This webinar will be hosted live and available on-demand
Thursday, October 6, 2022
11:00 AM - 12:00 PM Eastern Time
The reliability and reproducibility of metabolomics data depends on analytical quality. However, even the highest analytical quality obtained using the most sophisticated instruments cannot substitute for poor sample quality. For example, inaccuracies and errors during sample collection from nonclinical settings, including timing and temperature variations prior to processing and freezing, negatively affect clinical study outcomes. As a result, controlling and standardizing pre-analytical factors, as well as optimizing analytical performance are the key considerations that determine the success of metabolomics projects.
In this Technique Talk, Shama Naz will reveal how to optimize experimental design and sample processing to improve the reliability and reproducibility of metabolomics data.
Learning Objectives
- Introduction to metabolomics
- Pre-analytical factors to consider for a metabolomics project
- Choosing an appropriate analytical tool
Shama Naz, PhD
Manager
Metabolomics Core Facility
University of Ottawa
