Comprehensive and Routine Characterization of Proteins and Peptides by LC/MS and LC/MSE

The company has had abstracts accepted for three oral presentations and five posters.

In this episode, we explore BIOVECTRA’s capabilities in antibody-drug conjugate (ADC) manufacturing, from complex conjugation chemistry to synthesis of highly potent payloads. We’ll also showcase how BIOVECTRA’s extensive experience in complex chemistries and specialized small molecule manufacturing gives them a unique perspective, strengthening their approach to ADC production and ensuring clients receive custom solutions across all project stages.

Dr. Vinay Prasad, MD, MPH, a hematologist-oncologist, has been chosen to lead the Center for Biologics Evaluation and Research at FDA.

Metabolic Flux Analysis (MFA) is a powerful technique used to characterize metabolic phenotype driving to improved productivity in biomanufacturing. MFA is most powerful when absolute concentrations of the metabolic intermediates are measured, but doing so in practice is often impractical due to inherent limitations of conventional absolute quantitation by mass spectral analysis. Recently, advances in artificial intelligence (AI) have been applied to solving the problem of broad, untargeted, absolute quantitation in liquid chromatography-mass spectrometry (LC-MS). These new approaches extend readily to the determination of absolute concentrations of stable isotopically-labeled metabolic intermediates, offering a new tool for MFA. Dr Sam Yenne from Metalytics Inc., a company that specializes in the science of metabolic flux, has recently assessed and adopted Pyxis, a new tool for absolute quantitation of raw LC-MS data. Dr Yenne describes MFA, its utility in biopharmaceutical development, associated challenges and how Pyxis impacts those challenges.

Although automation is increasingly adopted in biomanufacturing, challenges remain in implementing it at the cell harvesting step.

Incorporating sustainable practices into process designs as early as possible ensures optimal performance.