CHO Cell Culture Research Articles

Genome-Scale Modeling of CHO Cells Unravel the Critical Role of Asparagine in Cell Culture Feed Media.

Amino acids, including asparagine, aspartate, glutamine, and glutamate, play important roles in purine and pyrimidine biosynthesis as well as serve as anaplerotic sources fueling the tricarboxylic acid (TCA) cycle for mitochondrial energy generation. Despite extensive studies on glutamine and glutamate in CHO cell cultures, the roles of asparagine and aspartate, especially in feed media, remain underexplored. In this study, we utilized a CHO genome scale model to first deeply characterize the intracellular metabolic states of CHO cells cultured in different combinations of basal and feed media to understand the traits of asparagine/aspartate-dependent and glutamate-dependent feeds. Subsequently, we identified the critical role of asparagine and aspartate in the feed media as anaplerotic sources and conducted in silico simulations to ascertain their optimal ratios to improve cell culture performance. Finally, based on the model simulations, we reformulated the feed media by tailoring the concentrations of asparagine and aspartate. Our experimental data reveal a CHO cell preference for asparagine compared with aspartate, and thus maintaining an optimal ratio of these amino acids is a key factor for achieving optimal CHO cell culture performance in biopharmaceutical production.

A user-friendly fluorescent biosensor for precise lactate detection and quantification in vitro.

As a critical metabolite, the standardization of lactate quantification is increasingly crucial. Therefore, we developed LaconicSF, a lactate-responsive biosensor exhibiting exceptional specificity in lactate detection. LaconicSF enables efficient lactate quantification in CHO cell culture medium and holds potential as a user-friendly detection tool for lactate quantification in vitro.

Improving Raman-Based Models for Real-Time Monitoring the CHO Cell Culture Process with Effective Variable Selection Strategies

Research has shown that Raman spectroscopy could be applied to monitor various components in mammalian cell culture in real time. In the process of application, it is necessary to ensure the performance of the Raman-based model. The variable selection strategy is an effective method that significantly influences the model performance and simplification. In this study, different variable selection strategies were evaluated, and the optimal variable selection strategy was determined for monitoring the CHO cell culture process. Firstly, a wide variety of spectral regions involving the Raman fingerprinting region and the C-H stretching region were investigated. Secondly, six different variable selection algorithms were meticulously assessed. Thirdly, the combination of different variable selection algorithms was used to improve model performance and simplify the model. Finally, the monitoring of cell culture processes was implemented. The findings underscored that commonly used spectral regions could improve the model performance but could not simplify the model well. Moving-window partial least square (MWPLS), genetic algorithm (GA), and random frog (RF) are more suitable for Raman modeling of the cell culture process, but they must be used after the spectral region selection. The combination of three variable selection algorithms (MWPLS-GA-RF) improved the model’s performance by 16–70% by selecting 30–60 variables, effectively simplifying the model. For glucose, lactate, viable cell density, and ammonium ion, real-time monitoring was performed well. This study will be helpful for researchers to select suitable variable selection strategies for building models for the real-time monitoring of cell culture.

GlyCompute: towards the automated analysis of protein N-linked glycosylation kinetics via an open-source computational framework.

Understanding the complex biosynthetic pathways of glycosylation is crucial for the expanding field of glycosciences. Computer-aided glycosylation analysis has greatly benefited in recent years from the development of tools found in web-based portals and open-source libraries. However, the in silico analysis of cellular glycosylation kinetics is underrepresented in current glycoscience-related tools and databases. This could be partly attributed to the limited accessibility of kinetic models developed using proprietary software and the difficulty in reliably parameterising such models. This work aims to address these challenges by proposing GlyCompute, an open-source framework demonstrating a novel, streamlined approach for the assembly, simulation, and parameterisation of kinetic models of protein N-linked glycosylation. Specifically, given one or more sets of experimentally observed N-glycan structures and their relative abundances, minimum representations of a glycosylation reaction network are generated. The topology of the resulting networks is then used to automatically assemble the material balances and kinetic mechanisms underpinning the mathematical model. To match the experimentally observed relative abundances, a sequential parameter estimation strategy using Bayesian inference is proposed, with stages determined automatically based on the underlying network topology. The proposed framework was tested on a case study involving the simultaneous fitting of the kinetic model to two protein N-linked glycoprofiles produced by the same CHO cell culture, showing good agreement with experimental observations. We envision that GlyCompute could help glycoscientists gain quantitative insights into the effect of enzyme kinetics and their perturbations on experimentally observed glycoprofiles in biomanufacturing and clinical settings.

