White Paper on Continuous Bioprocessing May 20-21 2014 Continuous Manufacturing Symposium.

There is a growing interest in realizing the benefits of continuous processing in biologics manufacturing, which is reflected by the significant number of industrial and academic researchers who are actively involved in the development of continuous bioprocessing systems. These efforts are further encouraged by guidance expressed in recent US FDA conference presentations. The advantages of continuous manufacturing include sustained operation with consistent product quality, reduced equipment size, high-volumetric productivity, streamlined process flow, low-process cycle times, and reduced capital and operating cost. This technology, however, poses challenges, which need to be addressed before routine implementation is considered. This paper, which is based on the available literature and input from a large number of reviewers, is intended to provide a consensus of the opportunities, technical needs, and strategic directions for continuous bioprocessing. The discussion is supported by several examples illustrating various architectures of continuous bioprocessing systems. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

White paper on continuous bioprocessing. May 20-21, 2014 Continuous Manufacturing Symposium.

There is a growing interest in realizing the benefits of continuous processing in biologics manufacturing, which is reflected by the significant number of industrial and academic researchers who are actively involved in the development of continuous bioprocessing systems. These efforts are further encouraged by guidance expressed in recent US FDA conference presentations. The advantages of continuous manufacturing include sustained operation with consistent product quality, reduced equipment size, high-volumetric productivity, streamlined process flow, low-process cycle times, and reduced capital and operating cost. This technology, however, poses challenges, which need to be addressed before routine implementation is considered. This paper, which is based on the available literature and input from a large number of reviewers, is intended to provide a consensus of the opportunities, technical needs, and strategic directions for continuous bioprocessing. The discussion is supported by several examples illustrating various architectures of continuous bioprocessing systems.

Metabolic flux estimation in mammalian cell cultures.

Metabolic flux analysis with its ability to quantify cellular metabolism is an attractive tool for accelerating cell line selection, medium optimization, and other bioprocess development activities. In the stoichiometric flux estimation approach, unknown fluxes are determined using intracellular metabolite mass balance expressions and measured extracellular rates. The simplicity of the stoichiometric approach extends its application to most cell culture systems, and the steps involved in metabolic flux estimation by the stoichiometric method are presented in detail in this chapter. Specifically, overdetermined systems are analyzed since the extra measurements can be used to check for gross measurement errors and system consistency. Cell-specific rates comprise the input data for flux estimation, and the logistic modeling approach is described for robust-specific rate estimation in batch and fed-batch systems. A simplified network of mammalian cell metabolism is used to illustrate the flux estimation procedure, and the steps leading up the consistency index determination are presented. If gross measurement errors are detected, a technique for determining the source of gross measurement error is also described. A computer program that performs most of the calculation described in this chapter is presented, and references to flux estimation software are provided. The procedure presented in this chapter should enable rapid metabolic flux estimation in any mammalian cell bioreaction network by the stoichiometric approach.

Error propagation from prime variables into specific rates and metabolic fluxes for mammalian cells in perfusion culture.

Error propagation from prime variables into specific rates and metabolic fluxes was quantified for high-concentration CHO cell perfusion cultivation. Prime variable errors were first determined from repeated measurements and ranged from 4.8 to 12.2%. Errors in nutrient uptake and metabolite/product formation rates for 5-15% error in prime variables ranged from 8-22%. The specific growth rate, however, was characterized by higher uncertainty as 15% errors in the bioreactor and harvest cell concentration resulted in 37.8% error. Metabolic fluxes were estimated for 12 experimental conditions, each of 10 day duration, during 120-day perfusion cultivation and were used to determine error propagation from specific rates into metabolic fluxes. Errors of the greater metabolic fluxes (those related to glycolysis, lactate production, TCA cycle and oxidative phosphorylation) were similar in magnitude to those of the related greater specific rates (glucose, lactate, oxygen and CO(2) rates) and were insensitive to errors of the lesser specific rates (amino acid catabolism and biosynthesis rates). Errors of the lesser metabolic fluxes (those related to amino acid metabolism), however, were extremely sensitive to errors of the greater specific rates to the extent that they were no longer representative of cellular metabolism and were much less affected by errors in the lesser specific rates. We show that the relationship between specific rate and metabolic flux error could be accurately described by normalized sensitivity coefficients, which were readily calculated once metabolic fluxes were estimated. Their ease of calculation, along with their ability to accurately describe the specific rate-metabolic flux error relationship, makes them a necessary component of metabolic flux analysis.

