Feliza Mirasol

Protein aggregation is a particular challenge for biologic drug makers because this can occur at any point in the development or manufacturing process as well as during packaging and storage. Protein aggregates, typically impurities or molecular variants of the therapeutic protein, can change the therapeutic effect of the drug or cause protein degradation. This degradation can have serious implications for patient safety, product stability, potency, and biological activity, among other adverse consequences. Dealing with protein aggregation involves using analytical methods to detect and characterize the aggregates.

Fundamentally, protein aggregation occurs when proteins in their native state combine and aggregate or “clump” together in what is often a non-reversible process. This aggregation can occur either both inter- or intra-cellularly, caused by a change in the native structure of the protein. “The native structure is the most stable form of the protein, which essentially involves folding of the structure such that any hydrophobic regions are contained in the inner portion of the protein and hydrophilic on the exterior,” says Ashleigh Wake, business development director, Intertek Pharmaceutical Services, who explains that native structures are stabilized through a combination of disulfide bonds (formed between two cysteine residues) and non-covalent interactions, such as Van der Waals. “There are numerous ways in which these non-covalent interactions can be disturbed, which causes the protein to misfold or unfold, which ultimately leads to protein aggregations,” Wake states.

The formation of protein aggregates is attributed several main factors, including mutations in either DNA coding or other cellular proteins that are responsible for protein synthesis; variants in amino acid sequences or incorrect sequences that can occur when there is a problem with the translation of messenger RNA (mRNA); and aging of the cellular matrix. This reduces the ability of the matrix to refold protein or break down aggregated regions, according to Wake.

In addition, external factors play a role in protein aggregation, such as the protein being exposed to extremes of heat, pH, or oxidative conditions, says Wake.

Therapeutic proteins, however, require a specific structure for maximum functionality and activity, Jon S. Kauffman, PhD, vice-president, Biopharma Biologics, Eurofins Lancaster Laboratories interjects. “Aggregates can be introduced at any step of the process from production to dosing and can cause variability in potency, safety, and efficacy. Therefore, a thorough understanding of aggregation is critical to the success of biopharmaceutical drug candidates,” Kauffman says.

The mechanism by which aggregation increases immunogenicity is subject to considerable current research, but the inherent resultant particle size is certainly one factor that can be considered in this respect, Wake says.

Because protein therapeutics are administered to patients in the form of liquid injections as intravenous (IV), intramuscular (IM), or subcutaneous (SC), they often require high concentrations of proteins, thus making the formulation prone to aggregation. When a protein therapeutic aggregates in the blood stream, it has been shown to invoke immune response, which can result in the patient becoming immune to the monomer molecule, Kauffman elucidates. “The immune response is associated with adverse clinical effects, such as neutralizing the antibody, which inhibits efficacy of the products or causes cross-reactivity and neutralizes an endogenous protein counterpart. This may cause severe hypersensitivity response, such as anaphylaxis. Therefore, ensuring stability of the native molecule and minimizing the formation of higher molecular weight species is vital in reduction of immunogenicity of protein therapeutics,” Kauffman states.

Protein aggregation can potentially occur at almost every stage of a biopharmaceutical process—including development, formulation, and manufacturing—making it critical to have insights for guiding robust processing strategies, adds Lisa J. Graham, PhD, vice-president, Analytics Engineering, Seeq, a Seattle, WA-based software company that specializes in advanced analytics for process manufacturing data. These insights come from combining robust analytical instrument technology, process information with batch context, and advanced analytics to support collaboration, knowledge capture, and workflows, Graham notes.

Characterizing protein aggregates is as important as detecting them. Complete characterization of aggregates requires various pieces of critical information, Kauffman notes. It is key to know at what concentration protein aggregates form, the distribution of aggregate size and the change of aggregation percent and size of aggregates with time and concentration, Kauffman says.

“Particle sizing methods are increasingly being utilized to measure polydispersity and size distribution of the candidates,” Kauffman says. Dynamic light scattering (DLS), analytical size exclusion chromatography (SEC), sedimentation velocity analytical ultracentrifugation (SV–AUC), and transmission electron microscopy (TEM) are some of the analytical methods employed to detect and characterize protein aggregates.

DLS is a non-invasive method typically utilized to measure particle size and distribution. Because it is non-invasive, sample can be recovered at the end of the experiment. DLS can measure a broad range of sample sizes ranging from nanometers to micrometers and allows for fast data acquisition, reproducibility, and high sensitivity, Kauffman states, adding that DLS provides a good starting point to identify the presence of aggregation. The quantification of mass of individual aggregated species can be a limitation with DLS, however.

Analytical SEC is a form of high-performance liquid chromatography (HPLC) that is used to analyze the aggregation state of the sample. SEC uses differing Stokes’ radii to separate various species in a porous stationary phase column, Kauffman explains. “Smaller monomeric species are retained for a longer period in the stationary phase compared to larger aggregated molecules. Retention time of the sample can be compared with the retention of a known protein standard to calculate the molecular weight,” he states.

