A Decade of Characterization

Over the past 10 years, the biopharmaceutical industry has placed increasing pressure on analytical laboratories, whose work is more important to the success of biotherapeutic products than ever before. Nearly concomitant with the appearance of BPI on the scene, the US Food and Drug Administration put forth its final report on the 21st century good manufacturing practice initiative, which in changing how regulators would review product applications, changed how companies must approach them (1). The guiding principles — risk management, science-based policies and standards, integrated quality systems, and international cooperation for strong public health protection — particularly emphasize the value of analysis in characterizing products and processes, identifying critical quality and process attributes (CQAs, CPAs) and critical process parameters (CPPs), setting specifications, and defining a design space within which unit operations can function with full confidence in their results. As a result, BPI has been in large part devoted to analytical strategies and methods related to quality assurance and control.

Production process development involves a large amount of analytical laboratory work, from cell line engineering and characterization to the optimization of culture media — and increasingly, leachables and extractables studies for single-use technology. Typical downstream process characterization and/or validation studies might measure membrane and resin lifetimes; in-process and buffer hold times; protein load limits for columns; pH and conductivity specifications; extractables and leachables; virus removal/inactivation; impurity removal; and small-molecule clearance.

This photo montage from BPI’s March 2009 cover illustrates the globe-spanning nature of modern biopharmaceutical development information infrastructure. ()

Bio/Analysis: One distinction worth addressing comes from editorial advisor and industry consultant Nadine Ritter: According to FDA guidance, she explains, analytical and bioanalytical methods are not the same thing (2). Bioanalytical methods are not used for elucidating quality parameters (e.g., identity, purity) of a biotech product; they’re for determining the quantity of a drug (or the presence of induced antibodies) in biological samples. So their applications in pharmacology, bioavailability, bioequivalence, pharmacokinetic, and toxicology studies are a very important but separate part of product development.

One major challenge is posed by regional differences in regulatory guidance and expectations, Ritter told BPI associate editor Leah Rosin early in 2008. “Even though it’s supposed to be harmonized, and we’re all using ICH (International Conference on Harmonisation of Technical Requirements for the Registration of Pharmaceuticals for Human Use), we see some regional differences in what is expected for certain types of CMC (chemistry, manufacturing, and controls).” She explained that the difficulty for new entrants into European markets, for example, is knowing what to expect from each country. “There are still subtle differences that can really drive some substantial CMC studies earlier in the process,” said Ritter. Analytical Strategy

Evolving approaches to biological product analysis have been been the main thrust of BPI’s long-standing relationship with the California Separation Science Society’s (CASSS) CMC Strategy Forum series — beginning with the first such paper from the forum committee in our second year (3).

Advancing analytical technology made quality by (QbD) design possible, but early in its implementation, the industry faced an absence of clear guidance that led to uncertainty in the fitness of product development plans, occasional misalignment of priorities and delays in regulatory review of filings, and inconsistent standards from product to product and sponsor to sponsor (4). Aggregates and host-cell impurities were of particular concern (5,6,7).

By 2008, large companies such as Amgen and Genentech were leading the way toward developing strategies that worked with the new paradigm (8, 9). “The analytical program for a given biotherapeutic has a life cycle analogous to that of a manufacturing process used to prepare material for clinical and commercial use” (9). That life cycle is divided into two distinct phases (8): a developmental phase (initial method development through clinical studies) and a validated phase (late-stage activities for commercial settings). New products that have been in development during the QbD period may have an advantage because they weren’t subject to major strategic changes partway through this life cycle (10).

An Analytical Discussion with Editorial Advisors

T. Shantha Raju is a research fellow in the biologics research division at the Janssen Pharmaceuticals Companies of Johnson and Johnson, 145 King of Prussia Road, Radnor, PA 19087; [email protected]. And consultant Adriana Manzi is managing director of Atheln, Inc., 6051 Scripps Street, San Diego, CA 92122; 1-858-554-0636, fax 1-858-405-4584; [email protected]. Both are members of BPI’s editorial advisory board.

BPI: How has quality by design (QbD) and process analytical technology (PAT) changed the way analytical laboratories work in the biopharmaceutical industry?

