Implementing quality by design for biotech products: Are regulators on track?

Current challenges and recent advances on the path towards continuous biomanufacturing

Continuous biopharmaceutical manufacturing is currently a field of intense research due to its potential to make the entire production process more optimal for the modern, ever-evolving biopharmaceutical market. Compared to traditional batch manufacturing, continuous bioprocessing is more efficient, adjustable, and sustainable and has reduced capital costs. However, despite its clear advantages, continuous bioprocessing is yet to be widely adopted in commercial manufacturing. This article provides an overview of the technological roadblocks for extensive adoptions and points out the recent advances that could help overcome them. In total, three key areas for improvement are identified: Quality by Design (QbD) implementation, integration of upstream and downstream technologies, and data and knowledge management. First, the challenges to QbD implementation are explored. Specifically, process control, process analytical technology (PAT), critical process parameter (CPP) identification, and mathematical models for bioprocess control and design are recognized as crucial for successful QbD realizations. Next, the difficulties of end-to-end process integration are examined, with a particular emphasis on downstream processing. Finally, the problem of data and knowledge management and its potential solutions are outlined where ontologies and data standards are pointed out as key drivers of progress.

Quality by Design (QbD) Approach in Marketing Authorization Procedures of Non-Biological Complex Drugs: A Critical Evaluation

The emergence of innovator-driven complex drug products, such as Non-Biological Complex Drugs (NBCDs), has provided disruptive advances in the Nanotechnology and Biotechnology fields. However, the design and development of NBCDs can be particularly challenging due to some unresolved scientific and regulatory challenges associated with the pharmaceutical quality assessment. The application of a more holistic, systematic, integrated science and risk-based approach, such as Quality by Design (QbD), is essential to address key scientific, technological, and regulatory constraints in the research and development of the NBCDs. The deeper product and process understanding derived from the implementation of the QbD approach ensures consistent, reliable, and high-quality pharmaceutical products. Furthermore, this approach promotes innovation and continuous improvement in the entire product lifecycle. Regulatory authorities highly recommend QbD-based submissions to successfully translate NBCDs from laboratory-scale research to the pharmaceutical market with the required quality, safety, and efficacy standards. The main aim of this article is to obtain a comprehensive and in-depth investigation into the state of implementation of the QbD approach in the pharmaceutical development and marketing authorization of NBCDs in Europe and the United States, through the analysis of the available data from their regulatory dossiers. In addition, it aims to understand and discuss how the QbD approach is used and implemented for complex drug products in the pharmaceutical industry, highlighting the gaps and challenges involved with its implementation. An analysis is held regarding QbD's advantages in terms of knowledge growth, regulatory flexibility, and the speed of development based on big data science, along with the reduction of regulatory failures and market withdrawals.

Automated multi-attribute method sample preparation using high-throughput buffer exchange tips

RATIONALE

The multi-attribute method (MAM) has become a valuable mass spectrometry (MS)-based tool that can identify and quantify the site-specific product attributes and purity information for biotherapeutics such as monoclonal antibodies (mAbs) and fusion molecules in recent years. As we expand the use of the MAM at various stages of drug development, it is critical to enhance the sample preparation throughput without additional chemical modifications and variability.

METHODS

In this study, a fully automated MAM sample preparation protocol is presented, where rapid desalting in less than 15 minutes is achieved using miniaturized size-exclusion chromatography columns in pipette tips on an automated liquid handler. The peptide samples were analyzed using an electrospray ionization (ESI) orbitrap mass spectrometer coupled to an ultra-high-performance liquid chromatography (UHPLC) system with a dual column switching system.

RESULTS

No significant change was observed in product attributes and their quantities compared with manual, low-artifact sample preparation. The sample recovery using the buffer exchange tips was greatly enhanced over the manual spin cartridges while still demonstrating excellent reproducibility for a wide variety of starting sample concentrations. Unlike a plate desalting system, the individual columns provide flexibility in the number of samples prepared at a time and sample locations within plates.

