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European Biopharmaceutical Review

It’s a Small World

The quantification of subvisible particles in injectable therapeutic protein products has been established in the US and European Pharmacopeia under Chapters 788 and 2.9.19, respectively. In accordance with these rules and procedures, limits have been made for subvisible particulate content that were calculated based on the risk of >10μm and >25μm particles blocking certain percentages of blood vessels in the lungs following intravascular infusion. This has marked a shift in the industry towards more convenient administrations, such as subcutaneous and intramuscular injections.

This move has also opened a discussion on the relevance of the pharmacopeia chapters, specifically those relating to protein therapeutics. Over the past decade, a substantial amount of work has been published that investigates the propensity of proteins to aggregate and form subvisible particulates (1-3), and the potential risk of immunogenicity due to presence of protein aggregates and subvisible protein particles in therapeutic protein products (4-6).

Regulatory Guidance


Concurrently, the FDA has become increasingly concerned with the safety and efficacy of therapeutic protein products as, in the past, subvisible particles between 0.1-10μm were not being actively monitored (7,8). As a result, a new US Pharmacopeia (USP) monograph, Chapter 787: Subvisible particulate matter in therapeutic protein injection, was drafted and became effective in 2014. In this monograph, in addition to allowing smaller particle size detection reporting, several improvements – such as reductions in required testing volumes – were implemented. For example, while the previous Chapter 788 required a minimum volume of 25mL to complete a test, the new chapter allows for a volume as low as 1mL. This small volume method not only saves costs by requiring less product, but also allows for the determination of vialto- vial or syringe-to-syringe variability of particle counts. Furthermore, although the reporting of >10μm and >25μm size ranges is still required, the establishment of product specific-limits is permitted.

As well as USP Chapter 787, general information Chapter 1787: Measurement of subvisible particulate matter in therapeutic protein injections, was drafted. This chapter recommends the collection of 2-10μm (>2μm and >5μm) subvisible particle concentrations, and gives guidance on orthogonal methods to characterise subvisible particles as inherent intrinsic or extrinsic; it specifically spells out the need to distinguish silicone oil from other proteinaceous, inherent or intrinsic particles.

The FDA has also approved Guidance for Industry on the Immunogenicity Assessment for Therapeutic Protein Products that states: “[assessment] should be made of the range and levels of subvisible particles (2-10 microns) present in therapeutic protein products initially and over the course of shelflife… As more methods become available, sponsors should strive to characterize particles in smaller (0.1-2 microns) size ranges”. Meanwhile, the EMA’s Guideline on Development, Production, Characterisation and Specifications for Monoclonal Antibodies and Related Products states: “[the] formation of aggregates, sub-visible and visible particulates in the drug product is important, and should be investigated and closely monitored on batch release and during stability studies. In addition to the pharmacopoeial test for particulate matter, other orthogonal analytical methods may be necessary to determine levels and nature of particles.”

As more regulatory agencies start to request extra particle detection, specifically below 10 micron, it becomes imperative for companies to fully understand the orthogonal methods available and their limitations. As discussed in Chapter 1787, particles in the >10μm size range can be highly variable due to other inherent or intrinsic components, such as silicone oil. Therefore, combining orthogonal techniques to help identify and characterise these particles becomes essential for data analysis and interpretation.

Dynamic Light Scattering (DLS)

DLS is a non-destructive qualitative method to determine size distribution of particles in the submicron range of 0.001- 1μm. The method is based on Brownian motion of particles in solution and the Rayleigh light scattering relationship of scattering intensity being proportional to hydrodynamic radius, to the sixth power. Due to the Rayleigh relationship, DLS can be very sensitive to the presence of larger particles such as dust or micronsize protein aggregates/particulates. For this reason, sample preparation is of utmost importance when performing DLS analysis. In addition, as the diffusion of a particle is a function of the viscosity of the solution, knowing the exact viscosity of samples is important for calculating the resulting hydrodynamic radii.

Resonant Mass Measurement (RMM)


An RMM system detects particle buoyancy mass by changes in frequency of a resonator as individual particles pass through. This technique is a true orthogonal approach to microfl ow imaging (MFI) and LO in the 1-5μm size range, since it does not rely on refractive index changes or blockage of light, but instead on the volume of solution displaced by individual particles. Such a system is recommended for detection of particles in the 0.5-5μm size range when solutions have silicone oil droplets present – for example, prefi lled syringe or device combinations. However, MFI is unable to distinguish between silicone oil and other inherent particles below 5 microns. The combination of RMM and MFI allows for the full characterisation of particles in the 1-10μm size range, which has been of interest lately.

Light Obscuration

LO is the most widely used subvisible particle assay in the pharmaceutical industry, and is the preferred compendial method of the US, European and Japanese Pharmacopeia. It detects particles based on blockage of light by individual particles passing through a light sensing zone, and gives details of size and counts, assuming spherical shape of particles. The disadvantage of LO is that it provides the least amount of information compared to flow imaging and RMM methods: if an increase in particle counts is observed, it is not known whether that rise is a result of extraneous matter, protein particulation, microbubbles, or silicone oil. Performing orthogonal methods alongside LO has become the industry standard to help characterise subvisible particles present in parenteral products.

Micro-Flow Imaging

MFI is a more sensitive orthogonal method to LO that detects particles using Bright-field images captured as a solution is passed through a flow cell. This detection method relies on refractive index changes rather than blockage of light, which makes it more sensitive to translucent particles, such as protein. The images collected are then used by the software to create an extensive database of information – including size, shape and transparency – on the particles detected, which can be used for wider classification and differentiation.