SEC is limited, however, by the assumption that the sample has the same conformation as the molecular standard and the sample is inert to the stationary phase, Kauffman continues. Furthermore, the effect of dilution while the sample is flowing through the column must be considered, he adds. Multiple angle light scattering (MALS) coupled with SEC (SEC–MALS) is a preferred analytical technique used to calculate the absolute molecular weight of the aggregate. SEC-MALS is effective in evaluating the effect of time and solvent size distribution of the aggregate, says Kauffman.

Meanwhile, the use of SV–AUC to characterize the size-distribution of aggregates has gained popularity in the last decade, Kauffman emphasizes. “Although, SV–AUC was developed in the early twentieth century, the lack of analytical solution to Lamm’s equation limited its application. Samples can be analyzed in their near native condition (buffer and pH) with no interaction with an analytical column like the other methods discussed. Additionally, the allowed range of concentration that can be tested is wider when compared to other methods,” Kauffman says.

He goes on to explain that TEM is a direct method to visualize the size, shape, curvature, and aggregation state of the protein formulation. The short wavelength of an electron allows for a significantly higher image resolution to be obtained using TEM as compared to other techniques. TEM can provide large size ranges from nanometers to millimeters, but it is limited in its scope of quantitatively evaluating the size distribution of the candidate. “Depending on the case, automated particle detection and size measuring codes need to be written and tested. Additionally, experiments are performed at very low concentration, which might not reflect the true state of the sample. Furthermore, negative staining and freezing also make the visualization condition far from the native condition,” says Kauffman.

Graham agrees that protein aggregation can be detected in several ways, whether visually observed in the solution, detected in the void-volume using SEC, and/or detected using DLS.

“In addition to characterizing the extent of aggregate formation, it is important to understand the conditions under which protein aggregation occurs. Having insight into the aggregation mechanisms and developing mitigating strategies are crucial to ensure the safety and clinical efficacy of the drug product,” she states.

For example, Graham points out, proteins are extremely sensitive to solution conditions and temperature, which are key process variables to consider when trying to gain insight from the aggregation data provided by analytical instruments. “From a process perspective, having an analytics strategy that looks at aggregation data, in context of the physical operation of the system, provides the opportunity to gain insight into the specific process conditions leading to aggregate formation. The occurrence of protein aggregation must be controlled throughout the manufacturing process during bioprocessing, with greater emphasis on purification, formulation, and fill/finish steps, to optimize yield and achieve target quality, while lowering production costs,” she adds.

Characterization of aggregates is potentially one of the key quality attributes to both measure and control, says Wake, who explains that any amount of aggregation, because it has the potential to increase immunogenicity, is therefore critical during quality control. Determining the amounts and sizes of aggregates formed, such that these can be compared to specification limits established during safety studies, can help ensure the continued efficacy and safety of the product, Wake emphasizes.

“More so during product registration, it is critical to establish that the levels of aggregates will remain within this specification through the product lifecycle. This is where formulation of the products plays a key role in stabilization, finding the optimal environment based on, for example, salt/excipient level or pH, to control aggregation,” Wake states.

The methods Wake describes for detecting soluble aggregates include analytical ultracentrifugation (AUC), asymmetrical fast field flow fractionation (FFF or AF4), sodium dodecyl sulfate electrophoresis, microscopy and turbidity in addition to SEC and DLS. “For evaluating secondary or tertiary structural changes, which can be complicit in aggregation this list also includes circular dichroism, Fourier-transform infrared spectroscopy, differential scanning calorimetry, and fluorescence,” she adds.

“For non-soluble aggregates, sub-visible particle or visible particle analysis techniques, such as light obscuration or flow imaging, can be applied. In any characterization, stability, or quality control program it is typical that orthogonal methods be applied to monitor aggregation considering both soluble and non-soluble forms. These methods often complement one another to ensure a comprehensive assessment,” Wake says.

New biologic modalities also pose further challenges to protein aggregate detection and characterization. Graham stresses that protein drug product formulation from varying biologic modalities often outpace monitoring technologies and analytical method development. She also points out that demand is increasing for multi-purpose facilities, not just multi-product facilities, to meet changing market demands for these newer modalities. “As a result, there is a need for an agile approach to continually adapt the evolving analytical methods in concert with the changing manufacturing processes. Coupling these components together into a robust data analytics environment makes it possible to capture the holistic understanding of the process environment necessary for an agile manufacturing strategy,” Graham states.

For example, Graham notes, “advanced analytics used to examine plant time-series data is foundational to developing process understanding, creating models, and developing control strategies to support the delivery of data-based decisions and process improvements. These analytical strategies can be used to create insights from the data supplied by instruments and analyzers to improve the manufacturing process.”

“The challenges for newer modalities are in many ways not that different from those for standard biologics and, where additional complexity does exist, it is more likely the result of the influence of the modality’s biochemistry,” chimes in Wake. “In the case of antibody drug conjugates (ADCs), for example, the inclusion of the linker or drug can increase hydrophobicity given the conjugated molecule a greater tendency to aggregate.”

In terms of detection and characterization, however, challenges with all aggregation analysis often involve ensuring that the system or systems are sensitive enough in terms of traditional limit of quantitation (LOQ) as well as size range, Wake continues. Other challenges include the notion that the analytics are not affected by the components of formulation, or the process of analysis is not inducing the aggregation that is being measured.

