Trace Element Prediction - Data-Driven Understanding and Control of Impurities in Cell Culture Media
Webinar
In this webinar, you will learn:
- How trace element (TE) impurities in cell culture media (CCM) raw materials impact cell performance and product quality
- How computational analysis of a decade-spanning database of raw material TE impurities enables prediction of TE concentrations and variability in CCM powder identifying high-risk materials in your formulation
- How data-driven TE specification setting and risk mitigation strategies, such as usage of low-impurity raw material, can improve batch-to-batch consistency
Speakers
Kevin Kent
Merck
Senior Data Scientist
Kevin is a Senior Data Scientist working on predicting impurity levels in cell culture media working from raw material and media database data. Kevin joined our company as a Data Scientist in 2025 and has a background in applying and deploying models to predict outcomes of bioprocess changes on yields and critical quality attributes.
Corinna Merkel
Merck
Senior Scientist in Cell Culture Media Production
Corinna is a Senior Scientist specializing in the optimization of cell culture media (CCM) design and manufacture. She joined the CCM business in 2016 and has since built deep expertise in guiding customer formulation requests toward robust, optimized CCM powders. She is one of the main contributors to the trace element prediction tool for CCM and is actively driving the implementation of low-impurity iron salts as a strategy to reduce batch-to-batch variability and improve media consistency.
Monoclonal antibody manufacturing
- Gene therapy manufacturing
期间:1h
语言:English
场次 1:往期 July 23, 2026