Consistency, consistency - Automated Sample Prep for Translational Proteomics
sponsored by Thermo Fisher Scientific
March 17, 2020
9am PDT, 12pm EDT
High-throughput LC-MS workflows are essential in translational and clinical research proteomics. While LC-MS methods have been sufficiently standardized today in terms of throughput, depth and coverage, sample preparation is still somewhat manual involving multiple steps to extract, purify, and digest proteins with clean-up before LC-MS analysis.
This bottleneck can be resolved with automation in combination with verified kits that eliminate the risk of error and variability, while enabling longitudinal standardization irrespective of the number of samples.
Collectively, automated Thermo Scientific™ EasyPep 96™ MS Sample Prep Kit provides a generic, scalable, and cost-effective pipeline for routine and standardized proteomic sample processing, enabling reproducible proteomics in a broad range of clinical research and non-clinical applications.
In this webinar we will describe (1) a consistent, reproducible, and high throughput sample preparation methodology for omics analysis of clinical research samples and (2) the robustness and speed of clinical research sample processing on an automated platform with proven chemistry.
Combined, these advances in sample processing, and LC-MS workflows make it possible to routinely analyze and quantify hundreds of samples, transforming translational clinical research and the understanding of human diseases to a new level.
Learning Objectives
- Implementation of a high throughput sample preparation workflow that is consistent and reproducible.
- How to automate and increase the speed of clinical research sample processing with proven chemistry and sample clean-up for LC-MS.
- Increase the productivity of sample preparation using a flexible and automated platform.
Who should attend
- Lab Managers in translational and medical research centers/institutes.
- CRO managers that offer translational research assays.
- Researchers that work with samples from large human cohorts.
- Biopharma/Biotech R&D managers with translational research projects.