TSR: QbD/PAT has changed the industry quite significantly. We think of product characterization very early on, which leads us to develop critical quality attributes (CQAs) well before regulatory submission. That changed the people’s perception on posttranslational modifications, proteolysis, and other degradation mechanisms. As a result, we pay closer attention to developing state-of-the art analytical methods.

AM: I believe what has enabled more in-process testing in recent years is the ability to adapt assays to “high throughput,” reducing the time it takes to obtain results. The fact that technology allows for such adaptation of complex methods is what truly drove the changes. Coupling high-throughput testing with adequate sampling technology resulted in PAT. These facts made QbD a reality: If you understand your process very well and run it within a well defined design space, there is in turn less need to test at the final product level.

BPI: What newly introduced instruments and/or methods have had the most impact?

TSR: Mass spectrometry and liquid chromatography (e.g., LC–MS) have changed quite significantly. High-throughput assays are becoming the norm. Instrumentation has significantly improved in the biophysical arena as well as in bioassays. We used to use enzyme-linked immunosorbent assays (ELISAs) with ∼20% variability. Now that is no longer acceptable. Highly sensitive detection methods have been developed. As a result, new areas such as genomics, proteomics, glycomics, and so on are thriving.

AM: (See the “Advances” box, next page.)

BPI: What new product categories present the greatest challenge in QA/QC analytics — and how?

TSR: Antibody payloads are still a challenge to characterize. And PEG–protein conjugates (using polyethylene glycol) are complex to characterize. Cell therapy is another area where analyst are having difficult time to develop robust methods.

AM: I believe the struggle at this point in regulated analytical history is in defining the quality attributes for cell therapies and what affects them. This would enable process standardization and generalized release testing that, in addition to some specific assays for each product, could result in a situation similar to how we characterize a recombinant protein or MAb today.

BPI: And what do you think of as the most significant technological advancement(s) in analysis/bioanalysis over the past decade?

TSR: Multiplex assays are a significant advancement. And significant advancements have been made in the mass spectrometry field, especially in the use of MS for target identification and validation, isotope-exchange experiments, proteomics, and glycomics.

AM: Advances in analytical chemistry and MS are providing new insights into chemical and biological processes.

The FDA’s newly released process validation guidance both clarified and complicated the issue (11). It changes the language for discussing these things. For example, the traditional “4Q” qualification approach famously appears nowhere in the guidance (11, 12). But questions related to to that approach — and how it fits into QbD — have been at issue throughout BPI’s first 10 years (12,13,14,15).

Industry consultant Peter Watler explains the new paradigm this way (11): “The focus should be on what a study says, not about what it is called. And the FDA is clear on this. It has caused some in industry to divert validation efforts away from a scientific understanding to strict adherence of terminology and protocol. Fortunately the new guidance does away with that nonsense so industry can put resources into science and understanding rather than protocol and definitions.” Evolving Methods

Biomolecular analysis falls into three categori
es: chemical or biochemical, immunological, and biological assays (16). Biochemical and chemical assays account for 66–75% of those performed in product characterization, and they can take 400–800 work-hours to develop and validate. Bioassays require more time and make up about 15% of the total number of assays performed. Overall assay development and validation can cost around US$1.5 million — ∼$150,000 for three immunological assays, around $1 million for maybe a dozen chemical/biochemical assays, and nearly half a million for three bioassays.

In 10 years of BPI, authors have closely examined a number of analytical methods and described their application in a growing range of characterizations: from molecular structure (17,18,19,20,21,22,23,24) to protein concentration (25, 26) to contamination — especially of host-cell origin (27,28,29,30,31,32,33,34,35). And lot-release testing hasn’t gone by the wayside even as it has diminished in criticality (36, 37). With the advent of biosimilars, comparability studies have an increasingly important role to play (38). And as products move through development, these technologies are also important to technology transfer and scale-up efforts. Laboratory automation increases throughput and efficiencies in many analytical activities, but not without its own problems (39, 40).

Chromatography and electrophoretic techniques are the traditional “work horses” for measuring and monitoring protein quality (41). They are used in all stages of R&D including formulation development, comparability assessment, and commercial-product quality testing (release and stability). But motivation for the advancements we’ve seen and continue to see stems from the desire to improve method sensitivity, accuracy, and specificity and handle modern sample characteristics (e.g., high-concentration formulations) as well as adapt to higher throughput.