Dialysis rolled scaffold bioreactor allows extended production of monoclonal antibody with reduced media use.

Rapidly expanding biopharmaceutical market demands more cost-effective platforms to produce protein therapeutics. To this end, novel approaches, such as perfusion culture or concentrated fed-batch, have been explored for higher yields and lower manufacturing costs. Although these new approaches produced promising results, but their wide-spread use in the industry is still limited. In this study, a dialysis rolled scaffold bioreactor was presented for long-term production of monoclonal antibodies with reduced media consumption. Media dialysis can selectively remove cellular bio-wastes without losing cells or produced recombinant proteins. The dialysis process was streamlined to significantly improve its efficiency. Then, extended culture of recombinant CHO cells for 41 days was successfully demonstrated with consistent production rate and minimal media consumption. The unique configuration of the developed bioreactor allows efficient dialysis for media management, as well as rapid media exchange to harvest produced recombinant proteins before they degrade. Taken together, it was envisioned that the developed bioreactor will enable cost-effective and long-term large-scale culture of various cells for biopharmaceutical production.

Ala-Cys-Cys-Ala dipeptide dimer alleviates problematic cysteine and cystine levels in media formulations and enhances CHO cell growth and metabolism

Cysteine and cystine are essential amino acids present in mammalian cell cultures. While contributing to biomass synthesis, recombinant protein production, and antioxidant defense mechanisms, cysteine poses a major challenge in media formulations owing to its poor stability and oxidation to cystine, a cysteine dimer. Due to its poor solubility, cystine can cause precipitation of feed media, formation of undesired products, and consequently, reduce cysteine bioavailability. In this study, a highly soluble cysteine containing dipeptide dimer, Ala-Cys-Cys-Ala (ACCA), was evaluated as a suitable alternative to cysteine and cystine in CHO cell cultures. Replacing cysteine and cystine in basal medium with ACCA did not sustain cell growth. However, addition of ACCA at 4 mM and 8 mM to basal medium containing cysteine and cystine boosted cell growth up to 15% and 27% in CHO-GS and CHO–K1 batch cell cultures respectively and led to a proportionate increase in IgG titer. 13C-Metabolic flux analysis revealed that supplementation of ACCA reduced glycolytic fluxes by 20% leading to more efficient glucose metabolism in CHO–K1 cells. In fed-batch cultures, ACCA was able to replace cysteine and cystine in feed medium. Furthermore, supplementation of ACCA at high concentrations in basal medium eliminated the need for any cysteine equivalents in feed medium and increased cell densities and viabilities in fed-batch cultures without any significant impact on IgG charge variants. Taken together, this study demonstrates the potential of ACCA to improve CHO cell growth, productivity, and metabolism while also facilitating the formulation of cysteine- and cystine-free feed media. Such alternatives to cysteine and cystine will pave the way for enhanced biomanufacturing by increasing cell densities in culture and extending the storage of highly concentrated feed media as part of achieving intensified bioproduction processes.

Sialyllactose supplementation enhances sialylation of Fc-fusion glycoprotein in recombinant Chinese hamster ovary cell culture

Sialylation during N-glycosylation plays an important role in the half-life of therapeutic glycoproteins in vivo and has sparked interest in the production of therapeutic proteins using recombinant Chinese hamster ovary (rCHO) cells. To improve the sialylation of therapeutic proteins, we examined the effect of sialyllactose supplementation on sialylation of Fc-fusion glycoproteins produced in rCHO cells. Two enzymatically-synthesized sialyllactoses, 3′-sialyllactose (3′-SL) and 6′-sialyllactose (6′-SL), were administered separately to two rCHO cell lines producing the same Fc-fusion glycoprotein derived from DUKX-B11 and DG44, respectively. Two sialyllactoses successfully increased sialylation of Fc-fusion glycoprotein in both cell lines, as evidenced by isoform distribution, sialylated N-glycan formation, and sialic acid content. Increased sialylation by adding sialyllactose was likely the result of increased amount of intracellular CMP-sialic acid (CMP-SA), the direct nucleotide sugar for sialylation. Furthermore, the degree of sialylation enhanced by sialyllactoses was slightly effective or nearly similar compared with the addition of N-acetylmannosamine (ManNAc), a representative nucleotide sugar precursor, to increase sialylation of glycoproteins. The effectiveness of sialyllactose was also confirmed using three commercially available CHO cell culture media. Taken together, these results suggest that enzymatically-synthesized sialyllactose represents a promising candidate for culture media supplementation to increase sialylation of glycoproteins in rCHO cell culture.

