Predicting mab product yields from cultivation media components, using near‐infrared and 2D‐fluorescence spectroscopies

Abstract

The yield of monoclonal antibody (Mab) production processes depends on media formulation, inocula quality, and process conditions. As in industrial processes tight cultivation conditions are used, and inocula quality and viable cell densities are controlled to reasonable levels, media formulation and raw materials lot-to-lot variability in quality will have, in those circumstances, the highest impact on process performance. In the particular Mab process studied, two different raw materials were used: a complex carbon and nitrogen source made of specific peptones and defined chemical media containing multiple components. Using different spectroscopy techniques for each of the raw material types, it was concluded that for the complex peptone-based ingredient, near-infrared (NIR) spectroscopy was more capable of capturing lot-to-lot variability. For the chemically defined media containing fluorophores, two-dimensional (2D)-fluorescence spectroscopy was more capable of capturing lot-to-lot variability. Because in Mab cultivation processes both types of raw materials are used, combining the NIR and 2D-fluorescence spectra for each of the media components enabled predictive models for yield to be developed that out-performed any other model involving either one raw material alone, or only one type of spectroscopic tool for both raw materials. For each particular raw material, the capability of each spectroscopy to detect lot-to-lot differences was demonstrated after spectra preprocessing and specific wavelength regions selection. The work described and the findings reported here open up several possibilities that could be used to feed-forward control the process. These include, for example, enabling specific actions to be taken regarding media formulation with particular lots, and all types of predictive control actions aimed at increasing batch-to-batch yield and product quality consistency at harvest.