FEATURED ARTICLEJoe Shambaugh, Head Genedata Expressionist USA, Genedata, Lexington, USA Automated Quality Monitoring of Biotherapeutics by Multi-attribute Methods

Mass spectrometry (MS) provides methods for simultaneously measuring multiple biotherapeutic quality attributes at the molecular level. Applying these multi-attribute methods (MAMs) can increase product quality while reducing development and manufacturing costs. Here we present an implementation of MAMs using Genedata Expressionist®—the software platform of choice for the processing, analysis, and management of MS data.

Industry embraces Quality by DesignDevelopment and manufacturing of novel biotherapeutics is a time-consuming and costly process. One problem is high attrition rates during development due to lack of efficacy and potential safety issues of the molecule under investigation; an-other is the incidence of quality problems that frequently arise during the bioprocess development and manufacturing phase.

To mitigate these challenges, the FDA has suggested the adoption of Quality by Design (QbD), a systematic approach to collect and analyze all quality-relevant information during the complete bioprocess development and manufacturing process. QbD requires the measurement of Product Quality Attributes (PQAs), which are assessed and ranked according to their potential impact on product quality, ultimately defining the Critical Quality Attributes (CQAs).

MAMs provide the best way to measure CQAs In principle, CQAs can be measured throughout a molecule’s life cycle using a wide array of analytical assays including IEx, CE-SDS, CEX-HPLC, SEC, ELISA, etc. However, the proliferation of a wide array of assays creates a major time and cost burden related to setting up, mastering, managing, and maintaining multiple analytical platforms. Furthermore, collecting analyti-cal results from different assays and integrating them into a single comprehensive database provides a significant IT chal-lenge. This ultimately results in a major data integrity problem and the monitoring of CQAs becomes impossible.

Many major players in the biopharma industry have therefore started to adopt MS as the primary, consolidated analytical

platform for monitoring CQAs. Whereas currently employed assays often provide only an indirect measure of a CQA, MS methods frequently deliver detailed information directly re-lated to the CQA. In addition, MS-based methods can moni-tor multiple CQAs simultaneously within a single experiment. Evidence indicates that these MS-based MAMs currently pro-vide the most efficient approach to monitoring CQAs.

Software requirements for MS-based MAMsApplying MAMs to monitor CQAs can generate significant operational cost savings by consolidating traditional assays. The cost savings can be further increased if the process of col-lecting, managing, processing, analyzing, and reporting of data can be addressed with a single, integrated software system. Many bioanalytical labs still employ a heterogeneous collection of loosely connected software tools—often from different soft-ware vendors—for data processing, analysis, and reporting. The process of data transfer is usually error-prone and the quality of reported results is thus an inherent problem for those labs. Furthermore, experimental data is frequently stored in places where access is limited to the persons who have been directly involved in data generation. Integrating data across different labs and experiments is then a major issue. Coupled with the high cost of maintaining multiple IT tools, the lack of integrat-ed data management creates a data integrity problem which ultimately can become a huge financial risk for biopharma companies, as several examples over the last few years have proven. Genedata has recognized that the successful imple-mentation of MAMs for monitoring CQAs in biopharma requires a single integrated enterprise software platform for the collec-tion, management, processing, analysis, and reporting of MS

Reducing time for data pro-cessing and analysis. Any workflow created in Gene-data Expressionist can be automated. Workflows can be set up, tested, and locked down before specifying the automation protocol. For example, a workflow might be created by an expert at the end of a project, and there-after routinely applied to provide quality control (QC) and quantitative data analysis of the molecular attributes of interest (Figure 1).

Alternatively, at the begin-ning of a project, a workflow might be set up in method development and then evolve as more data is analyzed and the workflow is tested for robustness. The iterative

nature of method development is facilitated by automation, allowing the analysis methodology to evolve as needed to reach a robust solution that is then passed to production. In this way, even the most complex data analysis can be devel-oped and deployed in a way to limit users’ input requirements.