“SEC, for example, is perhaps the most widely used technique for assessment of aggregation with many benefits, such as ease of use and the ability, through use of external standards or MALS detection, to predict molecular weight of each observed species. Adversely the process of separation can induce aggregation, and its application is limited only to the assessment of soluble aggregates over a specified mass range, that is, large soluble aggregates can elute outside the size exclusion range and has limited resolution,” Wake says.

As the complexity of modalities increase, these challenges increase, such as, for example, in ensuring that the system can achieve the required LOQ or resolve aggregates of similar overall mass. “The best approach in all instances, therefore, is to include orthogonal assessment,” Wake emphasizes. “For example, adding an AUC assessment alongside SEC can help confirm that the process of separation is not causing aggregation and that the mass range being assessed is fully inclusive.”

A modality such as ADCs tend to have aggregation issues, notes Kauffman, who explains that these issues stem from the fact that some of the payloads employed in ADCs are highly hydrophobic and increase the potential for aggregation. “The analytical procedures need to be robust and specific enough to handle the more complex structure since ADCs are composed of monoclonal antibodies, a wide range of linkers, and payloads that are typically highly cytotoxic,” Kauffman states.

Meanwhile, there are a significant number of advanced therapy medicinal products (ATMPs) in the pipeline, Kauffman also stresses. Many of these ATMP candidates use a viral vector, such as an adeno-associated virus (AAV) or lentivirus to deliver RNA/DNA to its target. “By nature, the outer coat or capsid of these viruses is made up essentially of protein aggregates. Therefore, many of the analytical techniques discussed here are also used to study higher order structure of these gene therapy products,” Kauffman says.

With the growing challenges posed by new biologic modalities, there is a need for further advancement in analytical techniques or methods to improve aggregate detection and characterization. The ultimate aggregation tool, for example, would potentially allow highly sensitive and reproducible quantitative and qualitative assessment of soluble and insoluble aggregates in a single analysis without pre-treatment of the sample, that is, direct analysis of the drug substance or drug product, Wake highlights. This poses a considerable task, however, given the diversity of potential aggregates.

“There are, however, numerous new technologies under evaluation that aim to introduce additional orthogonal approaches, overcoming some limitations of current approaches and importantly improvements to existing technology,” Wake says. “Several new approaches have been reported in recent years, including differential mass analysis, which can be applied to low concentration proteins to provide data on mass as well as re-application of existing analytical technology, such as surface plasmon resonance and flow cytometry. These have not typically been associated with aggregation analysis.”

In terms of existing approaches, in the meantime, improvements in software for AUC and AF4 analysis continue to make these options much more viable for routine quality control applications, Wake adds.

“The techniques described [DLS, SEC, SV–AUC, TEM, etc.] can be quite complex and require a high degree of expertise,” Kauffman interjects. “Advances will need to be made to the software required to perform data acquisition and analysis so that they can be more widely used. Further, the software must be developed to be Part 11 (1) compliant should the technique be required for stability and/or release testing of clinical and commercial material.”

Graham adds that innovations in analytical instrument technology are needed to drive faster, more accurate measurement of protein aggregation. Advanced analytics are also needed that put data into the hands of process engineers and scientists. “These subject matter experts are invaluable for getting the insights needed at the pace required to keep up with the operational demands,” Graham states.

Furthermore, Graham makes the case that subject matter experts use experience based on what they have seen in the past and weigh that against what the data says to further apply critical knowledge and intuition. This balanced strategy creates a vital collaboration between human and machine, Graham emphasizes.

To achieve connectivity, innovations in advanced analytics need to address sevaral issues, including data connectivity and access, where time series and contextual data are typically stored in disparate sources. Access to all potential data sources must be provided while complying with data governance regulations and practices, Graham notes.

Advanced analytics must also address the need for iterative and agile processes. Production optimization is an iterative process, for example, so advanced analytics must be able to support fluidity in organizational priorities and context, rather than delivering a one-time snapshot of operational status. Further, advanced analytics must support organizational goals, such as providing easy-access (and enough) data, quickly generating insights, and enabling data-based decision making, though this does not always equal execution, Graham highlights. She adds that leadership and employee objectives must support a move to an analytics-centric culture.

Thus, while a variety of current analytical methods can be used for protein aggregation detection and characterization, changing market needs require innovative approaches and strategies to provide meaningful data and analysis for better quality control.

Guidance for Industry: Part 11, Electronic Records; Electronic Signatures—Scope and Application


Vol. 33, No. 9
September 2020
Pages: 35–39

When referring to this article, please cite is as F. Mirasol, “Risky Business: Assessing Protein Aggregation Grows Increasingly Challenging,” 

Articles

Current and newer biologic modalities pose increasingly complex challenges to the detection and characterization of protein aggregates.

When Assessing Protein Aggregation Grows Increasingly Challenging

Dissolution testing is an important aspect of drug development, allowing drug developers to determine the stability of a drug as well as providing 

This article originally appeared in the August 2020 issue of 

For solid oral dosage forms, dissolution testing is a requirement, necessary for detecting physical changes in an API as well as in the formulated product (1). Furthermore, including this analytical test early in the drug development lifecycle can allow drugmakers to optimize the drug’s release in a particular formulation.