CONCLUSIONS

This automated protocol enables the preparation of up to 96 samples with less "at-bench" time than the manual preparation of a smaller batch of samples, thereby greatly facilitating support of process development and the use of the MAM in quality control.

Multi-attribute method performance profile for quality control of monoclonal antibody therapeutics

Multi-attribute method (MAM) using peptide map analysis with high resolution mass spectrometry is increasingly common in product characterization and the identification of critical quality attributes (CQAs) of biotherapeutic proteins. Capable of providing structural information specific to amino acid residues, quantifying relative abundance of product variants or degradants, and detecting profile changes between product lots, a robust MAM can replace multiple traditional methods that generate profile-based information for product release and stability testing. In an effort to provide informative and efficient analytical monitoring for monoclonal antibody (mAb) products, from early development to manufacturing quality control, we describe the desired MAM performance profile and address the major scientific challenges in MAM method validation. Furthermore, to support fast speed investigational product development, we describe a platform method validation strategy and results of an optimized MAM workflow. This strategy is applied to support the use of MAM for multiple mAb products with similar structures and physicochemical properties, requiring minimal product-specific method validation activities. Three mAb products were used to demonstrate MAM performance for common and representative product quality attributes. Method validation design and acceptance criteria were guided by the Analytical Target Profile concept, as well as relevant regulatory guidelines to ensure the method is fit-for-purpose. A comprehensive system suitability control strategy was developed, and reported here, to ensure adequate performance of the method including sample preparation, instrument operation, and data analysis. Our results demonstrated sufficient method performance for the characteristics required for quantitative measurement of product variants and degradants.

Quality by Design tools reducing the gap from bench to bedside for nanomedicine

Pharmaceutical nanotechnology research is focused on smart nano-vehicles, which can deliver active pharmaceutical ingredients to enhance their efficacy through any route of administration and in the most varied therapeutical application. The design and development of new nanopharmaceuticals can be very laborious. In recent years, the application of mathematics, statistics and computational tools is emerging as a convenient strategy for this purpose. The application of Quality by Design (QbD) tools has been introduced to guarantee quality for pharmaceutical products and improve translational research from the laboratory bench into applicable therapeutics. In this review, a collection of basic-concept, historical overview and application of QbD in nanomedicine are discussed. A specific focus has been put on Response Surface Methodology and Artificial Neural Network approaches in general terms and their application in the development of nanomedicine to monitor the process parameters obtaining optimized system ensuring its quality profile.

In silico process characterization for biopharmaceutical development following the quality by design concept

With the quality by design (QbD) initiative, regulatory authorities demand a consistent drug quality originating from a well-understood manufacturing process. This study demonstrates the application of a previously published mechanistic chromatography model to the in silico process characterization (PCS) of a monoclonal antibody polishing step. The proposed modeling workflow covered the main tasks of traditional PCS studies following the QbD principles, including criticality assessment of 11 process parameters and establishment of their proven acceptable ranges of operation. Analyzing effects of multi-variate sampling of process parameters on the purification outcome allowed identification of the edge-of-failure. Experimental validation of in silico results demanded approximately 75% less experiments compared to a purely wet-lab based PCS study. Stochastic simulation, considering the measured variances of process parameters and loading material composition, was used to estimate the capability of the process to meet the acceptance criteria for critical quality attributes and key performance indicators. The proposed workflow enables the implementation of digital process twins as QbD tool for improved development of biopharmaceutical manufacturing processes.

Fully automated peptide mapping multi-attribute method by liquid chromatography-mass spectrometry with robotic liquid handling system