Bioassays serve a number of purposes including drug-candidate selection, product release and stability assessment, and comparability to support proposed process changes or biosimilarity. Because of their complexity, however, bioassay development is often problematic (42). Biological assays, especially potency assays needed for product release, are often poorly understood and even feared (43). For that reason, many companies initiate their development too late and without a clear idea of how each assay should be used and formatted. Late development can lead to costly clinical holds. Compounding these problems has been a lack of official regulatory guidance — although the US Pharmacopeia published related chapters in 2010.

Maintaining animals and cell lines for bioassay use can be difficult and expensive when kept in-house (44). So this is one type of work that may be best outsourced. The assays themselves can be costly to perform — involving specialized equipment and well-trained technicians — and lack the precision and robustness of other analytical methods (45). Most development scientists consider bioassays to be the most challenging analytical technique to develop and transfer, whether in-house or contracted out (46). Given the challenges, it is natural that alternative strategies to potency testing would be investigated. Binding and physicochemical assays have gained interest, but no regulatory pathways are yet clearly defined to allow such methods to replace cell-based testing, although they may be appropriate for augmenting it (47).

Advances in Mass Spectrometry

When I think of the past decade in analytical chemistry, I think about how advances in MS — not one instrument or one method, but multiple aspects of technology in combination with innovation — have had a great impact not only for researchers, but also for the pharma and biopharma sectors overall. The advent and development of soft ionization techniques enable extension of MS methods to large molecules and molecular complexes. Advances include

Biological applications of mass spectrometry have grown exponentially since the discovery of matrix-assisted laser-desorption ionization (MALDI) and electrospray ionization techniques. Single-cell analysis is gaining popularity in the MS field as a method for analyzing protein and peptide content in cells. The spatial resolution of MALDI MS imaging is largely limited by the laser-focal diameter and displacement of analytes during matrix deposition. Because of recent advancements in both laser optics and matrix deposition methods, spatial resolution of a single eukaryotic cell is now achievable.

MALDI imaging MS (IMS) can measure the distribution of hundreds of analytes at once and has great potential in the field of tissue-based research. An ambitious goal is to monitor the level and modification of all proteins and metabolites in a biological sample (e.g., plasma), and MS is poised to enable this dream in the next few years.

Adriana Manzi is managing director of Atheln, Inc., 6051 Scripps Street, San Diego, CA 92122; 1-858-554-0636, fax 1-858-405-4584;[email protected]. She is also a member of BPI’s editorial advisory board. Quality Assurance and Control

By now, it is generally accepted that quality cannot be left up to testing or inspecting a finished product. Instead, quality, safety, and effectiveness must be designed and built into the manufacturing process — and that can happen only with the right information at hand. A typical bioprocess involves a complicated matrix of input and output parameters, which can be interlinked with or independent of one another. Sources of variability include changes in raw materials, operators, facilities, and equipment, and it is difficult to understand all their possible permutations and effects on the quality of a final drug product.

Statistical design of experiments (DoE) methods are helping process engineers understand the effects of possible multidimensional combinations and interactions of various parameters on final drug quality (48). Application of a DoE strategy provides scientific understanding of the effects of multiple process parameters and raw material attributes on product CQAs and leads to establishment of a “design space” and manufacturing control strategy. Other “tools” have been introduced to bioprocessing — and consequently the analytical laboratories that support it — for risk management. Such approaches include failure modes and effects analysis (FMEA) and the hazard analysis and critical control points (HACCP) method originally developed in conjunction with the US space program (49).

A company’s quality control unit is part of its quality system, one of six manufacturing systems in a facility that are subject to inspection by the FDA: quality, facilities and equipment, materials, production, packaging and labeling, and laboratory controls (50). Over the past decade, the “systems-based” inspection approach was implemented in part to save time and resources in an overstretched regulatory agency. If a manufacturing system is in compliance, then all products dealt with as part of that system should be under the same degree of compliance, reflecting a “state of control” in that system. Documentation continues to play a vital role in making the case — especially for laboratory personnel who must be familiar with both GMPs and good laboratory practice (GLP), and in some cases, even good clinical practice (GCP) as well.