With oral administration, drug absorption from a solid dosage form depends on the release of the active substance and its ability to be absorbed through the gastrointestinal (GI) tract of the patient. These two critical steps, solubilization and absorption, make 

 dissolution studies relevant predictors of a drug’s 

 dissolution tests for solid oral dosage forms (e.g., tablets, capsules) are thus used to assess lot-to-lot drug product quality, guide the development of new formulations, and ensure continuing product quality and performance after changes in formulation, manufacturing processes, manufacturing scale up, and manufacturing site (1).

A major issue in drug development is the need to enhance the level of drug in the patient and the availability of the drug to be absorbed by the patient’s body to have the intended therapeutic affect for which it was made. The challenge has always been that, without correct optimization of drug levels and solubility, a drug may not have sufficient therapeutic effect. Whereas, too high drug levels and solubility can conversely lead to adverse events or toxicity in the patient. These factors make dissolution testing crucial to the drug development process.

For most dosage forms to be therapeutically effective, APIs must be absorbed into a body’s circulatory system, normally through the GI tract as mentioned earlier, for the drug to be transported to the targeted site. The dissolution and absorption process, therefore, contribute to the drug’s bioavailability, and it is in understanding this multi-step process that a proper 

 dissolution testing method can be developed.

 conditions, including media (e.g., solvent) and hydrodynamics, can simulate 

 conditions. However, conditions that are optimal for quality control purposes may not be applicable for establishing 

 correlation (IVIVC) (relationship between 

 response). This may make it necessary to establish two dissolution tests, one to meet development objectives and another to meet regulatory demands (3).

Dissolution tests should be robust and reproducible and should have the ability to discern changes in product performance. Typically, the characteristics of a drug’s dosage form dictate what specific dissolution testing technique should be used; however, industry testing standards are given by the United States Pharmacopeia (USP) (2).

USP describes four apparatus setups for dissolution testing techniques:

Apparatus 1 comprises a vessel (can be covered), a motor, a metallic drive shaft, and a cylindrical basket.

Apparatus 2 comprises the assembly in Apparatus 1 but adds a paddle element (blade).

Apparatus 3 comprises a set of cylindrical glass vessels flat at the bottom, a set of glass reciprocating glass cylinders, inert fittings, nonsorbing, nonreacting screens, that cover the tops and bottoms of the glass cylinders, and a motor and drive assembly to move the cylinders.

Apparatus 4 comprises a reservoir and pump for dissolution medium, a flow-through cell, and water bath (2).

Dissolution testing has also historically been used for quality control, in R&D applications to detect the effects of critical variables in the manufacturing process, and for comparative 

Poorly soluble drugs are another challenge to dissolution testing, particularly when the dosage form is meant to be an immediate-release formulation. Challenges to testing the dissolution of poorly soluble drugs include developing an appropriate test method, validating the method, demonstrating that the method is appropriately discriminatory, and dealing with the potential of an 

With poorly soluble drugs, the extent of drug release tends to be low, and it is common that the dosage from cannot be fully dissolved. Additionally, the rate at which drug is released is too slow, which hinders attainment of meaningful data from dissolution testing. Some approaches to improving the dissolution of poorly soluble drugs have been studied (4).

To start, increasing the volume of the dissolution solution helps to optimize the maximum dissolvable dose. Other approaches include changing the dissolution medium to another solution/compound that increases the solubility of the compound or reducing dissolution sink requirements. In addition, nonaqueous solvents can be used if appropriate. Media that has been known to improve saturation solubility include biorelevant media, surfactants with mixed micelles, and certain nonaqueous media, in addition to water.

Dissolution data for regulatory consideration

Dissolution testing has increasingly become an important tool in regulatory decision-making over a drug, especially generic drugs. The testing can be used to waive requirements for 

 bioequivalence studies, for example, in addition to its role in determining formulation development, in monitoring manufacturing processes, and its use as a quality control test. It also plays a role in predicting the potential for dose-dumping in the case of a modified-release drug product if taken with alcoholic beverages. 

 dissolution testing can reduce the regulatory burden on FDA as well as alleviate the need for human studies that may be unnecessary for generic drug development. At the same time, the quality of the generic drug product would not be impacted (5).

FDA’s guidance (1) on dissolution testing discusses the Biopharmaceutics Classification System (BCS), which is based on API solubility and permeability. According to the guidance, highly permeable drugs are classified as Case 1 for high solubility and Case 2 for low solubility APIs. APIs that have low permeability are classified as Case 3 for high solubility and Case 4 for low solubility. The classification serves to provide a basis for setting up 

 dissolution specifications for the test and can also provide a basis for predicting 

The development of dissolution tests for a generic drug product must take into consideration the official methods and standards described by USP, while ensuring that the testing method is robust and can be reproduced in daily operations. The method should also be transferrable between laboratories. Finally, the test method must have the capability of distinguishing any changes in solubility behavior or drug properties that may affect the end product’s performance 

If there is an absence of an available USP method appropriate for the generic drug in question, a dissolution testing method can be developed following FDA guidelines or recommendations (6). In its guidance, FDA explains three categories under which dissolution specifications for generic products should be established:

A USP drug product dissolution test is available

A USP drug product dissolution test is not available, but a dissolution test for the reference listed new drug application (NDA) drug product is publicly available

A USP drug product dissolution test is not available, and a dissolution test for the reference-listed NDA drug product is not publicly available (1).

