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Accelerating Biotherapeutic Analysis – Can you afford not to use your most valuable data?

Protein biotherapeutics have shown considerable promise in the treatment of a wide range of diseases and are one of the fastest growing segments in the pharmaceutical industry. Because of their high specificity and low immunogenicity as compared to small molecule drugs, protein therapeutics are revolutionizing the treatment of cancer, immune disorders, infections and other diseases that are challenging to combat with conventional medicine.

Monoclonal antibodies (mAbs) comprise a major class of protein biotherapeutics, having many product specific factors that are essential to the quality of the drug product. Biologics are significantly larger and more complex than their small molecule counterparts. This makes them more challenging to characterize and relate structure to function. Sophisticated technology and a highly controlled manufacturing process are required to assure Critical Quality Attributes (CQAs) are respected. Many biologics are produced using recombinant DNA technology, even minor differences in the cell lines or manufacturing process can create variations in the resulting protein.

Developers of these biologic drugs often seek to apply Quality by Design (QbD) strategies to gain productivity and efficiency as a biotherapeutic prospect progresses through its late-development characterization stages towards regulatory filing. This combination of biomolecular complexity and the drive for QbD-based processes has contributed to the development of multi-attribute methods (MAM), where several CQAs are measured and monitored within a single analytical assay. 1, 2

Multi-Attribute Methodology Transforms Biopharmaceutical Development

Liquid chromatography – mass spectrometry (LC-MS) has emerged as a preferred technology for MAM assays due to its ability to provide molecular-level data, with many vendors designing their use specifically for analysts in high-throughput, late-development laboratories. LC-MS assays are used for the detection and measurement of post-translational modifications of a protein and its sequence variants to develop a quality target drug profile and control strategy, including peptide maps that identify and quantify multiple CQAs simultaneously.

Companies have invested heavily in mass spectrometry in their analytical laboratories and are now challenged with how to effectively harness the data generated. Traditional LIMS and ELNs are not designed to manage large, data-rich LC-MS files. Critical information is left dormant. Despite enormous investment in biotherapeutics, organizations struggle to operationalize the significant benefits that LC-MS data can bring.

Improving efficiency with automation of both sample analysis and data processing are key for the application of MAM in the characterization of biotherapeutics. However, many laboratories experience bottlenecks in developing MAM approaches. While LC-MS methods themselves are becoming streamlined, sample preparation and data analysis are laborious and susceptible to inconsistency and human errors.

  • Manual sample preparation has limited throughput, low reproducibility of digestion profiles, and increased quantitation variation.
  • Complicated manual LC-MS data analysis requires a high level of expertise and creates barriers to high throughput due to limited analysis turnaround times and can introduce inconsistent results.
  • With a variety of software platforms supporting a diverse range of LC-MS systems, analysts face challenges in consistently documenting and auditing analysis results, which involve highly repetitive and time-consuming reporting.
  • For large sample sets with multiple molecule attributes that must be monitored, manual results inspection and quantitation is difficult, putting data integrity at risk.

Boldly Advancing Protein Characterization

Protein Metrics offers a new approach to automated MAM workflows, from sample preparation to data analysis and reports generation, providing higher throughput along with traceable, quality results for GxP compliance. Their BYOS™ software suite provides the foundation for LC-MS-based MAM optimized workflows, allowing for a faster turnaround time for MAM analyses with lower barriers to implementation, improved reproducibility of results, as well as auditability. LC-MS end to end workflow automation using the Byosphere™  enterprise platform accelerates multi-attribute monitoring capabilities for large sample sets that identify numerous attributes, provide relative quantitation, and generate configurable reports that support biotherapeutic development while embracing QbD principles.

BYOS brings together all your LC-MS data and analysis, regardless of MS hardware. If you are creating a data lake that contains both raw data as well as characterization results, all of that information can now be mined more effectively. Byosphere provides a seamless way to connect raw data, meta data, analysis, and results and gives organizations the possibility to mine this information by leveraging AI and ML tools to gain valuable insights and understand complex relationships within their data.

Conclusion

Multi-attribute methods for monitoring biotherapeutic CQAs offer much promise to streamline late-development characterization activities, but to achieve truly efficient productivity with LC-MS-based assays, laboratories need to consider the full workflow from sample preparation to data analysis. By incorporating automated sample preparation protocols as well as Byos software that enables high-throughput quantitation, the use of searchable product-specific watchlists for both exploratory and targeted monitoring, automated data processing, and automated report generation for auditable data review, greater productivity can be achieved with low barriers to implementation.

With a clear focus on protein characterization, Protein Metrics’ vendor-neutral software suite allows scientists to use data generated on analytical instruments like mass spectrometers to quickly identify and report protein sequences as well as any variations from the expected form. By working within an efficient environment designed around the laboratory workflows, your teams will experience a step change increase in the quality and quantity of their work to accelerate biotherapeutic innovation.

Why it Matters for You

Biopharmaceutical organizations have one of the most valuable tools available today for advancing their pipeline: mass spec characterization of their protein. However, most of them also struggle to maximize this valuable information. Adopting the principles of Quality by Design and multi-attribute methodology will accelerate biotherapeutic innovation in the following ways:

  • Improving efficiency with automation of both sample analysis and data processing are key for the application of MAM in the characterization of biotherapeutics.
  • Implementing BYOS software suite provides the foundation for LC-MS-based MAM optimized workflows, allowing for a faster turnaround time for MAM analyses with lower barriers to implementation, improved reproducibility of results, as well as auditability.
  • Automating end to end LC-MS workflows using the Byosphere enterprise platform accelerates multi-attribute monitoring capabilities for large sample sets that identify numerous attributes, provide relative quantitation, and generate configurable reports that support biotherapeutic development while embracing QbD principles.
  • Using Byosphere provides a seamless way to connect raw data, meta data, analysis, and results thereby allowing organizations to leverage AI and ML tools to gain valuable insights and understand complex relationships within their data.

About Astrix

Astrix partners with many of the industry leaders in the informatics space to offer state of the art solutions for all of your laboratory informatics needs. With over 25 years of industry proven experience, Astrix has the informatics specialists and business process analysis tools required to develop and implement the solution that works best for your enterprise. Our domain experts have helped hundreds of companies globally effectively navigate their digital transformation journey, connecting people, processes and systems to accelerate the advancement of science and medicine.

References

1U.S. Food and Drug Administration. Guidance for Industry: Q8(R2) Pharmaceutical Development. 2009,

2mAbs, Vol. 7, No. 5, October 2015