Assay Development for translational and research applications

Robustness, reproducibility, and scalability are becoming increasingly important as proteomics workflows move closer to clinical and diagnostic applications.

In this webinar, we will explore how the Evosep Eno supports the development of robust diagnostic assays through standardized, high-throughput LC–MS workflows. Join us to learn how reproducible performance, streamlined operation, and scalable proteomics methods can help accelerate the transition from discovery research to real-world applications.

Robust Data from Evosep Eno coupled to Exploris 480 for the Development of Diagnostic Assays

Models derived from machine learning approaches possess enormous diagnostic potential. At OXcan we create reliable machine learning models using training data sets generated from LC-MS data. A good model is accurate, reliable, and resistant to overfitting. In order to achieve this performance, the clinical and control data must have enough features and be sufficiently robust to allow the model to generate diagnostic features with a high degree of confidence.

Accepting that there is a pressing need to create reliable proteomic data, to facilitate the training of machine learning models, we will discuss our workflow for generating robust data from digested plasma samples. The workflow leverages the performance capabilities of our Evosep Eno LC system coupled to a Thermo Exploris MS. This LC-MS platform gives us reproducible data, with the throughput required for the development of our machine learning derived diagnostic assays.

Speaker: Giles Drinkwater (Researcher at OXcan Analytics)