Biomass specific perfusion rate as a control lever for the continuous manufacturing of biosimilar monoclonal antibodies from CHO cell cultures.

Continuous manufacturing enables high volumetric productivities of biologics such as monoclonal antibodies. However, it is challenging to maintain both high viable cell densities and productivities at the same time for long culture durations. One of the key controls in a perfusion process is the perfusion rate which determines the nutrient availability and potentially controls the cell metabolism. Cell Specific Perfusion Rate (CSPR) is a feed rate proportional to the viable cell density while Biomass Specific Perfusion Rate (BSPR) is a feed rate proportional to the biomass (cell volume multiply bycell density). In this study, perfusion cultures were run at three BSPRs in the production phase. Low BSPR favored a growth arresting state that led to gradual increase in cell volume, which in turn led to an increase in net perfusion rate proportional to the increase in cell volume. Consequently, at low BSPR, while the cell viability and cell density decreased, high specific productivity of 55 pg per cell per day was achieved. In contrast, the specific productivity was lower in bioreactors operating at a high BSPR. The ability to modulate the cell metabolism by using BSPR was confirmed when the specific productivity increased after lowering the BSPR in one of the bioreactors that was initially operating at a high BSPR. This study demonstrated that BSPR significantly influenced cell growth, metabolism, and productivity in cultures with variable cell volumes.

Development of a biotechnology process for the production of a novel hyperglycosylated long-acting recombinant bovine follicle-stimulating hormone.

Follicle-stimulating hormone (FSH) is an important protein used for bovine ovarian hyperstimulation in multiple ovulation and embryo transfer technology (MOET). Several attempts to produce bovine FSH (bFSH) in recombinant systems have been reported, nonetheless, up to date, the most commonly used products are partially purified preparations derived from porcine or ovine (pFSH or oFSH) pituitaries. Here we describe the development of a biotechnology process to produce a novel, hyperglycosylated, long-acting recombinant bFSH (LA-rbFSH) by fusing copies of a highly O-glycosylated peptide. LA-rbFSH and a nonmodified version (rbFSH) were produced in suspension CHO cell cultures and purified by IMAC with high purity levels (>99%). LA-rbFSH presented a higher glycosylation degree and sialic acid content than rbFSH. It also demonstrated a notable improvement in pharmacokinetic properties after administration to rats, including a higher concentration in plasma and a significant (seven-fold) reduction in apparent clearance (CLapp). In addition, the in vivo specific bioactivity of LA-rbFSH in rats was 2.4-fold higher compared to rbFSH. These results postulate this new molecule as an attractive substitute for commercially available porcine pituitary-derived products.

Development and characterization of a novel variant of long-acting bovine follicle-stimulating hormone (brscFSH)

Assisted reproduction is a key aspect of modern animal breeding, providing valuable assistance in improving breeding programs. In this field, the administration of exogenous hormones, such as follicle-stimulating hormone (FSH), plays a crucial role in the induction of multiple ovulations. However, commercial FSH used in veterinary practice has been derived primarily from pituitary glands, obtained mostly from pigs for nearly four decades. Although these hormones have contributed significantly to the advancement of assisted reproductive techniques, they have certain limitations that warrant further improvements. These limitations include contamination with luteinizing hormone (LH), the potential risk of pathogen contamination, the potential to trigger an immune response in non-pig species, and the short half-life in circulation, requiring the implementation of complex 8-dose superovulation schedules. Our research team has developed and characterized a new variant of bovine follicle-stimulating hormone (bscrFSH) to address these limitations. The new hormone is produced recombinantly in CHO cell cultures, with a specific productivity of about 30 pg/cell/day. The bscrFSH can be purified to a high purity of 97 % using a single step of immobilized metal affinity chromatography (IMAC). N-glycan analysis of bscrFSH showed that approximately 74 % of the glycans corresponded to charged structures, including mono-, di-, tri-, and tetra-sialylated glycans. Superovulation trials conducted in cattle revealed that bscrFSH, administered at a total dose of about 0.5 μg per kg of body weight, using a decrescent schedule of 4 doses with 24-h intervals, resulted in an average yield of 8–12 transferable embryos per animal. Further research is required; however, the preliminary findings indicate that bscrFSH, currently packaged under the provisional brand name of Cebitropin B, holds potential as a commercial product for assisted reproduction in ruminants.