About the Author

Author Details
Cheryl Scott is cofounder and has been senior technical editor of BioProcess International since the first issue.

REFERENCES

1.) Pharmaceutical cGMPs for the 21st Century — A Risk-Based Approach: Final Report. US Food and Drug Administration: Rockville, MD, September 2004.

2.) Ritter, NM. 2011. Distinctions Between Analytical and Bioanalytical Test Methods. BioProcess Int. 9:80.

3.) Schenerman, MA. 2004. CMC Strategy Forum Report: Analysis and Structure Characterization of Monoclonal Antibodies. BioProcess Int. 2:42-52.

4.) Simmerman, H, and RP. Donnelly. 2005. Defining Your Product Profile and Maintaining Control Over It, Part 1: Session One of the WCBP CMC Strategy Forum, 19–20 July 2004. BioProcess Int. 3:32-40.

5.) Champion, K. 2005. Defining Your Product Profile and Maintaining Control Over It, Part 2: Challenges of Monitoring Host Cell Protein Impurities. BioProcess Int. 3:52-57.

6.) Boerner, R, and K. Clouse. 2005. Defining Your Product Profile and Maintaining Control Over It, Part 3: Product-Related Impurities. BioProcess Int. 3:50-56.

7.) Brorson, K, and J. Phillips. 2005. Defining Your Product Profile and Maintaining Control Over It, Part 4: Tackling Aggregates. BioProcess Int. 3:50-54.

8.) Apostol, I, and DN. Kelner. 2008. Managing the Analytical Lifecycle for Biotechnology Products: A Journey from Method Development to Validation, Part One. BioProcess Int. 6:12-19.

9.) Apostol, I, and DN. Kelner. 2008. Managing the Analytical Lifecycle for Biotechnology Products: A Journey from Method Development to Validation, Part Two. BioProcess Int. 6:12-19.

10.) Capen, R. 2007. Establishing Potency Specifications for Antigen Vaccines: Clinical Validation of Statistically Derived Release and Stability Specifications. BioProcess Int. 5:30-42.

11.) Scott, C. 2011. Quality By Design and the New Process Validation Guidance. BioProcess Int. 9:14-21.

12.) Winter, W. 2006. Analytical Instrument Qualification: Standardization on the 4Q Model. BioProcess Int. 4:46-50.

13.) Ritter, N. 2004. What Is Test Method Qualification? Proceedings of the WCBP CMC Strategy Forum, 24 July 2003. BioProcess Int. 2:32-46.

14.) Smith, P. 2007. Trends in Analytical Instrument Qualification. BioProcess Int. 5:30-38.

15.) Brown, DB. 2009. Assay Validation for Rapid Detection of Mycoplasma Contamination. BioProcess Int. 7:30-40.

16.) Scott, C. 2007. Analytical Methods for Biologics. BioProcess Int. 5:S35-S38.

17.) Chait, A, and B. Zaslavsky. 2003. Structural Signatures for Analysis and Characterization of Biological Products. BioProcess Int. 1:60-67.

18.) Defrancq, L. 2004. DSA-FACE: High-Throughput Analysis of the N-Glycans of NS0 Cell–Secreted Antibodies. BioProcess Int. 2:60-68. https://bioprocessintl.com/wp-content/uploads/bpi-content/0208ar07_78579a.pdf

19.) Jefferis, R. 2006. Criteria for Selection of IgG Isotype and Glycoform Antibody Therapeutics. BioProcess Int. 4:40-43.

20.) Rosenfeld, R. 2007. High-Throughput Glycoanalysis for Biopharmaceutical Development and Manufacturing. BioProcess Int. 5:38-47.

21.) Bierau, H. 2008. Higher-Order Structure Comparison of Proteins Derived from Different Clones or Processes. BioProcess Int. 6:52-59.

22.) Que, AH. 2010. Sequence Variant Analysis Using Peptide Mapping By LC-MS/MS. BioProcess Int. 8:52-60.

23.) Wei, Z. 2011. The Role of Higher-Order Structure in Defining Biopharmaceutical Quality. BioProcess Int. 9:58-66.