As shown, setting dissolution specifications for generic drugs depends on whether or not an official compendial test exists for the drug product and what dissolution test was employed for the reference drug.

Even if an FDA-recommended method is not sufficient or fitting for a drugmaker’s specific API/product, then the generic drugmaker can develop its own dissolution method (5). In the end, FDA requires comprehensive dissolution testing data in the drug’s application as part of the generic drug review process.

Guidance for Industry, Dissolution Testing of Immediate Release Solid Oral Dosage Forms

 (CDER, August 1997).
2. USP, General Chapter <711>, “

,” USP29–NF24 (US Pharmacopeial Convention, Rockville, 2011).
3. Lubrizol Life Science Health, “

 Dissolution Testing for Solid Oral Dosage Forms,” 

, March 9, 2020.
4. K. Gowthamarajan and S.K. Singh, 

 17 (3) 24–32 (2010).
5. O. Anand, et al., 


Vol. 44, No. 8
August 2020
Pages: 47–48

When referring to this article, please cite it as F. Mirasol, “Defining Drug Stability with Dissolution Testing,” 

Dissolution testing is an important aspect of drug development as it provides stability parameters and helps predict drug behavior in-vivo. 

Outlining Drug Stability and Solubility with Dissolution Testing

Determining product quality is a critical measure of a proposed biosimilar product. Appropriate analytical methods are needed to assess quality as well as for applying quality control (QC). One of the key challenges in developing or selecting an assay to determine biosimilar product quality is determining which critical quality attributes (CQAs) are the most important for a given stage of the drug development lifecycle, notes Stephen Shakespeare, product manager, Sartorius.

“For example, a binding assay may be more relevant during clone selection than a mechanism-of-action-bioassay, which would be more suited for the final stages of development,” Shakespeare says.

Titer is another critical process parameter, and to ensure final product quality, it is necessary to measure the product concentration throughout a bioreactor run, adds Laura Madia, sales and marketing manager at IDEX Health & Science.

Another point of consideration is the kind of information that is required from the assay. “Is it selective and specific for the product? Does it address the CQAs that have been identified from analysis of the innovator?” says Shakespeare, who points out that the use of orthogonal methods provides a host of information on the product that is critical for ensuring the quality.

“There are a number of challenges facing biopharma production, and their impact (overall production, development timelines, cost, etc.) can be more significant for companies developing biosimilars,” includes Madia. “One challenge in particular is the drive for improving process efficiencies. Biosimilars are considered to be cost-effective alternatives to expensive biologics. There is a significant pressure placed on reducing production costs through improved manufacturing processes to improve yields without introducing product variation that might require additional processing or testing.”

The tradeoffs between time and cost are particularly important when developing biosimilars given the limited development time, Madia continues, saying that “biosimilars do not benefit from the same patent protection as novel biologics so there is typically more pressure on prices immediately after approval.”

Another question to consider is what are the most effective assays currently used to test for biosimilar product quality? When assessing a biosimilar, Shakespeare explains, it is critical to take what he calls an orthogonal approach to looking at antibody fragment (Fab) binding and fragment crystallization (Fc) binding using a variety of techniques.

“In Fc functional assays, for example, antibody-dependent cellular cytotoxicity (ADCC) can be addressed in numerous ways using peripheral blood mononuclear cells (PBMCs) or natural killer (NK) cells isolated from blood. Meanwhile, reporter gene assays can be validated for submission to the regulators. The sensitivity of each of these methods provides key information on the quality of the product at different stages of development,” Shakespeare notes.

He adds that there is an array of methods, from enzyme-linked immunosorbent assay (ELISA) and flow cytometry to surface plasmon resonance (SPR), that can be used to determine Fab binding.

Another example of an orthogonal approach is the use of size exclusion and ion exchange analytical methods, which can show differences in aggregation/fragmentation and charge profile, respectively. These attributes can be important when assessing the stability and safety of a biosimilar, Shakespeare says.

Understanding the innovator biologic is also critical to understanding the CQAs of the biosimilar product, Shakespeare also notes. Understanding the innovator CQAs allows the biosimilar developer to determine the quality target product profile (QTPP) design space. Design-of-experiment software (e.g., Umetrics software, Sartorius) enables biomanufacturers to monitor the production process and track whether certain biosimilar CQAs are drifting, allowing them to respond accordingly.

“Being able to monitor different aspects of a biosimilar production in real-time, such as binding and function, enables you to control CQAs and minimize any potential downstream issues with delivering consistent quality product,” Shakespeare states.

There are situations where a process depends on a quick measurement to move forward, Madia remarks. “Measuring titer is not considered simple nor quick. Titer is often run on a high-performance liquid chromatography (HPLC) in the QC lab due to the high level of skill required for method development and day-to-day operation. It is not uncommon for upstream process development or manufacturing teams to wait 24 hours or longer to see the results of a HPLC titer analysis because they had to send it to a separate lab,” Madia explains. As a result, titer is often underutilized or batched for retrospective insights, rather than using titer for real-time decision making, Madia points out.