The multi-attribute method (MAM) based on liquid chromatography (LC)-tandem mass spectrometry is emerging as a powerful tool to directly monitor multiple product quality attributes simultaneously. To better implement MAM, either for product characterization or for quality control (QC), there is a need for a robust, universal, and high-throughput workflow that can be broadly adopted in different laboratories with minimal barriers to implementation. Manual preparation of samples for MAM, however, is labor intensive and produces nontrivial variations across analysts and laboratories. We describe the development of a fully automated peptide mapping procedure with a high-throughput robotic liquid handling system to improve sample handling capacity and outcome reproducibility while saving analyst hands-on time. Our procedure features the automation of a "microdialysis" step, an efficient desalting approach prior to proteolytic digestion that optimizes digestion completeness and consistency each time. The workflow is completely hands-free and requires the analyst only to pre-normalize the sample concentrations and to load buffers and reagents at their designated positions on the robotic deck. The robotic liquid handler performs all the subsequent preparation steps and stores the digested samples on a chiller unit to await retrieval for further analysis. We also demonstrate that the manual and automated procedures are comparable with regard to protein sequence coverage, digestion completeness and consistency, and quantification of posttranslational modifications. Notably, in contrast to a previously reported automated sample preparation protocol that relied on customized accessories, all components in our automation procedure are commercial products that are readily available. In addition, we also present the high-throughput data analysis workflow by using Protein Metrics. The automation procedure can be applied cross-functionally in the biopharmaceutical industry and, given its practicality and reproducibility, can pave the way for MAM implementation in QC laboratories.

Implementation of Quality by Design (QbD) Principles in Regulatory Dossiers of Medicinal Products in the European Union (EU) Between 2014 and 2019

BACKGROUND

Quality by Design (QbD) is a systematic risk-based approach to development, with predefined characteristics and quality risk management throughout the life cycle of a product. International Conference on Harmonization (ICH) guidelines Q8-Q11 give guidance on QbD applications with ICH Q8 (R2)-approved in 2009-describing the principles of QbD in detail. Since its adoption over 10 years ago, more information about QbD usage for the development of medicinal products is expected to be written in regulatory dossiers by companies.

METHODS

The present study set out to evaluate the implementation of QbD principles and elements in all EU approved marketing applications (MA) (n = 494), based on information available in the European Public Assessment Reports (EPARs), for a period of six years (2014-2019), starting 5 years after QbD adoption.

RESULTS

Of the 494 MAs, 271 were submitted with a full dossier (article 8(3)). According to EMA (38%), out of the 271 full dossier submissions, only 104 were developed using full QbD. This figure did not increase during this period. Interestingly, between 2014 and 2019, several MAs were not developed via full QbD implementation but used one or more QbD elements during development, including design space. In addition, a higher percentage of small molecule products were developed with QbD as opposed to biotechnology-derived products (78% vs. 22%, respectively).

CONCLUSION

Overall, QbD during development of medicinal products is still not commonly described in dossiers. However, more companies started mentioning QbD elements, thus making it a promising step toward QbD as the standard for development in the future.

Native peptide mapping - A simple method to routinely monitor higher order structure changes and relation to functional activity

In the biopharmaceutical environment, controlling the Critical Quality Attributes (CQA) of a product is essential to prevent changes that affect its safety or efficacy. Physico-chemical techniques and bioassays are used to screen and monitor these CQAs. The higher order structure (HOS) is a CQA that is typically studied using techniques that are not commonly considered amenable to quality control laboratories. Here, we propose a peptide mapping-based method, named native peptide mapping, which could be considered as straightforward for HOS analysis and applicable for IgG4 and IgG1 antibodies. The method was demonstrated to be fit-for-purpose as a stability-indicating assay by showing differences at the peptide level between stressed and unstressed material. The unfolding pathway induced by a heat stress was also studied via native peptide mapping assay. Furthermore, we demonstrated the structure–activity relationship between HOS and biological activity by analyzing different types of stressed samples with a cell-based assay and the native peptide mapping. The correlation between both sets of results was highlighted by monitoring peptides located in the complementary-determining regions and the relative potency of the biotherapeutic product. This relationship represents a useful approach to interrogate the criticality of HOS as a CQA of a drug.

A Different Perspective: How Much Innovation Is Really Needed for Monoclonal Antibody Production Using Mammalian Cell Technology?

