Accumulation of lactate in mammalian cell culture often negatively impacts culture performance, impeding production of therapeutic proteins. Many efforts have been made to limit the accumulation of lactate in cell culture. Here, we describe a closed loop control scheme based on online spectroscopic measurements of glucose and lactate concentrations. A Raman spectroscopy probe was used to monitor a fed-batch mammalian cell culture and predict glucose and lactate concentrations via multivariate calibration using partial least squares regression (PLS). The PLS models had a root mean squared error of prediction (RMSEP) of 0.27 g/L for glucose and 0.20 g/L for lactate. All glucose feeding was controlled by the Raman PLS model predictions. Glucose was automatically fed when lactate levels were beneath a setpoint (either 4.0 or 2.5 g/L) and glucose was below its own setpoint (0.5 g/L). This control scheme was successful in maintaining lactate levels at an arbitrary setpoint throughout the culture, as compared to the eventual accumulate of lactate to 8.0 g/L in the historical process. Automated control of lactate by restricted glucose feeding led to improvements in culture duration, viability, productivity, and robustness. Culture duration was extended from 11 to 13 days, and harvest titer increased 85% over the historical process. Biotechnol. Bioeng. 2016;113: 2416-2424. © 2016 Wiley Periodicals, Inc.

It is a common practice in biotherapeutic manufacturing to define a fixed-volume feed strategy for nutrient feeds, based on historical cell demand. However, once the feed volumes are defined, they are inflexible to batch-to-batch variations in cell growth and physiology and can lead to inconsistent productivity and product quality. In an effort to control critical quality attributes and to apply process analytical technology (PAT), a fully automated cell culture feedback control system has been explored in three different applications. The first study illustrates that frequent monitoring and automatically controlling the complex feed based on a surrogate (glutamate) level improved protein production. More importantly, the resulting feed strategy was translated into a manufacturing-friendly manual feed strategy without impact on product quality. The second study demonstrates the improved process robustness of an automated feed strategy based on online bio-capacitance measurements for cell growth. In the third study, glucose and lactate concentrations were measured online and were used to automatically control the glucose feed, which in turn changed lactate metabolism. These studies suggest that the auto-feedback control system has the potential to significantly increase productivity and improve robustness in manufacturing, with the goal of ensuring process performance and product quality consistency.

Dielectric spectroscopy (biocapacitance) is an up-and-coming technology for real time monitoring of biomass in cell culture processes and has opened the door for nextgeneration cell culture process control techniques such as automated on-demand nutrient feeding. In this case study we empirically demonstrate the lower limit of quantitation (LOQ), probe-to-probe consistency, and scalability of in situ biocapacitance probes using data generated from small-and large-scale Chinese hamster ovary (CHO) bioreactor cultures. The process understanding experiments culminated in the use of biocapacitance for process control in the current good manufacturing practices (GMP) manufacturing environment, first to automate the dilution of seed train cultures during scale-up stages and later as a method of predicting future glucose demand. The automated biomass-probe-based inoculation strategy yielded consistent results in six consecutive seed trains in the GMP manufacturing suite. In the process of improving our understanding of the technology we determined that biocapacitance could additionally be used as an indicator of a shift in the salt balance of a cell culture, and that collecting real time biomass data via biocapacitance has the potential to reduce the total timeline for feed strategy development by providing additional insights into culture performance which are not otherwise apparent using conventional optical cell counting methods.

The recent development of microfluidic "lab on a chip" devices requiring sample sizes <100 lL has given rise to the need to concentrate dilute samples and trap analytes, especially for surface-based detection techniques. We demonstrate a particle collection device capable of concentrating micron-sized particles in a predetermined area by combining AC electroosmosis (ACEO) and dielectrophoresis (DEP). The planar asymmetric electrode pattern uses ACEO pumping to induce equal, quadrilateral flow directed towards a stagnant region in the center of the device. A number of system parameters affecting particle collection efficiency were investigated including electrode and gap width, chamber height, applied potential and frequency, and number of repeating electrode pairs and electrode geometry. The robustness of the on-chip collection design was evaluated against varying electrolyte concentrations, particle types, and particle sizes. These devices are amenable to integration with a variety of detection techniques such as optical evanescent waveguide sensing.

Elemental metals are critical raw material attributes which can impact cell culture performance and associated therapeutic protein product quality profiles. Metals such as copper and manganese act as cofactors and reagents for numerous metabolic pathways which govern cell growth, protein expression, and glycosylation, thus mandating elemental monitoring. The growing complexity of modern cell culture media formulations adds additional opportunities for elemental variance and its associated impact risks. This article describes an analytical technique applying inductively coupled plasma mass spectrometry to characterize a list of common raw materials and media powders used in mammalian cell culture and therapeutic protein production. We aim to describe a method qualification approach suitable for biopharmaceutical raw materials. Furthermore, we present detailed profiles of many common raw materials and discuss trends in raw material subtypes. Finally, a case study demonstrating the impact of an unexpected source of raw material variation is presented along with recommendations for raw material elemental risk profiling and control.