Since the manufacture of the first biosimilars, there have been many innovations in analytical techniques and practices. In recent years, for example, high throughput (HTP) flow cytometers (e.g., iQue screener, Sartorius) have enhanced the speed with which data can be generated, Shakespeare highlights. HTP flow cytometry, coupled with live cell imaging (e.g., Incucyte, Sartorius), enhances the breadth of information that is collected and allows for more informed decisions to be made faster, he explains.

Other recent analytical innovations include capillary electrophoresis techniques, which have replaced slab gel techniques, resulting in assays that have high resolution, are highly reproducible, and are applicable to a wide range of protein molecules—not just immunoglobulins and biosimilars. “The use of capillary isoelectric focusing (cIEF) and capillary electrophoresis sodium dodecyl sulfate (CE–SDS) techniques are now almost universally applied for CQA determination, stability studies, and lot release testing,” Shakespeare says.

Manufacturers, meanwhile, are continuing to implement liquid chromatography–mass spectrometry (LC–MS) techniques for investigating glycan structure, verifying sequences, analyzing intact mass, and analyzing post-translational modifications of the innovator and of biosimilar candidates, Shakespeare adds. “By introducing simple and affordable kits, manufacturers are getting greater instrument resolution, improvements in software processing and databases, and fast sample preparations,” he explains.

“In a similar vein, the ongoing reduction in particle size to < 3 µm in ultra-high-performance liquid chromatography (UHPLC) columns continues to enable reduced run times and higher throughput while maintaining peak resolution,” Shakespeare also adds.

Having an innovative new product that measures titer on demand is also a beneficial advancement, Madia adds. Drawing on experiences with the Tridex Analyzer (IDEX), Madia highlights how innovative technology can enable development and facilitate experimentation by providing trend data quickly and easily. With the trend data, it may be possible to determine product loss during the evaluation of filtration options or to monitor breakthrough with a new piece of equipment. “Ultimately, a full analysis will be required as part of the product acceptance, but by eliminating options early, it is only necessary to run a full analytical evaluation on the strongest candidates,” Madia says.

The most common application for antibody titer is in determining concentration in the bioreactor tank at the end of a cell culture run, Madia emphasizes. Once a process moves to production, current analytical tools are too large or complex to be co-located near the tank or in the manufacturing suite, she explains.

“During the crucial transition from upstream to downstream purification, manufacturing teams require the final titer data in order to load the purification columns. Once the tank is emptied and the filtration step is complete, production stops. Product is put in a holding tank while the team waits for results. Eliminating downtime while waiting for titer could shave hours or days and can also reduce the risk of moving product between areas. Using real-time titer to streamline this transition can make a real impact at manufacturing scale,” Madia says.

In May 2019, FDA proposed a draft guidance for the development of biosimilars (1) in which it outlines comparative analytical studies for determining quality criteria. The guidance itself recommends using orthogonal techniques and not relying on one analytical method when analyzing biosimilars, notes Shakespeare.

“For example, consider analyzing the charge profile of a sample using ion exchange on a UHPLC as well as by using cIEF on a capillary electrophoresis instrument. Both techniques will show the difference in charge profiles between the innovator and biosimilar, but when a manufacturer is gathering evidence of the biosimilarity of their molecule compared to the innovator, there is strength in using multiple techniques that incorporate different instruments,” Shakespeare says.

Meanwhile, BioAgilytix, a bioanalytical lab service provider, encourages biosimilar developers to engage with their chemistry, manufacturing, and controls (CMC) team because it is important to discuss the analytical characterization of both the biosimilar and innovator biologic and note any observed differences. The company has pointed out that differences observed in an anti-drug antibody (ADA) assay, for example, “may reflect previously undiscovered analytical differences between the biosimilar and the originator” (2). It is advisable that a discussion be held with regulatory authorities if there are unexplained differences between the biosimilar and the innovator biologic, and that these discussions occur prior to moving on to the next stage of biosimilar drug development.

BioAgilytix supports a single assay approach, such as an ADA assay or antigenic assay, to support biosimilar development. When developing an ADA assay, the company advises building it in a systematic, stepwise manner. This will support the build-up of knowledge needed to instill confidence in the assay’s ability to detect antibodies against the biosimilar and the innovator biologic. To that end, the focus should be on reducing the risk for potential variability and developing a meaningful interpretation of data derived from the assay (2).

Draft Guidance for Industry: Development of Therapeutic Protein Biosimilars: Comparative Analytical Assessment and Other Quality-Related Considerations

 (CDER, CBER, May 2019).
2. T. Lester, “Questions on Immunogenicity Testing for Biosimilars Answered: Part 1,” 


Vol. 33, No. 7
July 2020
Pages: 32–33, 47

When referring to this article, please cite it as F. Mirasol, “Analytical Assays Determine Biosimilar Product Quality,” 

The use of analytical assays is crucial for determining that biosimilar critical quality attributes remain on point.