As biopharmaceutical companies have optimized cell line and production culture process development, titers of recombinant antibodies have risen steadily to 3-8 g/L for fed-batch mammalian cultures at production scales of 10 kL or larger. Most new antibody products are produced from Chinese Hamster Ovary (CHO) cell lines, and there are relatively few alternative production hosts under active evaluation. Many companies have adopted a strategy of using the same production cell line for early clinical phases as well as commercial production, which reduces the risk of product comparability issues during the development lifecycle. Product quality and consistency expectations rest on the platform knowledge of the CHO host cell line and processes used for the production of many licensed antibodies. The lack of impact of low-level product variants common to this platform on product safety and efficacy also builds on the established commercial history of recombinant antibodies, which dates back to 1997.Efforts to increase titers further will likely yield diminishing returns. Very few products would benefit significantly from a titer greater than 8 g/L; in many cases, a downstream processing bottleneck would preclude full recovery from production-scale bioreactors for high titer processes. The benefits of a process platform based on standard fed-batch production culture include predictable scale-up, process transfer, and production within a company's manufacturing network or at a contract manufacturing organization. Furthermore, the confidence in an established platform provides key support towards regulatory flexibility (e.g., design space) for license applications following a quality-by-design strategy.These factors suggest that novel technologies for antibody production may not provide a substantial return on investment. What, then, should be the focus of future process development efforts for companies that choose to launch antibody products using their current platform? This review proposes key focus areas in an effort to continually improve process consistency, assure acceptable product quality, and establish appropriate process parameter limits to enable flexible manufacturing options.

Development of L-Asparaginase Biobetters: Current Research Status and Review of the Desirable Quality Profiles

L-Asparaginase (ASNase) is a vital component of the first line treatment of acute lymphoblastic leukemia (ALL), an aggressive type of blood cancer expected to afflict over 53,000 people worldwide by 2020. More recently, ASNase has also been shown to have potential for preventing metastasis from solid tumors. The ASNase treatment is, however, characterized by a plethora of potential side effects, ranging from immune reactions to severe toxicity. Consequently, in accordance with Quality-by-Design (QbD) principles, ingenious new products tailored to minimize adverse reactions while increasing patient survival have been devised. In the following pages, the reader is invited for a brief discussion on the most recent developments in this field. Firstly, the review presents an outline of the recent improvements on the manufacturing and formulation processes, which can severely influence important aspects of the product quality profile, such as contamination, aggregation and enzymatic activity. Following, the most recent advances in protein engineering applied to the development of biobetter ASNases (i.e., with reduced glutaminase activity, proteolysis resistant and less immunogenic) using techniques such as site-directed mutagenesis, molecular dynamics, PEGylation, PASylation and bioconjugation are discussed. Afterwards, the attention is shifted toward nanomedicine including technologies such as encapsulation and immobilization, which aim at improving ASNase pharmacokinetics. Besides discussing the results of the most innovative and representative academic research, the review provides an overview of the products already available on the market or in the latest stages of development. With this, the review is intended to provide a solid background for the current product development and underpin the discussions on the target quality profile of future ASNase-based pharmaceuticals.

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.

Modeling in the quality by design environment: Regulatory requirements and recommendations for design space and control strategy appointment

Mathematical models can be used as an integral part of the quality by design (QbD) concept throughout the product lifecycle for variety of purposes, including appointment of the design space and control strategy, continual improvement and risk assessment. Examples of different mathematical modeling techniques (mechanistic, empirical and hybrid) in the pharmaceutical development and process monitoring or control are provided in the presented review. In the QbD context, mathematical models are predominantly used to support design space and/or control strategies. Considering their impact to the final product quality, models can be divided into the following categories: high, medium and low impact models. Although there are regulatory guidelines on the topic of modeling applications, review of QbD-based submission containing modeling elements revealed concerns regarding the scale-dependency of design spaces and verification of models predictions at commercial scale of manufacturing, especially regarding real-time release (RTR) models. Authors provide critical overview on the good modeling practices and introduce concepts of multiple-unit, adaptive and dynamic design space, multivariate specifications and methods for process uncertainty analysis. RTR specification with mathematical model and different approaches to multivariate statistical process control supporting process analytical technologies are also presented.

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.