Depending on the context and user applying it, any workflow can be employed in a manual, semi-automated, or fully auto-mated mode. In combination with its scalable architecture, Genedata Expressionist enables the application of standard-ized MAMs of any complexity at any stage of a biomolecule’s life cycle, and provides significantly streamlined, high-quality data analysis.

data. The platform needs to be highly scalable for the rapidly increasing volumes of MS data as well as highly flexible to support numerous diverse MS-based methods. Furthermore it needs to address the following key requirements:

33 Support of harmonization of MAM-related data processes to ensure robust, high-quality results and efficient communication across an organization.

33 Support of automation of MAM-related data processes to reduce time-consuming data analysis steps.

33 Support for deployment in GxP-compliant/regulated environments.

Genedata Expressionist—a software platform for MAM-based monitoring of CQAs

Supporting diverse applications and addressing changing needs. Typically, the specific analyses required for the char-acterization of biotherapeutic molecules differ from one mol-ecule to the next. This means that any software adopted by an organization for the characterization of biopharmaceuticals must be flexible enough to address current and future needs. Genedata Expressionist enables submission of raw data from any MS instrument for direct analysis by highly efficient algorithms. Any MAM-related data analysis can be customized to address specific requirements, and saved for later reuse (Figure 1). To address changes in analysis protocols as the molecule is handed from one group to another throughout the R&D process, workflows can be versioned as required.

Figure 1: Schematic representation of MAM setup and application as routine monitoring method. Peptide mapping workflow is created, optimized, and applied for candidate characterization (left). Product knowledge is consolidated (center) before an automated MAM workflow monitors CQAs (right).

Figure 2: Corporate knowledge base is accumulated in libraries that are re-used for automated CQA monitoring workflow at a later stage.

MAM Setup

Workflow is built by connecting activities suited for a specific MAM (e.g. pepmap)

Automated CQA monitoring workflow leveraging product knowledge

Product knowledge is accumulated and consolidated

Create Apply

Knowledge build-up

MeasureLoad/Process Data

System Suitability

Review & Release

Monitor CQAs

Detect Unknowns

Custom Report

m/z

RT

Automated MAM

Ensuring robust, high-quality results. All organizations can benefit from standard operating procedures (SOPs) that ensure data integrity and high result quality. The biopharma industry is well aware of these benefits and routinely employs SOPs in production and QC. The requirements of QbD—coupled with a desire to implement MS-based MAMs—mean that companies must refine their SOPs. With Genedata Expressionist, the workflows become SOPs and as such are easily deployed.

Ensuring efficient communication and method and project management across the organizations. The implementation of MAMs across different stages of a molecule’s life cycle represents an extraordinary opportunity for the biopharma industry to adopt a genuine QbD approach. To meet this chal-lenge, organizations must enable collaboration, and knowl-edge gained about the product must be consolidated and disseminated across different functions in discovery, develop-ment, and manufacturing.

Together with advanced project management functionalities, the Genedata Expressionist central server platform enables organizations to share data, methods, and results from differ-

ent laboratories, and facilitates integration of metadata into corporate knowledge bases. Multi-level user access rights management ensures data security and thus data integrity. Final results are automatically consolidated in customizable reports that smoothly integrate with corporate file structures (for example, PDF reports for Lab Notebook entries). Using Genedata Expressionist, methods and knowledge obtained about a product can be transferred seamlessly within and between organizations.

Supporting implementation in regulated environments. Implementation of MAMs in manufacturing requires a soft-ware platform that can be deployed in regulated environ-ments. Genedata Expressionist is ready for deployment with workflow and report approval through electronic signatures (FDA 21 CFR Part 11), full audit logs on data and results traces, and support of SOPs.

A case study: Establishing MAMs to monitor CQAs MAM-based CQA monitoring was implemented with Genedata Expressionist serving as the central enterprise software plat-form for the collection, management, processing, analysis, and reporting of CQAs.

Building up knowledge throughout the R&D process. First, peptide mapping was implemented to measure PQAs throughout the R&D process. Peptide mapping is a widely used MS method for character-izing the primary structure of proteins and has become one of the most frequently applied MAMs. A custom peptide map-ping workflow for the molecule candidate was built and shared across the whole biopharma R&D organization to harmonize the process (Figure 1).

