Improved manufacturability of mAb variants
In the pharmaceutical and biotechnology industry, development programs
of therapeutic mAbs are often abandoned due to poor manufacturability.
Poor manufacturability of an antibody includes low expression cultures
or formation of aggregates. Developability studies are now being carried
out early during the process to identify any problems associated with
protein stability, solubility that is insufficient to meet dosing need
or sensitivity to stress. These experiments include short-term stability
studies at different temperatures, freeze-thaw cycles, forced
degradation studies and viscosity determination at high concentration of
samples (X. Yang et al., 2013). Considering that drug substance and drug
product quality attributes are affected by minimal changes in the
manufacturing process, all steps may be critical to material quality and
patient safety. Thus, it is mandatory to minimize and control the level
of antibody variants in the drug product.
As early as translation, variants can be formed in production cell lines
through the misincorporation of amino acids, such as the incorporation
of serine instead of asparagine in CHO cells. While both are neutral,
polar amino acids with similar physical properties, this results in the
generation of a different amino acid sequence, a phenomenon found to be
caused by starvation of a particular amino acid in cell medium (Khetan
et al., 2010; Parker, Pollard, Friesen, & Stanners, 1978; Wen et al.,
2009; X. C. Yu et al., 2009). Despite this, most variants originate from
post-translational modifications (PTMs) or are generated during the
manufacturing process. Modifications of a drug are considered critical
quality attributes (CQA), if they are linked to stability, activity, or
efficacy (Jacobi et al., 2014). Major quality modifications are
extensively described in literature (Jacobi et al., 2014; Sissolak,
Lingg, Sommeregger, Striedner, & Vorauer-Uhl, 2019), and glycosylation
variants are commonly known to influence pharmacokinetics, antigen
binding and immunogenicity (Eon-Duval, Broly, & Gleixner, 2012; Mimura
et al., 2018). A priori knowledge and glycoengineering advances
of therapeutic IgG antibodies provide opportunities to optimize safety,
functionality and efficacy of the drug (Sissolak et al., 2019). Examples
of applying protein engineering techniques include amino acid exchanges
to prevent aggregation or avoiding methionine residues in
complementary-determining regions (CDRs) to prevent impactful oxidation.
mAb oxidation occurs primarily on methionine residues, leading to more
polar side chains by the formation of methionine sulfoxide.
Additionally, replacement of N-terminal residues by glutamine can be
designed to reduce the number of charge variants arising upon
pyroglutamate formation (Beck, Wurch, Bailly, & Corvaia, 2010; Y. D.
Liu, Goetze, Bass, & Flynn, 2011). Improvements of protein sequence
modifications by in silico engineering and structure-based
rational design simulations have provided advancements in predicting
aggregation-prone regions, stability calculations and solubility of a
monoclonal antibody (Arslan, Karadag, & Kalyoncu, 2019; Kuroda &
Tsumoto, 2020; Sormanni, Amery, Ekizoglou, Vendruscolo, & Popovic,
2017). Furthermore, improvement of the thermodynamic stability of a
monoclonal antibody can be monitored by experimental stress studies,
including temperature, pH and protease incubations, to select molecules
more resistant to aggregation (Arslan et al., 2019; Enever,
Pupecka-Swider, & Sepp, 2015; Tesar et al., 2017). Monoclonal antibody
structures may be altered when exposed to different temperatures, pH and
stress conditions, causing unwanted products which may exhibit increased
immunogenicity as well as reduced efficacy and activity (Cui, Cui, Chen,
Li, & Guan, 2017). Further protein engineering approaches are beyond
the scope of this review and have been described elsewhere (Chiu &
Gilliland, 2016; Popplewell, 2015; C. Yang, Gao, & Gong, 2018).
Along with protein engineering efforts, the central goal of process
development of biologics is the establishment of manufacturing
technologies and processes that will generate consistency in different
batches (Carson, 2005). Quality-by-design (QbD) was established and
first developed by Dr. Joseph M. Juran in the early 1990s, who believed
that quality should be designed into a product, and that most quality
crises and complications arose from the way a product was designed
(Juran, 1992). Along with GMP, regulatory agencies encourage risk-based
approaches and have adopted the QbD principles since early 2000s (L. X.
Yu et al., 2014). By providing guidance on pharmaceutical development,
QbD aims at facilitating the design of products and processes,
ultimately maximizing the product’s efficacy and safety profile while
enhancing product manufacturability (Alt et al., 2016). The principles
are described by the International Council for Harmonisation of
Technical Requirements for Pharmaceuticals for Human Use (ICH) guideline
documents, ICH Q8-11. The guideline documents cover: pharmaceutical
development in ICH Q8, quality risk management in ICH Q9, pharmaceutical
quality system in ICH Q10, and development and manufacture of drug
substance in ICH Q11 (ICH ; Yu et al., 2014). The objectives of
pharmaceutical QbD include: achieving meaningful product quality
specifications based on clinical performance; increasing process
capability and reducing product variability and defects by enhancing
product and process design; facilitating the ability to identify root
causes of failures; and improving product development and manufacturing
efficiencies (L. X. Yu et al., 2014). Of the QbD milestones,critical quality attributes (CQA) identifies the crucial
characteristics of a product required to ensure quality from a patient’s
perspective. By identifying specifications or numerical ranges for CQAs,
candidates may be ranked and discarded accordingly (Somma, 2007).
Several QbD milestones are summarized in Figure 2.
For improved manufacturability, the QbD paradigm has been incorporated
into mAb-specific aspects. Karlbert et al. (2018) reported the adoption
of quantitative structure-activity relationship (QSAR)-type modelling by
exploiting the structural characteristics of mAbs for directed QbD
implementation, increasing both product and process understanding. For
upstream processes, Nagashima et al. (2013) applied the QbD approach to
mAb production in CHO cells, focusing on quality risk management using
failure mode and effects analysis. By doing so, the authors identified
potential critical process parameters (CPPs) and key performance
indicators (KPI) that may impact quality attributes and gained further
knowledge to mitigate any future cell culture-related issues (Nagashima
et al., 2013). On a scale beyond single processes, Genentech
participated in a pilot program launched in 2008 by the FDA in an effort
to expand the implementation of QbD, leading to imperative improvement
of QbD tools and concepts for subsequent products (Alt et al., 2016;
Finkler & Krummen, 2016). Today, QbD activities are fully integrated
into product development phases and have led to more robust, productive
manufacturing processes with increased clinical efficiency (Gronemeyer
et al., 2014). A recent report has also demonstrated the efficient
implementation and feasibility of using QbD-based similarity assessment
of a biosimilar mAb, using an adalimumab biosimilar to Humira® (Zhang et
al., 2020).