based on biomarkers. Biomarkers can identify the potential drug-responsive patient group for priority treatment in clinical trials to maximize the likelihood of a positive clinical outcome. The Intellicyt® iQue Platform is an advanced flow cytometry technology featuring high throughput multiplex capability and fast acquisition speed, which is tailored for high content screening and biomarker profiling. A high dimensional data set with enormous data points presents analytical challenges to unravel the complex biochemistry needed to provide meaningful biological signatures of drug candidates and samples from potential patients for insight-driven decision making. Clustering and dimension reduction are two bread-and-butter techniques in machine learning to visualize high dimensional data. Here we combine these two techniques with the iQue platform to explore the possibility to automate pattern recognition in drug screening and patient stratification.
As a proof of concept, we screened a kinase chemogenomic library with 152 inhibitors in an 8-color assay to look for T cell activation modulators, and profiled 12 patients’ peripheral blood mononuclear cell samples with a 13-color immune panel on iQue platform. Samples were acquired in 20 minutes per plate. Pre-analyzed data metrics were exported from iQue ForeCyt software and re-analyzed by Python programming language with unsupervised machine learning algorithms. Two groups of inhibitors were determined by elbow and K-means algorithms. In addition, dimension reduction algorithm either tSNE or PCA was adopted for better visualization. The result showed two groups of the screening wells automatically surrounding 2 control well sets (the positive/negative), while the unsupervised machine learning did not know the labeling of control wells during the computation. More interestingly, 12 compounds were identified with similar patterns as the well-known Jak1/2 inhibitor drug ruxolitinib, and a compound with highly similar pattern as ruxolitinib in tSNE plot was confirmed to have approximate quantitation in almost every single endpoint, which demonstrates the effectiveness of unsupervised learning in pattern recognition. In a separate biomarker profiling study with a 12-patient cohort, 11 cytokines and 13 cellular endpoints were profiled.