Case Study: A Novel Bacterial Contamination in Cell Culture Production--Leptospira licerasiae.

Leptospira licerasiae, a novel bacterial contaminant found in Genentech cell culture manufacturing operations, poses a challenge to current microbial control strategies in upstream cell culture processes, as this microorganism is fully capable of passing through 0.1 µm sterilizing-grade filtration and is not detectable by standard microbiological methods described in major pharmaceutical compendia for microbial screening and quantification required for release of raw materials, in-process intermediates, and finished products in biopharmaceutical production. The root cause investigation was greatly aided by the genetic identification of the contaminant and subsequent confirmation by cultural method and real-time polymerase chain reaction assay from the affected product batches. The purpose of this case study is to share knowledge on the novel contaminant, L. licerasiae, and potential routes of contamination in the cell culture manufacturing environment from a series of investigations involving root cause analysis, impact assessments, risk assessment, and global corrective and preventative action, as well as to provide guidance on the detection and prevention of Leptospira contamination with the intent to aid the industry to continually improve microbial control strategies for the benefit of patients. LAY ABSTRACT: Leptospira licerasiae, a novel bacterial contaminant found in cell culture manufacturing operations, poses a challenge to current microbial control strategies in upstream cell culture processes because this microorganism is capable of passing through 0.1 µm sterilizing-grade membrane filters and is not detectable by standard microbiological methods used in biopharmaceutical production. The root cause investigation was greatly aided by the genetic identification of the contaminant and subsequent confirmation by cultural method and real-time polymerase chain reaction assay from the affected product batches. The purpose of this case study is to share knowledge on the novel contaminant, L. licerasiae, and potential routes of contamination in the cell culture manufacturing environment from a series of investigations to provide the industry with guidance on the detection and prevention of Leptospira contamination.

Application of dynamic flux balance analysis to an industrial Escherichia coli fermentation.

We have developed a reactor-scale model of Escherichia coli metabolism and growth in a 1000 L process for the production of a recombinant therapeutic protein. The model consists of two distinct parts: (1) a dynamic, process specific portion that describes the time evolution of 37 process variables of relevance and (2) a flux balance based, 123-reaction metabolic model of E. coli metabolism. This model combines several previously reported modeling approaches including a growth rate-dependent biomass composition, maximum growth rate objective function, and dynamic flux balancing. In addition, we introduce concentration-dependent boundary conditions of transport fluxes, dynamic maintenance demands, and a state-dependent cellular objective. This formulation was able to describe specific runs with high-fidelity over process conditions including rich media, simultaneous acetate and glucose consumption, glucose minimal media, and phosphate depleted media. Furthermore, the model accurately describes the effect of process perturbations--such as glucose overbatching and insufficient aeration--on growth, metabolism, and titer.

Use of process data to assess chromatographic performance in production-scale protein purification columns.

Transition analysis was performed on production-scale chromatography data in order to monitor column performance. Analysis of over 300 transitions from several different chromatography operations demonstrated the utility of the techniques presented. Several of the transitions analyzed occurred on columns with known integrity breaches. The techniques proved sensitive for detection of these breaches. Seven transition calculations are presented, which were combined to produce a single overall integrity value for each column. In addition, principal components analysis (PCA) was used to detect shifts in the transition pattern, including those attributed to integrity breaches. Besides detection of integrity breaches, transition analysis proved useful in monitoring column efficiency over multiple column uses.