Use of spectroscopic process analytical technology for rapid quality evaluation during preparation of CHO cell culture media.

Media preparation parameters contribute significantly to media quality, cell culture performance, productivity, and product quality. Establishing proper media preparation procedures is critical for ensuring a robust CHO cell culture process. Process analytical technology (PAT) enables unique ways to quantify assessments and improve media quality. Here, cell culture media were prepared under a wide range of temperatures (40-80°C) and pH (7.6-10.0). Media quality profiles were compared using three real-time PATs: Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, and excitation-emission matrix (EEM) spectroscopy. FTIR and Raman spectroscopies identified shifts in media quality under high preparation temperature (80°C) and at differing preparation pH which negatively impacted monoclonal antibody (mAb) production. In fed-batch processes for production of three different mAbs, viable cell density (VCD) and cell viability were mostly unaffected under all media preparation temperatures, while titer and cell specific productivity of mAb decreased when cultured in basal and feed media prepared at 80°C. High feed preparation pH alone was tolerated but cell growth and productivity profiles deviated from the control condition. Further, charge variants (main, acidic, basic species) and glycosylation (G0F, afucosylation, and high mannose) were examined. Statistically significant differences were observed for one or more of these quality attributes with any shifts in media preparation. In this study, we demonstrated strong associations between media preparation conditions and cell growth, productivity, and product quality. The rapid evaluation of media by PAT implementation enabled more comprehensive understanding of different parameters on media quality and consequential effects on CHO cell culture.

Explainable AI for CHO cell culture media optimization and prediction of critical quality attribute

Cell culture media play a critical role in cell growth and propagation by providing a substrate; media components can also modulate the critical quality attributes (CQAs). However, the inherent complexity of the cell culture media makes unraveling the impact of the various media components on cell growth and CQAs non-trivial. In this study, we demonstrate an end-to-end machine learning framework for media component selection and prediction of CQAs. The preliminary dataset for feature selection was generated by performing CHO-GS (-/-) cell culture in media formulations with varying metal ion concentrations. Acidic and basic charge variant composition of the innovator product (24.97 ± 0.54% acidic and 11.41 ± 1.44% basic) was chosen as the target variable to evaluate the media formulations. Pearson’s correlation coefficient and random forest-based techniques were used for feature ranking and feature selection for the prediction of acidic and basic charge variants. Furthermore, a global interpretation analysis using SHapley Additive exPlanations was utilized to select optimal features by evaluating the contributions of each feature in the extracted vectors. Finally, the medium combinations were predicted by employing fifteen different regression models and utilizing a grid search and random search cross-validation for hyperparameter optimization. Experimental results demonstrate that Fe and Zn significantly impact the charge variant profile. This study aims to offer insights that are pertinent to both innovators seeking to establish a complete pipeline for media development and optimization and biosimilar-based manufacturers who strive to demonstrate the analytical and functional biosimilarity of their products to the innovator.Key points• Developed a framework for optimizing media components and prediction of CQA.• SHAP enhances global interpretability, aiding informed decision-making.• Fifteen regression models were employed to predict medium combinations.

Online monitoring of the respiration activity in 96-deep-well microtiter plate Chinese hamster ovary cultures streamlines kill curve experiments.

Cell line generation of mammalian cells is a time-consuming and labor-intensive process, especially because of challenges in clone selection after transfection. Antibiotics are common selection agents for mammalian cells due to their simplicity of use. However, the optimal antibiotic concentration must be determined with a kill curve experiment before clone selection starts. The traditional kill curve experiments are resource-intensive and time-consuming due to necessary sampling and offline analysis effort. This study, thus, explores the potential of online monitoring the oxygen transfer rate (OTR), as a non-invasive and efficient alternative for kill curve experiments. The OTR is monitored using the Transfer-rate Online Measurement (TOM) system and the micro(μ)-scale Transfer-rate Online Measurement (μTOM) device, which was used for mammalian cells first. It could be shown that the OTR curves for both devices align perfectly, affirming consistent cultivation conditions. The μTOM device proves effective in performing kill curve experiments in 96-deep-well plates without the need for sampling and offline analysis. The streamlined approach reduces medium consumption by 95%, offering a cost-effective and time-efficient solution for kill curve experiments. The study validates the generalizability of the method by applying it to two different CHO cell lines (CHO-K1 and sciCHO) with two antibiotics (puromycin and hygromycin B) each. In conclusion, the broad application of OTR online monitoring for CHO cell cultures in 96-deep-well plates is highlighted. The μTOM device proves as a valuable tool for high-throughput experiments, paving the way for diverse applications, such as media and clone screening, cytotoxicity tests, and scale-up experiments.