Using Analytical Assays to Ensure Biosimilar Quality

Defining Drug Stability with Dissolution Testing

Bioanalytical studies are an important aspect in biologic drug development because data from these studies are needed to define the characteristics of potential new biologics. Bioanalyses data are also an important inclusion in regulatory filings, driving the need for outsourcing partners with in-depth bioanalytical experience and experience interacting with regulatory authorities. 

 spoke with Robert Kernstock, PhD, director, Immunoassay Laboratory Services at ICON, and Neelanjan Bose, PhD, Director of Bioanalytical Chemistry at Emery Pharma, both contract research organizations (CROs), about the need for bioanalytical testing programs and regulatory strategies for potential new biologics.

 Why is it so important to conduct bioanalytical studies during the development process of a new biological therapeutic?

 Bioanalytical studies, which are designed to provide estimates for concentration of drugs and biologics in pre-clinical and clinic studies of the therapeutic molecule or their metabolites, are critical for various aspects of human clinical pharmacology, studies related to bioavailability (BA)/bioequivalence (BE) evaluation, and some nonclinical studies requiring concentration information for pharmacokinetics, toxicokinetics, or biomarkers. Bioanalytical work serves to supplement pivotal studies and aid in the decision-making process for approval, safety, and/or labeling of a drug or biologic; in short, without proper bioanalytical data, the therapeutic product would not be approved. 

 Beyond the regulatory requirements for conducting bioanalytical studies, the scientific importance of the data that these assays generate is invaluable. Bioanalytical assays provide information on certain safety aspects of the therapeutic in determining the maximum tolerated dose. Pharmacokinetic (PK) scientists use the data to determine exposure, half-life, and other pharmacological parameters, which are used to guide decisions on how often and how much of a therapeutic should be given for efficacy without undue toxicity. 

	Bioanalytical assays extend beyond simply measuring drug concentrations over time but are also used to assess drug efficacy by way of pharmacodynamic (PD) endpoints (i.e., biomarkers). Biomarker assay results may provide early indicators of efficacy, or even safety issues. They can also be used to stratify patients to predict responders or non-responders.  Another key bioanalytical assay for biotherapeutics is the assessment of immunogenicity (both wanted and unwanted). For vaccine development, a positive immunogenicity result may be considered to be potential evidence that the vaccine is working as intended. Unwanted immunogenicity is much more complicated as the impact of anti-drug antibodies may influence the pharmacokinetics, efficacy, and safety, and has to be looked at down to the individual patient level.

 What type of data/information in particular do global regulatory authorities require from bioanalytical studies?

 For any regulated bioanalytical study to occur, a validated method is required. FDA has issued guidance documents detailing the scope of bioanalytical method validation required for PK/PD endpoints, but it is also important to consider other regional guidance documents (e.g., European Medicines Agency, Pharmaceuticals and Medical Devices Agency [Japan], Agência Nacional de Vigilância Sanitária [Anvisa] [Brazil], etc.) when conducting method validations. The general assessments for method validation consist of accuracy, precision, selectivity/specificity, linearity, robustness, and stability.  

	Depending on the type of assay, certain parameters may be added or removed to meet the assays’ context-of-use, and the analytical acceptance criteria may also vary. For immunogenicity assays, a statistical report or summary is required to justify your cut point(s). A well-described validation plan detailing the experiments and a priori acceptance criteria should be written and approved resulting in a bioanalytical report summarizing the experiments in tables, descriptions of deviations, and any pertinent conclusions. A quality statement from a quality assurance unit is typically included in the report for any regulated work. 

	Once the methods are validated, the sample analysis commences that follows bioanalytical plans and/or standard operating procedures (SOPS). The reported data typically contain information on subject (or animal) number, dose/treatment group, time point, and analytical result. A listing of assay performance characteristics, which include tables of assay control results, run summaries, and calibration curve results, are typically provided. Additional information, such as incurred sample reanalysis results and sample condition (e.g., hemolyzed) may also be included.

 On a broader perspective, FDA requires PK, toxicokinetic, or biomarker concentration evaluation through bioanalytical studies. It is critical that the data [are] generated via phase-appropriately validated methods (i.e., the methods are ‘fit-for-purpose’) and in many cases adhere to 

 58), Good Laboratory Practice for Nonclinical Laboratory Studies (1). These involve much experimentation, data curation and storage, quality review, personnel training, and generation of SOPs-all related documentation should be available for review by FDA, along with the bioanalytical report. 

	On a global scale, requirements and expectations around regulated bioanalysis generally follow the same thread as FDA, but with specific regional differences. Most jurisdictions have independent bioanalytical method validation guidance. 

 What types of approaches or strategies are best to plan out early on in the drug development process? 

 Bioanalytical studies are challenging to design and plan properly at the onset of the drug/biologic development process, as they involve samples from multiple pre-clinical species, tissue types, and human-derived samples with a diverse (and in most cases unknown) genetic and metabolic makeup. The bioanalytical methods need to be robust enough to work with the variability that comes with such a diverse set of samples. 

