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The development of a drug product is an arduous and intricate process. Besides ensuring the sterility and effectiveness of the final product, it should also be as free of particles as possible. In protein-based pharmaceuticals, aggregates may form over time and are mostly detrimental to product quality, as they can affect the efficacy, potency, clinical safety, and immunogenicity of the product.1-3 Protein aggregates are considered a type of particulate matter (PM), and it is important to minimize their occurrence, as well as to quantify the PM for ensuring the quality and safety of the drug products.
To establish a particle profile for a biopharmaceutical product, a comprehensive assessment of particles in pharmaceutical products is required. Instruments or equipment used for quantitative analysis of particulate matter, however, each have inherent measurement variabilities, and comparing particle results across different measurement technologies is not always straightforward, as different methods use different physical principles to count and size particles.
Currently, the two procedures employed within the pharmaceutical industry are light obscuration (LO) particle count test and microscopic membrane (MM) particle count test, which are specified in USP <787> Subvisible Particulate Matter in Therapeutic Protein Injections and <788> Particulate Matter in Injections. Both chapters address injections and are similar in regulatory requirements in relation to their nominal volumes. These test methods have their own shortcomings and may not fully address the demands of modern biopharmaceuticals.
In this article, flow imaging (FI) analysis will be discussed, particularly how it can address some of the challenges faced by the LO test method (since LO is the preferred method and MM is only applied when LO is deemed unsuitable or if the LO method does not meet the specified acceptance criteria).
FI Analysis and its advantages over LO
An FI method utilizes bright-field microscopy. The sample is drawn through a flow cell that is positioned in view of a microscopy system, which then captures consecutive bright-field images for analysis. Information, such as size, morphology, and image intensity, can then be derived from the automated analysis of the digital images captured. This analysis is beneficial in categorizing particles and provides enhanced understanding of the different particle types observed.
Despite both FI and LO being light-based techniques, the main advantage of FI over LO is that FI has a more sensitive detection threshold in terms of particle contrast with its matrix. A study was performed where polystyrene beads in matrices of varying refractive indices were measured by both FI and LO.4 Findings showed that FI can measure particles with low optical contrast to their matrix formulation more accurately than LO can. This is especially important for evaluating biopharmaceuticals because protein-based products have the tendency to aggregate, forming particles that are highly translucent.
In FI particles, liquid droplets and air bubbles that are captured in microscopic images can be classified according to morphology, image-intensity, and particle size. For instance, quantifiable morphological parameters can be used to differentiate particulate populations within the sample based on the degree of opaqueness or translucence of the particle. In order of increasing opaqueness, protein aggregates are highly translucent and allow a lot of light to pass through them, silicone oil has a dark outline with a bright center, while air bubbles are highly opaque.
Due to its sensitivity and enhanced ability to detect protein aggregates, FI can measure significantly more, and more types of, particles than LO can. This capability marks an advantage of FI over other particle characterization techniques, as it allows the determination of the relative proportions of different particle types, including silicone oil droplets and protein aggregates. Proper selection of flow cells and the right optics configurations in FI can further enhance the particulate detection process.
USP chapters <1787> and <1788> are supplementary chapters to <787> and <788> and suggest the use of flow imaging (FI), particularly for the purpose of particle characterization and product development,5,6 which constitutes a significant enhancement in particle sizing and enumeration. Additionally, the chapters provide guidance on the various analytical methods and to achieve orthogonal characterization of drug products, not only for monitoring purposes, but also during developmental phases and up to stability studies.
Currently, chapters <787> and <788> define the specification for quantifying subvisible particles equal to or greater than 10 µm and 25 µm using LO and MM testing, but no chapter has been established for other test methods such as FI. Nevertheless, FI can offer additional information on the particle types in a test sample, which can be used to supplement LO and MM test results.
With new therapeutic proteins emerging in the market, the types of subvisible particulate that may arise from these products can become more complicated and challenging to identify. Furthermore, these drug products undergo various stresses such as exposure to UV-light, heat, and agitation during the manufacturing and transportation processes, which can further encourage the generation of subvisible particles in therapeutic protein injections. Therefore, quantification and characterization of subvisible particulate is becoming increasingly important for ensuring the quality and safety of these drug products.
Even though the compendium elicits the LO and MM test methods for quantifying subvisible particles, their capabilities are not sufficient to detect certain types of particulates, as mentioned earlier. FI may be a complementary method to LO, as it is able to support in areas where LO is lacking, such as particle characterization. Characterization of particulate can allow particles to be classified into intrinsic (related to manufacturing process or containers), extrinsic (foreign to the process and product) or inherent (related to the formulation). Understanding the source of particulate allows for the application of a life cycle approach and enables continuous improvement. FI is more sensitive than LO when it comes to highly transparent particulate, and it can also detect a greater number of particles with detailed morphological properties. With the high-resolution images, FI can distinguish between different types of protein particles, which LO cannot do.
Understanding of the relevant particle count technologies available, method capabilities, and particle sources is critical in mitigating the risks associated with subvisible PM. To achieve accurate and reliable data on subvisible particle quantification, orthogonal techniques can be utilized to allow the assessment of a variety of characteristics of particles. Ultimately, adopting a testing strategy that uses various methods can help assure product quality through more accurate particle sizing and counting, as well as better characterization of the particulate profile.
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