Decreased pCO(2) accumulation by eliminating bicarbonate addition to high cell-density cultures.

High-density perfusion cultivation of mammalian cells can result in elevated bioreactor CO(2) partial pressure (pCO(2)), a condition that can negatively influence growth, metabolism, productivity, and protein glycosylation. For BHK cells in a perfusion culture at 20 x 10(6) cells/mL, the bioreactor pCO(2) exceeded 225 mm Hg with approximate contributions of 25% from cellular respiration, 35% from medium NaHCO(3), and 40% from NaHCO(3) added for pH control. Recognizing the limitations to the practicality of gas sparging for CO(2) removal in perfusion systems, a strategy based on CO(2) reduction at the source was investigated. The NaHCO(3) in the medium was replaced with a MOPS-Histidine buffer, while Na(2)CO(3) replaced NaHCO(3) for pH control. These changes resulted in 63-70% pCO(2) reductions in multiple 15 L perfusion bioreactors, and were reproducible at the manufacturing-scale. Bioreactor pCO(2) values after these modifications were in the 68-85 mm Hg range, pCO(2) reductions consistent with those theoretically expected. Low bioreactor pCO(2) was accompanied by both 68-123% increased growth rates and 58-92% increased specific productivity. Bioreactor pCO(2) reduction and the resulting positive implications for cell growth and productivity were brought about by process changes that were readily implemented and robust. This philosophy of pCO(2) reduction at the source through medium and base modification should be readily applicable to large-scale fed-batch cultivation of mammalian cells.

Logistic equations effectively model Mammalian cell batch and fed-batch kinetics by logically constraining the fit.

A four-parameter logistic equation was used to fit batch and fed-batch time profiles of viable cell density in order to estimate net growth rates from the inoculation through the cell death phase. Reduced three-parameter forms were used for nutrient uptake and metabolite/product formation rate calculations. These logistic equations constrained the fits to expected general concentration trends, either increasing followed by decreasing (four-parameter) or monotonic (three-parameter). The applicability of this approach was first verified for Chinese hamster ovary (CHO) cells cultivated in 15-L batch bioreactors. Cell density, metabolite, and nutrient concentrations were monitored over time and used to estimate the logistic parameters by nonlinear least squares. The logistic models fit the experimental data well, supporting the validity of this approach. Further evidence to this effect was obtained by applying the technique to three previously published batch studies for baby hamster kidney (BHK) and hybridoma cells in bioreactors ranging from 100 mL to 300 L. In 27 of the 30 batch data sets examined, the logistic models provided a statistically superior description of the experimental data than polynomial fitting. Two fed-batch experiments with hybridoma and CHO cells in benchtop bioreactors were also examined, and the logistic fits provided good representations of the experimental data in all 25 data sets. From a computational standpoint, this approach was simpler than classical approaches involving Monod-type kinetics. Since the logistic equations were analytically differentiable, specific rates could be readily estimated. Overall, the advantages of the logistic modeling approach should make it an attractive option for effectively estimating specific rates from batch and fed-batch cultures.

Experimental and theoretical analysis of tubular membrane aeration for Mammalian cell bioreactors.

A combination of experimental and theoretical approaches was used to characterize the dynamics of oxygen transfer in a membrane-aerated bioreactor. Pressure profiles along the length of the membrane at varying entrance and exit pressures were determined by actual experimental measurements, unlike most previous studies that have relied solely on theoretical descriptions of the pressure profile in the tubing. The mass transfer coefficient, k(L)a, was also determined under these conditions and was found to be essentially independent of tubing exit pressure. Measurement of the tubing pressure profile coupled with estimation of k(L)a allowed for computation of the oxygen transfer rate (OTR) along the length of the tubing. A mathematical model that incorporated friction pressure loss and losses due to tubing bending was developed to describe the pressure and hence OTR characteristics of membrane-aerated systems. The applicability of the model was verified by testing it on experimentally measured pressure data, and in all cases the model accurately described experimental data. When tubing properties are known, the mathematical model presented in this study allows for a priori estimation of OTR profiles along the length of the tubing. This information is vital for optimal design and scale-up of membrane-aerated bioreactors for mammalian cell culture.