	It is thus important to anticipate these challenges early on while in the R&D phase, and develop sample preparation protocol(s) and method(s) that can work with such diverse types of samples, varying sample amounts, and be able to account for less-than-ideal sample handling during shipment and storage. It is also preferable to start the method validation process early that ensures that the data are reliable. While FDA guidance suggest that the level of validation should be appropriate for the intended purpose of the study, it is often helpful and cost-effective in the longer term to expand validation a bit beyond that so as to get better prepared for the later development process.  

 Early in clinical development, it is important to understand the context-of-use for your bioanalytical assays, what type of therapeutic you have, and how your clinical studies are going to evolve. For instance, if you think your lowest effective concentration of your therapeutic is 500 µg/mL (trough levels), then developing an immunogenicity assay that is tolerant to high levels of therapeutic would be a critical consideration early in development. Whether or not your Phase I study is going to be in patients or healthy volunteers is another important consideration. 

	Similarly, the disease-state biomarker assays may require different sensitivities than if it was in a normal population. Understanding the sensitivity requirements for your PK assay is also important. Intravenous administration of the therapeutic may require a less sensitive assay in your serum samples, whereas an ocular injection of the therapeutic will require a very sensitive serum PK assay to measure circulating drug levels. When conducting a preclinical toxicology study, the PK assay may not need a very low limit of quantitation since the therapeutic will be dosed at high(er) levels, and the immunogenicity assay may not have a confirmatory tier as an immune response is expected from a foreign protein. Perhaps you have a novel cell therapy, and a flow cytometer is used to collect ‘cellular kinetics’. This means special handling instructions to analyze the samples within the demonstrated stability window, or the use of additives in the collection tube to stabilize study samples.   

 Are there any ‘best practices’ procedures or steps you can recommend for beginning a bioanalytical study program for a new therapeutic?

 There are a few best practices to consider, including identifying an appropriate blank matrix pool, testing disease-state selectivity as early as possible, and having a good supply of excellent critical reagents identified and appropriately characterized. Addressing these considerations will go a long way to avoiding future analytical headaches. Understanding the mechanism of action of your drug and how it relates to the sample is a critical assessment. For instance, if the drug target is a soluble cytokine that is abundant in serum and plasma, don’t be surprised if your selectivity experiment fails. More importantly in that case, what matrix pool are you using for your standard curve? Is the pool stripped of the cytokine, or did you use a surrogate matrix that doesn’t contain the interfering molecule?  

 FDA’s 2018 guidance on bioanalytical method validation (2) is a great place to start. Additionally, while still in draft form, the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) M10 

 guidance (3) has been a decade-long collaborative initiative of analytical sciences and regulatory agencies around the globe; it is among the best resource currently available to plan for, and design bioanalytical studies.

 Why is it important, or even necessary, for some biopharma companies to partner with an outsourcing partner for the purpose of bioanalytic studies?

 Method development in bioanalytical studies is a black box to many, requiring intense training and somewhat intuitive understanding of how analytes behave in diverse biological matrices. It is important to note that, unlike standard analytical studies, bioanalyses involve highly complex and largely undefined biological matrices, with likely millions of compounds that can interfere with specific and accurate concentration evaluation. 

	The required knowledge and expertise to successfully navigate bioanalytical studies may not be acquired quickly in-house, particularly when the regulatory landscape around bioanalyses changes regularly. Additionally, most bioanalytical studies are moving towards mass spectrometry (MS)-based analyses, which involve instrumentation that is too expensive to acquire for many companies and require specialized training for use and data analyses. 

	Furthermore, most bioanalytical studies involve conducting the work under good laboratory practice (GLP), thus, the analytical laboratory must adhere to 21 

 58. This requires companies having a quality system in place, regular audit of the facility, maintaining documentation, training records, instrument qualification, and so on, all of which often becomes too cumbersome for many biopharma companies with limited operational budget. It is thus much simpler to partner with a CRO with expertise in bioanalyses, which already have an established quality system and the required experience in interaction and data presentation to FDA and other regulatory bodies.  

 Partnering with contract laboratories can be extremely beneficial, and there are a number of reasons for doing so. The capacity in your own lab may have been exceeded and the need to outsource work to a partner lab would be necessary. Your own lab may be lacking in certain analytical equipment or experience, and a contract lab would be able to provide that service and expertise. CROs are particularly useful to smaller biotechs as the CROs can provide valuable consulting services and an expanded scope of service offerings such that they can be a ‘one-stop-shop’ for all of your bioanalytical needs. CROs have a very deep understanding of bioanalysis based on the number and diversity of assays they have developed. This is reflected in their scientific expertise as well as their understanding of global regulatory practices, since they are more frequently audited by multiple regulatory agencies; these factors end up benefiting all of their clients.

 (Government Printing Office, Washington, DC). 
	2. FDA, 

Bioanalytical Method Validation Guidance for Industry


	Vol. 44, No. 6
	June 2020
	Pages: 54–58

	When referring to this article, please cite it as F. Mirasol, “The Importance of Partnering for Bioanalytical Studies,” 

Bioanalytical studies are a significant part of biologic drug development that may require partnering with bioanalysis experts.

Partnering for Bioanalytical Studies

Bioanalytical studies are an important aspect of biologic drug development that may necessitate partnering with bioanalysis experts.