Development of a stable antibody production system utilizing an Hspa5 promoter in CHO cells

Comprehensive modeling of cell culture profile using Raman spectroscopy and machine learning

Chinese hamster ovary (CHO) cells are widely utilized in the production of antibody drugs. To ensure the production of large quantities of antibodies that meet the required specifications, it is crucial to monitor and control the levels of metabolites comprehensively during CHO cell culture. In recent years, continuous analysis methods employing on-line/in-line techniques using Raman spectroscopy have attracted attention. While these analytical methods can nondestructively monitor culture data, constructing a highly accurate measurement model for numerous components is time-consuming, making it challenging to implement in the rapid research and development of pharmaceutical manufacturing processes. In this study, we developed a comprehensive, simple, and automated method for constructing a Raman model of various components measured by LC-MS and other techniques using machine learning with Python. Preprocessing and spectral-range optimization of data for model construction (partial least square (PLS) regression) were automated and accelerated using Bayes optimization. Subsequently, models were constructed for each component using various model construction techniques, including linear regression, ridge regression, XGBoost, and neural network. This enabled the model accuracy to be improved compared with PLS regression. This automated approach allows continuous monitoring of various parameters for over 100 components, facilitating process optimization and process monitoring of CHO cells.

High-Level Production of scFv-Fc Antibody Using an Artificial Promoter System with Transcriptional Positive Feedback Loop of Transactivator in CHO Cells

With the increasing demand for therapeutic antibodies, CHO cells have become the de facto standard as producer host cells for biopharmaceutical production. High production yields are required for antibody production, and developing a high-titer production system is increasingly crucial. This study was established to develop a high-production system using a synthetic biology approach by designing a gene expression system based on an artificial transcription factor that can strongly induce the high expression of target genes in CHO cells. To demonstrate the functionality of this artificial gene expression system and its ability to induce the high expression of target genes in CHO cells, a model antibody (scFv-Fc) was produced using this system. Excellent results were obtained with the plate scale, and when attempting continuous production in semi-continuous cultures using bioreactor tubes with high-cell-density suspension culture using a serum-free medium, high-titer antibody production at the gram-per-liter level was achieved. Shifting the culture temperature to a low temperature of 33 °C achieved scFv-Fc concentrations of up to 5.5 g/L with a specific production rate of 262 pg/(cell∙day). This artificial gene expression system should be a powerful tool for CHO cell engineering aimed at constructing high-yield production systems.