This ensured robust, accurate and comparable results for PQA measurement. Genedata Expressionist served as: i) a central enterprise-wide data management infrastructure allowing the building and shar-ing of knowledge throughout the molecule life cycle across the whole organization and ii) a data processing and analysis system, ultimately enabling the com-parison of PQAs via the built-in

Figure 3: Genedata Expressionist enables automated MAM for bioprocess control. CQAs such as glycosylation are quantified and compared to reference values providing close to real-time assessment of the bioprocess.

CQA Residual t1Deamidation HC – N279

HC – N300HC – M255HC – N387

time

t1 t2 t4t3

Results

Bioreactor LC-MS

Glycosylation

DeamidationOxidation

t2 t3 t4Passed Passed Passed FailedPassed Passed Passed Failed

Passed Passed Passed FailedFailed Passed Passed Failed

Genedata Expressionist® fis part of the Genedata portfolio of advanced software solutions that serve the evolving needs of drug discovery, industrial biotechnology, and other life sciences.

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© 2015 Genedata AG. All rights reserved. Genedata Expressionist is a registered trademark of Genedata AG. All other product and service names mentioned are the trademarks of their respective companies.

Genedata Expressionist® is part of the Genedata portfolio of advanced software solutions that

serve the evolving needs of drug discovery, industrial biotechnology, and other life sciences.

© 2017 Genedata AG. All rights reserved. Genedata Expressionist is a registered trademark of Genedata AG. All other product and service names mentioned are the trademarks of their respective companies.

statistical analysis methods and subsequently, risk-based identification of CQAs.

Standardized and automated monitoring of CQAs. Automat-ed CQA monitoring was implemented with a MAM workflow building on previously acquired knowledge (Figure 2). This workflow ensured standardized monitoring throughout the bioprocess and manufacturing process, with the ability to fully automate the process without any human intervention.

Figure 3 illustrates how the abundance of glycopeptides was monitored at regular time intervals. While such automation provides benefits in terms of time and cost savings, these are amplified when used for process analytical technology (PAT); with a MAM providing close to real-time assessment of the drug product, managers can be alerted to potential issues and take corrective action. The speed and reproducibility provid-ed by Genedata Expressionist fulfilled the strict requirement

for rapid online analysis required for PAT.

Additionally, the results are available for statistical analysis for longitudi-nal studies and trend analysis. Data is automatically stored in a project-centric database and can easily be retrieved for multi-parametric analysis using the full complement of statistical analyses available in Genedata Expressionist.

Detecting putative CQAs. Monitoring of CQAs ensured product quality and enabled process control, yet the de-tection of unexpected quality issues remained to be addressed. Thanks to the flexible workflow concept of Genedata Expressionist, this imple-

mentation of MAM was amended to also allow a completely unbiased view of the complex data. This allowed the detection of even trace amounts of unexpected species and unknown contaminants.

LC-MS chromatograms of each sample were compared to a standard reference to detect differences (Figure 4). Intensity thresholds and qualification filters, e.g. on isotopic envelopes, were applied to reduce false positive identifications. This com-parative technique was greatly facilitated by refined data pro-cessing algorithms such as robust non-linear RT alignment.

Finally, these results were automatically integrated for quantitation and were reported with the routinely monitored CQAs. Additional analysis to identify these un-knowns was performed using the built-in applications of Genedata Expressionist. Ultimately, these unexpected results could identify novel and putative CQAs.

Figure 4: XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX

Figure 4: Detection of a new peak. Closer inspection of the peak at 28.6 min reveals an isotopically resolved charge cluster, confirming that this is a genuine peptide signal requiring subsequent identification.

Summary MAMs can generate significant operational savings by replacing traditional assays while at the same time enabling a true QbD approach for the development and production of biotherapeutics.

Genedata Expressionist offers a scalable enterprise software solution for the implementation of MAMs. From discovery to production, the software enables the end-to-end MAM process, from product attribute identification to automated CQA monitoring and detection of unknowns. It facilitates communication across organizations, harmonizes MAM methods across labs, enables complete automation, and supports deployment in regulated environments.