Development of a quantitative mass spectrometry multi-attribute method for characterization,quality control testing and disposition of biologics

Regulatory agencies have recently recommended a Quality by Design (QbD) approach for the manufacturing of therapeutic molecules. A QbD strategy requires deep understanding at the molecular level of the attributes that are crucial for safety and efficacy and for insuring that the desired quality of the purified protein drug product is met at the end of the manufacturing process. A mass spectrometry (MS)-based approach to simultaneously monitor the extensive array of product quality attributes (PQAs) present on therapeutic molecules has been developed. This multi-attribute method (MAM) uses a combination of high mass accuracy / high resolution MS data generated by Orbitrap technology and automated identification and relative quantification of PQAs with dedicated software (Pinpoint). The MAM has the potential to replace several conventional electrophoretic and chromatographic methods currently used in Quality Control to release therapeutic molecules. The MAM represents an optimized analytical solution to focus on the attributes of the therapeutic molecule essential for function and implement QbD principles across process development, manufacturing and drug disposition.     

Optimization of a mAb production process with regard to robustness and product quality using quality by design principles

Quality by Design principles are well described and widely used in biopharmaceutical industry. The characterization of a monoclonal antibody (mAb) production process is crucial for novel process development and control. Yet, the application throughout the entire upstream process was rarely demonstrated. Following previously published research, this study marks the second step toward a complete process characterization and is focused on the effect of critical process parameters on the antibody production efficiency and quality of the process. In order to conduct the complex Design of Experiments approach with optimal control and comparability, the ambr®15 micro bioreactor platform was used. Investigated parameters included the pH and dissolved oxygen set points, the initial viable cell density (iVCD) as well as the N‐1 duration. Various quality attributes (e.g., growth rate, viability, mAb titer, and peak proportion) were monitored and analyzed using multivariate data analysis to evaluate the parameter effects. The pH set point and the initial VCD were identified as key process parameters with strong influence on the cell growth as well as the mAb production and its proportion to the total protein concentration. For optimization and improvement in robustness of these quality attributes the pH must be increased to 7.2, while the iVCD must be lowered to 0.2 × 10⁶ cells/mL. Based on the defined design space, additional experiments verified the results and confirmed the intact bioactivity of the antibody. Thereby, process control strategies could be tuned toward high cell maintenance and mAb production, which enable optimal downstream processing.     

A Quadrupole Dalton-based multi-attribute method for product characterization,process development,and quality control of therapeutic proteins

During manufacturing and storage process, therapeutic proteins are subject to various post-translational modifications (PTMs), such as isomerization, deamidation, oxidation, disulfide bond modifications and glycosylation. Certain PTMs may affect bioactivity, stability or pharmacokinetics and pharmacodynamics profile and are therefore classified as potential critical quality attributes (pCQAs). Identifying, monitoring and controlling these PTMs are usually key elements of the Quality by Design (QbD) approach. Traditionally, multiple analytical methods are utilized for these purposes, which is time consuming and costly. In recent years, multi-attribute monitoring methods have been developed in the biopharmaceutical industry. However, these methods combine high-end mass spectrometry with complicated data analysis software, which could pose difficulty when implementing in a quality control (QC) environment. Here we report a multi-attribute method (MAM) using a Quadrupole Dalton (QDa) mass detector to selectively monitor and quantitate PTMs in a therapeutic monoclonal antibody. The result output from the QDa-based MAM is straightforward and automatic. Evaluation results indicate this method provides comparable results to the traditional assays. To ensure future application in the QC environment, this method was qualified according to the International Conference on Harmonization (ICH) guideline and applied in the characterization of drug substance and stability samples. The QDa-based MAM is shown to be an extremely useful tool for product and process characterization studies that facilitates facile understanding of process impact on multiple quality attributes, while being QC friendly and cost-effective.     

Chromatography process development in the quality by design paradigm I: Establishing a high‐throughput process development platform as a tool for estimating “characterization space” for an ion exchange chromatography step

This article describes the development of a high‐throughput process development (HTPD) platform for developing chromatography steps. An assessment of the platform as a tool for establishing the “characterization space” for an ion exchange chromatography step has been performed by using design of experiments. Case studies involving use of a biotech therapeutic, granulocyte colony‐stimulating factor have been used to demonstrate the performance of the platform. We discuss the various challenges that arise when working at such small volumes along with the solutions that we propose to alleviate these challenges to make the HTPD data suitable for empirical modeling. Further, we have also validated the scalability of this platform by comparing the results from the HTPD platform (2 and 6 μL resin volumes) against those obtained at the traditional laboratory scale (resin volume, 0.5 mL). We find that after integration of the proposed correction factors, the HTPD platform is capable of performing the process optimization studies at 170‐fold higher productivity. The platform is capable of providing semi‐quantitative assessment of the effects of the various input parameters under consideration. We think that platform such as the one presented is an excellent tool for examining the “characterization space” and reducing the extensive experimentation at the traditional lab scale that is otherwise required for establishing the “design space.” Thus, this platform will specifically aid in successful implementation of quality by design in biotech process development. This is especially significant in view of the constraints with respect to time and resources that the biopharma industry faces today. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29: 403–414, 2013     

Design of experiments applications in bioprocessing: Chromatography process development using split design of experiments

Development of a chromatographic step in a time and resource efficient manner remains a serious bottleneck in protein purification. Chromatographic performance typically depends on raw material attributes, feed material attributes, process factors, and their interactions. Design of experiments (DOE) based process development is often chosen for this purpose. A challenge is, however, in performing a DOE with such a large number of process factors. A split DOE approach based on process knowledge in order to reduce the number of experiments is proposed. The first DOE targets optimizing factors that are likely to significantly impact the process and their effect on process performance is unknown. The second DOE aims to fine-tune another set of interacting process factors, impact of whom on process performance is known from process understanding. Furthermore, modeling of a large set of output response variables has been achieved by fitting the output responses to an empirical equation and then using the parametric constants of the equation as output response variables for regression modeling. Two case studies involving hydrophobic interaction chromatography for removal of aggregates and cation exchange chromatography for separation of charge variants and aggregates have been utilized to illustrate the proposed approach. Proposed methodology reduced total number of experiments by 25% and 72% compared to a single DOE based on central composite design and full factorial design, respectively. The proposed approach is likely to result in a significant reduction in resources required as well as time taken during process development. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2730, 2019     

Quality attributes of recombinant therapeutic proteins: an assessment of impact on safety and efficacy as part of a quality by design development approach

Quality by Design (QbD) is a new approach to the development of recombinant therapeutic protein products that promotes a better understanding of the product and its manufacturing process. The first step in the QbD approach consists in identifying the critical quality attributes (CQA), i.e., those quality attributes of the product that have an impact on its clinical efficacy or safety. CQAs are identified through a science-based risk assessment taking into consideration a combination of clinical and nonclinical data obtained with the molecule or other similar molecules or platform products, as well as the published literature. The purpose of this article is to perform a comprehensive review of the published literature, supporting an assessment of the impact on safety and efficacy of the quality attributes commonly encountered in recombinant therapeutic proteins, more specifically those produced in mammalian cell expression systems. Quality attributes generally observed in biopharmaceutical proteins including product-related impurities and substances, process-related impurities, product attributes, and contaminants are evaluated one by one for their impact on biological activity, pharmacokinetics and pharmacodynamics, immunogenicity, and overall safety/toxicity.