The ability of MFI to distinguish silicone oil from proteinaceous or extrinsic particles is a significant advantage of this technique. Furthermore, the visual inspection of images can also provide important information on the types of protein particles being formed – including density, fibrillar versus compact, complexes of silicone oil and protein. MFI has become a valuable technique routinely used to complement compendial methods for subvisible particle detection.

Raman Microscopy

Raman microscopy is a powerful tool used to help identify subvisible and visible particles. Unlike Fourier transform infrared spectroscopy, this method is not sensitive to the presence of water in samples and allows for aqueous solutions to be analysed. An automated Raman microscopy system enables faster characterisation and identification of particles in solution.

Many inherent particles within a parental can have similar morphologies, potentially causing issues in classification with methods such as MFI. For example, excipients such as polysorbate can degrade and form insoluble particles that have similar shapes and transparencies to proteinaceous particles. However, using an automated system, it is possible to chemically identify subvisible particles down to 3-5μm in size, allowing for differentiation of subvisible particles with similar morphologies. In addition, the ability to perform spectral mapping across an individual particle allows for proper identification of particles that are complexes of material such as silicone oil and protein, or silicone oil and surfactant. Although automated Raman microscopy is not as high throughput as flow imaging techniques, it has repeatedly proven to be an invaluable method in answering the ‘what is it’ question that arises continuously in development, manufacturing and stability programmes.

Combining Orthogonal Methods


Compared to other particle analysis methods, the LO technique does not generate particle images. Instead, MFI systems collect the images of particles with which multiple morphological parameters can be determined. Due to the highly spherical nature and known refractive index of silicone oil droplets, MFI is a very useful tool to classify silicone oil from proteinaceous or other inherent particles (9). As a result of its unique classifi cation, it is possible to determine silicone oil content introduced to products by various sources such as syringes, devices or stoppers. The classification of this oil is also benefi cial to help eliminate the variability of oil content introduced from total particle counts, allowing for more accurate tracking of protein particles over shelflife or during forced degradation.

Thanks to the resolution, classifi cation of particles on morphological parameters determined from images can only be performed for particles >5μm. RMM is capable of detecting smaller particles ranging from 30nm-5μm, can classify particles based on their density, and provide a true orthogonal analysis to MFI in the 1-5μm range. The density of silicone oil is less than water and protein, which enables it to be distinguished from other particles by RMM. Thus, a combination of RMM and MFI allows for the complete classification of silicone oil versus protein, or other inherent particles in the 1-10μm range where the highest variability of silicone oil droplets tends to occur.

While the classification of silicone oil from protein is fairly straightforward with images analysis and buoyancy measurements, the quantification of proteinaceous particles from other inherent particles is more difficult. Many excipients – such as polysorbate – can form particles with similar image properties to that of proteinaceous particles. Automated Raman microscopy can provide image analysis, as well as Raman spectroscopy, of particles >3- 5μm in size. This method can establish a positive chemical identity of subvisible and visible particles. As a result, combining orthogonal techniques such as MFI, RMM and Raman microscopy is recommended to accurately quantify, characterise and identify subvisible particles.

References

1. Barnard JG, Babcock K and Carpenter JF, Characterization and quantitation of aggregates and particles in interferon-products: Potential links between product quality attributes and immunogenicity, J Pharm Sci 102: pp915-928, 2013
2. Simler BR, Hui GD, Dahl JE and Perez-Ramirez B, Mechanistic complexity of subvisible particle formation: Links to protein aggregation are highly specific, J Pharm Sci 101: pp4,140-4,154, 2012
3. Singh SK et al, An industry perspective on the monitoring of subvisible particles as a quality attribute for protein therapeutics, J Pharm Sci 99: pp3,302-3,321, 2010
4. Filipe V et al, Immunogenicity of different stressed IgG monoclonal antibody formulations in immune tolerant transgenic mice, mAbs 4: pp740-752, 2012
5. Fradkin AH, Carpenter JF and Randolph TW, Immunogenicity of aggregates of recombinant human growth hormone in mouse models, J Pharm Sci 98: pp3,247- 3,264, 2009
6. Fradkin AH, Carpenter JF and Randolph TW, Glass particles as an adjuvant: A model for adverse immunogenicity of therapeutic proteins, J Pharm Sci 100: pp4,953-4,964, 2011
7. Carpenter JF et al, Overlooking subvisible particles in therapeutic protein products: Gaps that may compromise product quality, J Pharm Sci 98: pp1,201-1,205, 2009
8. Rosenberg AS, Effects of protein aggregates: An immunologic perspective, The APPS Journal 8: e501-507, 2006
9. Strehl R et al, Discrimination between silicone oil droplets and protein aggregates in biopharmaceuticals: A novel multiparametric image filter for subvisible particles in microfl ow imaging analysis, Pharm Res 29: pp594-602, 2012


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Amber Fradkin is Associate Director at KBI Biopharma, where she manages the Particle Characterisation Core that specialises in analytical methods for quantifying, characterising and identifying submicron, subvisible and visible particles. Previously, she worked at Amgen Inc as a scientist supporting the biophysical characterisation of protein products. Amber received her PhD in Chemical Engineering, as well as her Masters and Bachelors of Science, from the University of Colorado, US.
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