Optimization of a Saccharomyces cerevisiae fermentation process for production of a therapeutic recombinant protein using a multivariate bayesian approach

Abstract

Various approaches have been applied to optimize biological product fermentation processes and define design space. In this article, we present a stepwise approach to optimize a Saccharomyces cerevisiae fermentation process through risk assessment analysis, statistical design of experiments (DoE), and multivariate Bayesian predictive approach. The critical process parameters (CPPs) were first identified through a risk assessment. The response surface for each attribute was modeled using the results from the DoE study with consideration given to interactions between CPPs. A multivariate Bayesian predictive approach was then used to identify the region of process operating conditions where all attributes met their specifications simultaneously. The model prediction was verified by twelve consistency runs where all batches achieved broth titer more than 1.53 g/L of broth and quality attributes within the expected ranges. The calculated probability was used to define the reliable operating region. To our knowledge, this is the first case study to implement the multivariate Bayesian predictive approach to the process optimization for the industrial application and its corresponding verification at two different production scales. This approach can be extended to other fermentation process optimizations and reliable operating region quantitation.

Exometabolome analysis reveals hypoxia at the up-scaling of a Saccharomyces cerevisiae high-cell density fed-batch biopharmaceutical process

“…In previous work, we reported the optimization of a S. cerevisiae high-cell density fed-batch process using a Bayesian approach [17]. The set points for critical process parameters (CPPs), temperature, pH and dissolved oxygen (DO), were selected based on the high probability region calculated to meet the acceptance criteria of relevant attributes for process performance and product quality.…”

“…The product accumulation profiles were also consistent with a sustained increase of product concentration (measured as broth titer) up to the maximum of approximately 1.8 g/L by the EOR (Figure  1C). The quality attributes were also highly comparable between the batches (see Table four in [17]). The results indicated that the process had good controllability for each of the CPPs, and a consistent performance, and hence was ready for scale-up.…”

“…Interestingly, the product accumulation profiles (broth titer) (Figure  4E) as well as other qualities, purity by reverse phase-HPLC (RP-HPLC), purity by capillary iso-electric focusing (cIEF), protease activity, and product-related 6AA-impurity level by ELISA assay, (data not shown) were also comparable. The acceptance criteria for broth titer, and the product quality attributes, such as purity by RP-HPLC and cIEF, protease activity, and the 6AA-impurity, were established and the related assay descriptions are detailed in our previous work [17]. The biomass concentration profiles measured by dry cell weight (DCW) were also comparable between two scales (Figure  4F), indicating the total number of cells per unit volume were comparable even though the WCWs were slightly different (Figure  5A).…”

“…However, these adaptive mechanisms can have a detrimental effect on the bioprocess related to the control and product quantity/quality in the industrial scale. In previous work we optimized the S. cerevisiae fermentation process at the small scale (10 L), using a multivariate Bayesian approach [17]. As a result, a robust and reproducible process at the 10 L scale bioreactor was established.…”

“…The fermentation process to produce a therapeutic recombinant protein, Pr-1, at the small scale (10 L) was described previously [17]. Briefly, Pr-1 production is conditionally induced in the host strain by glucose limitation that elicits product secretion into the medium.…”