Common challenges faced with existing flow cytometry software include speed, ability to create complex visualizations of large studies and meeting regulatory compliance. CellEngine was built from the ground-up by CellCarta to solve these challenges.
Today, CellEngine has been used to analyze nearly 5 million Flow Cytometry Standard (FCS) files in record time by users around the world. Analysis pipelines containing FlowSOM (which analyzes Flow or mass cytometry data using a Self-Organizing Map), UMAP (Uniform Manifold Approximation and Projection), PCA (Principal Component Analysis) and t-SNE (t-Distributed Stochastic Neighbor Embedding) can be run on millions of cells in seconds to minutes. A large variety of metadata-driven visualizations can be created, including ones combining categorical and continuous study metadata with the cytometry data.
As a cloud-based application, CellEngine makes it easy to collaborate with colleagues while keeping your data safe, secure and centrally organized. Its application programming interface (API) makes it possible to integrate with bioinformatics pipelines, Electronic Laboratory Notebooks (ELNs), Laboratory Information Management Systems (LIMSs) and more. CellEngine is rigorously validated, has an industry-leading uptime service-level agreement (SLA) and has all of the features required for use in Title 21 of the US Code of Federal Regulations (CFA), Part 11 compliant environments. Dr. Zachary Bjornson-Hooper will highlight these and other features in an introduction to CellEngine.
Dr. Dave McIlwain will discuss using CellEngine to decode host immune responses to acute infection with influenza, SARS-CoV-2 and Ebola viruses. The combination of large panels, large numbers of samples and multiple data modalities made CellEngine uniquely suited to analyze these studies. The findings Dr. McIlwain will present reveal the characteristics of acute disease, vaccine-induced protection and survival.
Two of the defining characteristics of CellEngine are its speed and its rich application programming interface. Dr. Federico Gherardini will cover how these features can be leveraged in modern data analysis workflows that enable reproducible analysis of datasets comprising thousands of samples.
Register for this webinar to learn how to achieve fast, complex visualizations of cytometry data and meet regulatory requirements.
Zachary Bjornson-Hooper, PhD, Sr. Director, Informatics, CellCarta
Dr. Bjornson-Hooper completed his undergraduate studies in biology at the Massachusetts Institute of Technology and earned his PhD in microbiology and immunology at Stanford University. He has extensive wet lab experience in comparative immunology, flow and mass cytometry and viral genomics, including leading the development of an atlas of immune signaling responses in various animal models relevant to infectious disease research. Additionally, he has 15 years of experience in bioinformatic analysis of CyTOF, flow cytometry and viral metagenomic data. At CellCarta, he oversees the development of the CellEngine single-cell analysis platform.Message Presenter
Dave McIlwain, PhD, Senior Research Scientist, Stanford University School of Medicine, Nolan Lab
Dr. McIlwain studies host response to infections using high-dimensional single-cell and spatial proteomics tools. He trained for his PhD at the University of Toronto, yielding insights into alternative mRNA splicing and iRhom2 as a new factor controlling the production of inflammatory mediator TNF. As a post-doctoral fellow, Dr. McIlwain investigated host response to viral infection in animal models at the University of Dusseldorf in Germany before moving to Stanford University where, along with Dr. Garry Nolan, he leads a team executing research contracted by the FDA’s Medical Countermeasures Initiative to study emerging pathogens. This work includes mass cytometry (CyTOF) and spatial proteomic (CODEX) single-cell analysis of human and animal model influenza, Ebola, zika and SARS-CoVs infections.Message Presenter
Pier Federico Gherardini, PhD, Computational Biology Consultant, Pragmatica.Bio
Dr. Gherardini has 14 years of experience in computational biology and bioinformatics. Dr. Gherardini obtained his PhD from the University of Rome Tor Vergata, and subsequently moved to Stanford for postdoctoral training. Dr. Gherardini has developed computational tools for the analysis of cytometry data and a technology to measure gene expression in single cells using mass cytometry. Most recently, Dr. Gherardini was Director of Informatics at the Parker Institute for Cancer Immunotherapy. While at the Parker Institute, Dr. Gherardini designed the CANDEL platform for the integration of clinical and molecular data from patient samples and led a team of scientists to analyze deep immune profiling data from clinical trials in immuno-oncology.Message Presenter
Who Should Attend?
This webinar will appeal to:
- Chief Medical Officer
- R&D Manager, Director
- QC & Process Development Manager
- Principal Scientist
- Clinical Scientists
- Research Scientist/Associate
What You Will Learn
Join this webinar to learn about:
- Extensive end-to-end analysis features and unmatched performance of the cloud-based cytometry analysis software
- Rigorous validation and comprehensive 21 CFR part 11-compliance features which are an excellent fit for regulated environments
- Analyzing longitudinal clinical studies with metadata-driven visualizations
- The ease of reproducibly analyzing datasets containing thousands of samples with speed and rich API
Leading provider of specialized precision medicine laboratory services to the biopharmaceutical industry. Leveraging its integrated analytical platforms in immunology, histopathology, proteomics and genomics, as well as related specimen collection and logistics services, CellCarta supports the entire drug development cycle, from discovery to late-stage clinical trials.
The company operates globally with 10 facilities located in Canada, USA, Belgium, Australia, and China.
For more information on how CellCarta can partner with you, please contact us: www.cellcarta.com