Letha Chemmalil

and 17 more

The biopharmaceutical industry is transitioning from currently deployed batch-mode bioprocessing to a highly efficient and agile next generation bioprocessing with the adaptation of continuous bioprocessing, which reduces the capital investment and operational costs. Continuous bioprocessing, aligned with FDA’s quality-by-design (QbD) platform, is designed to develop robust processes to deliver safe and effective drugs. With the deployment of knowledge based operations, product quality can be built into the process to achieve desired critical quality attributes (CQAs) with reduced variability. To facilitate next generation continuous bio-processing, it is essential to embrace a fundamental shift-in-paradigm from “quality-by-testing” to “quality-by-design”, which requires the deployment of process analytical technologies (PAT). With the adaptation of PAT, a systematic approach of process and product understanding and timely process control are feasible. Deployment of PAT tools for real-time monitoring of CQAs and feedback control is critical for continuous bioprocessing. Given the current deficiency in PAT tools to support continuous bioprocessing, we have integrated Agilent 2D-LC with a post-flow-splitter in conjunction with the SegFlow automated sampler to the bioreactors. With this integrated system, we have established a platform for online measurements of titer and CQAs of monoclonal antibodies (mAbs) as well as amino acid concentrations of bioreactor cell culture.

Tingwei Ren

and 5 more

Disulfide bond reduction has been a challenging issue in antibody manufacturing, as it leads to reduced product purity, failed product specifications and more importantly, impacting drug safety and efficacy. Scientists across industry have been examining the root causes and developing mitigation strategies to address the challenge. In recent years, with the development of high-titer mammalian cell culture processes to meet the rapidly growing demand for antibody biopharmaceuticals, disulfide bond reduction has been observed more frequently. Thus, it is necessary to continue evolving the disulfide reduction mitigation strategy and development of novel approaches to achieve high product quality. Additionally, in recent years as more complex molecules emerge such as bispecific and trispecific antibodies, the molecular heterogeneity due to incomplete formation of the interchain disulfide bonds becomes a more imperative issue. Given the disulfide reduction challenges that our industry are facing, in this review, we provide a comprehensive contemporary scientific insight into the root cause analysis of disulfide reduction during process development of antibody therapeutics, mitigation strategies and recovery based on our expertise in commercial and clinical manufacturing of biologics. First, this paper intended to highlight different aspects of the root cause for disulfide reduction. Secondly, to provide a broader understanding of the disulfide bond reduction in downstream process, this paper discussed disulfide bond reduction impact to product stability and process performance, analytical methods for detection and characterization, process control strategies and their manufacturing implementation. In addition, brief perspectives on development of future mitigation strategies will also be reviewed, including platform alignment, mitigation strategy application for bi- and tri-specific antibodies and using machine learning to identify molecule susceptibility of disulfide bond reduction. The data in this review are originated from both the published papers and our internal development work.

Zizhuo Xing

and 7 more

Significant amounts of soluble product aggregates were observed in the low-pH viral inactivation (VI) opertion during an initial scale-up run for an IgG4 monoclonal antibody (mAb IgG4-N1). Being earlier in development, a scale-down model did not exist, nor was it practical to use costly Protein A eluate (PAE) for testing the VI process at scale, thus, a computational fluid dynamics (CFD)-based high molecular weight (HMW) prediction model was developed for troubleshooting and risk mitigation. It was previously reported that the IgG4-N1 molecules upon exposure to low pH tend to change into transient and partially unfolded monomers during VI acidification (i.e., VIA) and form aggregates after neutralization (i.e., VIN) (Jin et al. 2019). Therefore, the CFD model reported here focuses on the VIA step. The model mimics the continuous addition of acid to PAE and tracks acid distribution during VIA. Based on the simulated low-pH zone (≤ pH 3.3) profiles and PAE properties, the integrated low-pH zone (ILPZ) value was obtained to predict HMW level at the VI step. The simulations were performed to examine the operating parameters, such as agitation speed, acid addition rate, and protein concentration of PAE, of the pilot scale (50-200L) runs. The conditions with predictions of no product aggregation risk were recommended to the real scale-up runs, resulted in 100% success rate of the consecutive 12 pilot-scale runs. This work demonstrated that the CFD-based HMW prediction model could be used as a tool to facilitate the scale up of the low-pH VI process directly from bench to pilot/production scale.

Letha Chemmalil

and 9 more