Analytical Tools for Process and Product Characterization - Select the best approach to determine critical quality attributes. - BioPharm International

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Analytical Tools for Process and Product Characterization
Select the best approach to determine critical quality attributes.


BioPharm International
Volume 22, Issue 8

A QUANTITATIVE TOOL CHARACTERIZATION AGGREGATES

Size exclusion chromatography (SEC) is the standard method for quantifying levels of aggregation in protein products.21 However, aggregate characterization by SEC can perturb the delicate equilibrium of protein self-association because of resin–protein interactions and undesirable mobile-phase effects inherent in chromatographic-based separations.22,23 Sedimentation velocity–analytical ultracentrifugation (SV–AUC) can be applied in biopharmaceutical development as an orthogonal technique to SEC. SV–AUC is free from many limitations intrinsic to SEC but exhibits much lower precision, compromising its usefulness as a quantitative technique.24

The level of aggregation in a protein product is a CQA of the product, which must be monitored during development and controlled during manufacture. Accurate and precise quantitation of protein aggregation in biopharmaceutical products therefore meets a crucial business need. We have developed an improved SV–AUC methodology that enables enhanced precision and accuracy of protein aggregate measurements directly in product formulation buffer. The improved methodology allows successful implementation of quantitative SV–AUC in biopharmaceutical applications requiring high-precision aggregate measurements.

SV–AUC can be applied in protein biopharmaceutical development for many diverse characterization purposes.22,23,25–27 For example, SV–AUC is useful for process characterization, product structural characterization, product impurity profile determination, protein-receptor binding studies, comparability assessment, and evaluation of SEC method accuracy. Some of these applications permit qualitative assessment whereas others require quantitative results with a high degree of precision and accuracy. Unfortunately, the current precision of SV–AUC may preclude or limit its use in characterization studies that require quantitative aggregate measurements. The technique's use is particularly limited in cases of low aggregate levels (<1%), or when attempting to quantify subtle differences in aggregate levels.

The standard deviation of repeated protein aggregate measurements determined by SV–AUC is typically between 0.3 and 0.5% aggregate, but can be as high as 1% aggregate.24 Measurement precision is affected by common laboratory variations, including the instrument used, analyst technique, centerpiece quality, sample characteristics, and the data-fitting approach.24,27,28 Although the analyst has limited control over many factors, others can be deliberately controlled to improve the consistency of results. Two specific aspects of SV–AUC experiments are considered here: data analysis approaches for experiments conducted in non-ideal solutions containing excipients, and alignment of centerpieces. Proper control of these factors can dramatically improve both accuracy and precision.

Therapeutic protein formulations often contain excipients such as sugars or sugar alcohols. Typical angular velocities used during SV–AUC experiments (i.e., 40,000 to 60,000 rpm) cause excipient concentration gradients to form over experimentally relevant time scales. If excipient concentration gradients are not properly modeled during data analysis, the capability of SV–AUC to measure protein aggregation is dramatically impaired.28 For example, measured aggregate levels for a MAb declined from 3.0 to 0.7% after 10% sorbitol was added to the solution.29 Sophisticated data analysis approaches, including modeling excipient gradients, can mitigate the quantitation problems caused by the sedimentation of excipients.28,29 In this case, modeling the 10% sorbitol gradient substantially improved accuracy (2.3% aggregate measured).28 SV–AUC measurements of protein aggregate in product formulation buffer exhibit poor accuracy unless the effects of excipients are adequately taken into account during data analysis.

Poor analyst technique and inadequate experimental control can significantly increase variability in SV–AUC results.24,27 SV–AUC experimentation is complex and requires extensive analyst training compared to SEC experiments. One experimental aspect that depends on analyst technique is alignment of the sample-containing AUC cells to the center of rotation. Misalignment of the centerpieces can cause convective disturbances resulting in sample mixing and inaccurate results.24 To better control cell alignment to the center of rotation, we designed a custom alignment tool capable of controlling cell alignment within 0.25. The standard cell alignment approach relies on visual alignment of score marks on the rotor and cell assembly. This visual alignment technique can result in up to 0.5 misalignment from the center of rotation. When AUC cells were deliberately misaligned by 0.5, 1.0, 2.0, and 4.0, measured levels of aggregate increased linearly with increasing angle of misalignment. Slight cell misalignment (≤0.5) outside analyst control can yield variability as high as 1% aggregate. This variability is reduced to less than 0.5% aggregate by using an alignment tool.24


Table 1. Accuracy and precision of aggregate measurements by sedimentation velocity–analytical ultracentrifugation for a model monoclonal antibody under different solution and experimental conditions
The best way to improve the quantitative use of SV–AUC in biopharmaceutical development is to reduce the intrinsic variability of the technique. Many factors affect SV–AUC measurement variability; some are more difficult to control than others. For instance, inherent instrument differences (e.g., lamp intensity) and problematic sample characteristics (e.g., reversible self-association) may be unavoidable. But improved analyst technique (e.g., careful alignment of centerpieces) and advanced data analysis can dramatically increase the overall precision of aggregate measurements. Two methods to improve precision and accuracy were discussed: accounting for excipients in product formulation and alignment of cells to the center of rotation. Table 1 demonstrates how precision and accuracy can be improved by properly accounting for these effects. These methodology improvements can yield a 50% increase in precision and allow accurate measurements in product formulation.

SV–AUC is routinely applied in many aspects of biopharmaceutical development, including process and product characterization. It is used as an orthogonal complement to SEC, with important advantages but also some limitations. SV–AUC allows analysis in product formulation buffer and separates without a stationary phase. However, SV–AUC has limited throughput and exhibits poor method performance characteristics compared to SEC. The specific examples of SV–AUC method improvements highlighted here demonstrate that measurement accuracy and precision can be substantially improved, thus enabling SV–AUC to be a quantitatively meaningful characterization technique. Further, methodology improvements are critical to ensure the continued application of SV–AUC in the biopharmaceutical industry.


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