24.) Michels, DA, O Salas-Solano, and C. Felten. 2011. Imaged Capillary Isoelectric Focusing for Charge-Variant Analysis of Biopharmaceuticals. BioProcess Int. 9:48-54.

25.) Lundblad, RL, and NC. Price. 2004. Protein Concentration Determination: The Achilles Heel of GMP?. BioProcess Int. 2:38-47.

26.) Rau, TD, and RR. Balcarcel. 2006. A 96-Well Plate Assay for Relative Monoclonal Antibody Titers. BioProcess Int. 4:42-48.

27.) Cronholm, K, and M. Johansson. 2007. Determining Endotoxin Levels and Inhibition and Enhancement of the Endotoxin Reaction. BioProcess Int. 5:78-83.

28.) Wolter, T, and A. Richter. 2005. Assays for Controlling Host-Cell Impurities in Biopharmaceuticals. BioProcess Int. 2:40-46.

29.) Venable, D. 2007. High-Throughput and Quantitative Detection of Residual NS0 and CHO Host-Cell Genomic DNA. BioProcess Int. 4:56-61.

30.) Mehta, S, and JT. Keer. 2007. Performance Characteristics of Host-Cell DNA Quantification Methods. BioProcess Int. 4:44-58.

31.) Wang, X. 2010. Improved HCP Quantitation By Minimizing Antibody Cross-Reactivity to Target Proteins. BioProcess Int. 8:18-24.

32.) Schwertner, D, and M. Kirchner. 2010. Are Generic HCP Assays Outdated? BioProcess Int. 8:56-62.

33.) Savino, E. 2011. Development of an In-House, Process-Specific ELISA for Detecting HCP in a Therapeutic Antibody, Part 1. BioProcess Int. 9:38-47.

34.) Savino, E. 2011. Development of an In-House, Process-Specific ELISA for Detecting HCP in a Therapeutic Antibody, Part 2. BioProcess Int. 9:68-75.

35.) Liu, N. 2012. Host Cellular Protein Quantification. BioProcess Int. 10:44-50.

36.) Gombold, J. 2006. Lot Release and Characterization Testing of Live-Virus–Based Vaccines and Gene Therapy Products, Part 1. BioProcess Int. 4:46-54.

37.) Gombold, J. 2006. Lot Release and Characterization Testing of Live-Virus–Based Vaccines and Gene Therapy Products, Part 2. BioProcess Int. 4:56-65.

38.) Towns, J, and K. Webber. 2008. Demonstrating Comparability for Well-Characterized Biotechnology Products. BioProcess Int. 6:32-43.

39.) Scott, C, and LD. McLeod. 2010. The Time Has Come for Automation in Bioprocessing. BioProcess Int. 8:16-25.

40.) Albert, KJ. 2009. Automated Liquid Handlers As Sources of Error. BioProcess Int. 7:56-60.

41.) Krishnamurthy, R. 2008. Emerging Analytical Technologies for Biotherapeutics Development. BioProcess Int. 6:32-42.

42.) Robinson, CJ, LE Little, and HJ. Wallny. 2008. Bioassay Survey 2006–2007. BioProcess Int. 6:38-48.

43.) Robinson, CJ. 2006. A Survey of Bioassays in the Biopharmaceutical Industry. BioProcess Int. 4:24-36.

44.) Rieder, N. 2010. The Roles of Bioactivity Assays in Lot Release and Stability Testing. BioProcess Int. 8:33-42.

45.) Das, RG, and CJ. Robinson. 2008. Assessing Nonparallelism in Bioassays. BioProcess Int. 6:36-56.

46.) Menendez, AT. 2009. Accelerating Bioassay Transfer in a GMP Environment. BioProcess Int. 7:26-33.

47.) Shivhare, M, and G. McCreath. 2010. Practical Considerations for DoE Implementation in Quality By Design. BioProcess Int. 8:22-30.

48.) Vega-Mercado, H. 2003. HACCP: A Process Validation Tool for Ensuring Quality of Biotech and Pharmaceutical Products. BioProcess Int. 1:50-57.

49.) Montgomery, SA. 2006. Operations and Quality Systems: Building in Success. BioProcess Int. 4:S58-S71.