Metabolic engineering of Bcat1, Adh5 and Hahdb towards controlling metabolic inhibitors and improving performance in CHO cell-cultures

CHO cells are known to secrete growth inhibitory metabolites during growth and production phases, which hampers cellular performance and negatively impacts final productivity and product quality attributes. Previous studies have identified different metabolic by-products derived from CHO metabolism and demonstrated their negative impacts on growth and titer productivity. This work presents a control strategy that incorporated genetic engineering and inhibitory metabolites pathway analysis to regulate cellular metabolism. In this study, three different metabolic genes involving the metabolism of branched-chain amino acids (Adh5, Bcat1 and Hadhb) were cloned from CHO reversely synthesized cDNA to study for gene functionality towards regulating cellular metabolism. Identified metabolic genes were individually engineered into expression vector and transfected to cells at plasmid concentration of 40 µg/µL. For all engineered conditions, the peak VCD profile of cells on Day 4 realized a 18–20% increase with cumulative VCD profile realizing 16–19% increase in terms of total viable cells collected on harvest day. Increase in IgG1 titer production and also more complex glycosylation profiles formation were also observed from all engineered subclones. This study hereby successfully demonstrated rewiring cellular metabolism through up-regulation of key metabolic enzymes can effectively control the accumulation of process inhibitors which therefore allowed improvement desirable critical process attributes.

Development and validation of a hybrid model for prediction of viable cell density, titer and cumulative glucose consumption in a mammalian cell culture system

Among the many approaches to build predictive models for bioprocesses, hybrid models have gained increased attention due to their ability to combine data driven approaches with process knowledge. This study develops and compares hybrid models that predict the performance of a mammalian CHO cell culture producing a therapeutic product. Three machine learning algorithms, MLP, Random Forest and XGBoost regressors are compared to understand the effect of algorithm choice on the rates predicted and overall performance of the hybrid model. When combined in series with mechanistic equations, all three algorithms could predict next day Viable Cell Density, titer and the cumulative amount of glucose consumed with low error, although decision tree-based algorithm required less computational time for training. The models performed well using a dataset for a new product, without further model training. Retraining the model on a subset of data from the new product improved the prediction accuracy of VCD and titer. The potential for application and further model developments are also outlined.

Exploring metabolic responses and pathway changes in CHO-K1 cells under varied aeration conditions and copper supplementations using 1 H NMR-based metabolomics.

The optimization of bioprocess for CHO cell culture involves careful consideration of factors such as nutrient consumption, metabolic byproduct accumulation, cell growth, and monoclonal antibody (mAb) production. Valuable insights can be obtained by understanding cellular physiology to ensure robust and efficient bioprocess. This study aims to improve our understanding of the CHO-K1 cell metabolism using 1 H NMR-based metabolomics. Initially, the variations in culture performance and metabolic profiles under varied aeration conditions and copper supplementations were thoroughly examined. Furthermore, a comprehensive metabolic pathway analysis was performed to assess the impact of these conditions on the implicated pathways. The results revealed substantial alterations in the pyruvate metabolism, histidine metabolism, as well as phenylalanine, tyrosine and tryptophan biosynthesis, which were especially evident in cultures subjected to copper deficiency conditions. Conclusively, significant metabolites governing cell growth and mAb titer were identified through orthogonal partial least square-discriminant analysis (OPLS-DA). Metabolites, including glycerol, alanine, formate, glutamate, phenylalanine, and valine, exhibited strong associations with distinct cell growth phases. Additionally, glycerol, acetate, lactate, formate, glycine, histidine, and aspartate emerged as metabolites influencing cell productivity. This study demonstrates the potential of employing 1 H NMR-based metabolomics technology in bioprocess research. It provides valuable guidance for feed medium development, feeding strategy design, bioprocess parameter adjustments, and ultimately the enhancement of cell proliferation and mAb yield.

Elucidating lactate metabolism in industrial CHO cultures through the combined use of flux balance and principal component analyses

Overflow metabolism in the form of lactate accumulation in proliferating mammalian cell cultures results in significant process design challenges for industrial bioprocesses. While lactate metabolism in CHO cell cultures naturally switches from lactate production (LP) to lactate consumption (LC) both in batch and fed-batch cultures, neither the exact mechanism nor what triggers the metabolic switch are well understood. Herein, a computational methodology based on flux balance analysis to analyse experimental data from multiple industrial CHO cell lines in order to identify key differences between the two metabolic states is presented. Experimentally determined uptake and secretion rates from the LP and LC states of four industrial cell lines were used to constrain a CHO genome-scale model. Subsequently, a large number of sampled flux distributions were retrieved from the space of feasible solutions for each state (LP, LC) and cell line using an Artificial Centering Hit-and-Run algorithm. The sampled flux distributions were labelled and randomised before being analysed by principal component analysis (PCA). PCA was able to identify and completely separate samples from the two metabolic states. Based on a detailed analysis of PCA loadings a mechanism detailing the function and switch of lactate metabolism is proposed. Briefly, we hypothesize that (I) the production of lactate is linked to the regeneration of the NAD+ pool in the cytosol as a result of large passive glucose intake, (II) the switch in lactate metabolism is regulated by (i) the concentration difference between extracellular and intracellular lactate and (ii) the transmembrane proton gradient.

Erratum to: Utilization of Glucocorticoids as Additives for Enhanced Sialylation of Fc-fusion Protein in CHO Cell Cultures

Erratum to: Utilization of Glucocorticoids as Additives for Enhanced Sialylation of Fc-fusion Protein in CHO Cell Cultures

Rosmarinic acid enhances CHO cell productivity and proliferation through activation of the unfolded protein response and the mTOR pathway.

Rosmarinic acid (RA) has gained attraction in bioprocessing as a media supplement to improve cellular proliferation and protein production. Here, we observe up to a two-fold increase in antibody production with RA-supplementation, and a concentration-dependent effect of RA on cell proliferation for fed-batch Chinese hamster ovary (CHO) cell cultures. Contrary to previously reported antioxidant activity, RA increased the reactive oxygen species (ROS) levels, stimulated endoplasmic reticulum (ER) stress, activated the unfolded protein response (UPR), and elicited DNA damage. Despite such stressful events, RA appeared to maintained cell health via mammalian target of rapamycin (mTOR) pathway activation; both mTOR complex 1 (mTORC1) and mTOR complex 2(mTORC2) were stimulated in RA-supplemented cultures. By reversing such mTOR pathway activity through either chemical inhibitor addition or siRNA knockdown of genes regulating the mTORC1 and mTORC2 complexes, antibody production, UPR signaling, and stress-induced DNA damage were reduced. Further, the proliferative effect of RA appeared to be regulated selectively by mTORC2 activation and have reproduced this observation by using the mTORC2 stimulator SC-79. Analogously, knockdown of mTORC2 strongly reduced X-box binding protein 1 (XBP1) splicing, which would be expected to reduce antibody folding and secretion, sugging that reduced mTORC2 would correlate with reduced antibody levels. The crosstalk between mTOR activation and UPR upregulation may thus be related directly to the enhanced productivity. Our results show the importance of the mTOR and UPR pathways in increasing antibody productivity, and suggest that RA supplementation may obviate the need for labor-intensive genetic engineering by directly activating pathways favorable to cell culture performance.

A two-phase approach optimizing productivity for a mAb-producing CHO cell culture process using dynamic response surface methodology models

Fed-batch cell culture processes are common in the biomanufacturing industry due to their ease of development and simplicity of execution in the cGMP environment. One challenge of fed-batch operation is that the physiochemical conditions within the bioreactor do not remain constant throughout a batch but change over time as the viable cell density changes. It is well accepted that fed-batch cultures are multi-phasic, divided into “growth, stationary, and death phases”. Yet, using empirical modeling methods such as response surface models (RSMs) for optimization is still common. While RSMs can identify local performance maxima, they are limited by the time-invariant factors (input parameters) they use. These factors do not change throughout the run. Dynamic RSM (DRSM) models predict the time-dependent impact of the process inputs allowing for the identification of optimized process operations that change with time. Starting with the data sets generated via a traditional Design of Experiments (DoE) design, the DRSM model successfully optimized the peak cell count during the growth phase of culture and then identified a second set of process parameters that optimized productivity during the stationary phase. The resulting process achieved a harvest titer improvement of 28% relative to the base process condition.