Oil-Immersion Flow Imaging Microscopy for Quantification and Morphological Characterization of Submicron Particles in Biopharmaceuticals

Three-Dimensional Homodyne Light Detection (3D-HLD) for High-Throughput Submicron Particle Analysis in (Highly Concentrated) Protein Biopharmaceuticals, Viral Vectors, and LNPs

During biopharmaceutical development, particle monitoring and characterization are crucial. Notably, particles can be impurities considered as critical quality attribute, or active pharmaceutical ingredient (e.g., viral vectors) or drug delivery system (e.g., lipid nanoparticles) itself. Three-dimensional homodyne light detection (3D-HLD) is a novel technique that can characterize particles in the ∼0.2 µm to 2.0 µm size range. We evaluated 3D-HLD for the analysis of high concentration protein formulations (up to 200 mg/mL), where formulation refractive index and background noise became limiting factors with increasing protein concentration. Sample viscosity however did not impact 3D-HLD results, in contrast to comparative analyses with NTA and MRPS. We also applied 3D-HLD in high-throughput screenings at high protein concentration or of lipid nanoparticle and viral vector formulations, where impurities were analyzed in the presence of a small (<0.2 µm) particulate active pharmaceutical ingredient. 3D-HLD turned out to be in good agreement with or a good complement to other state-of-the-art particle characterization techniques, including BMI, MRPS, and DLS. The main application of 3D-HLD is high-throughput particle analysis at low sample volume. Follow-up investigation of the optimized particle sizing approach and of detection settings could further improve the understanding of the method and potentially increase ease of operation.

Molecular investigation of the multi-phase photochemistry of Fe(III)-citrate in aqueous solution

Iron (Fe) is ubiquitous in nature and found as Fe^II or Fe^III in minerals or as dissolved ions Fe²⁺ or Fe³⁺ in aqueous systems. The interactions of soluble Fe have important implications for fresh water and marine biogeochemical cycles, which have impacts on global terrestrial and atmospheric environments. Upon dissolution of Fe^III into natural aquatic systems, organic carboxylic acids efficiently chelate Fe^III to form [Fe^III-carboxylate]²⁺ complexes that undergo a wide range of photochemistry-induced radical reactions. The chemical composition and photochemical transformations of these mixtures are largely unknown, making it challenging to estimate their environmental impact. To investigate the photochemical process of Fe^III-carboxylates at the molecular level, we conduct a comprehensive experimental study employing UV-visible spectroscopy, liquid chromatography coupled to photodiode array and high-resolution mass spectrometry detection, and oil immersion flow microscopy. In this study, aqueous solutions of Fe^III-citrate were photolyzed under 365 nm light in an experimental setup with an apparent quantum yield of (φ) ∼0.02, followed by chemical analyses of reacted mixtures withdrawn at increment time intervals of the experiment. The apparent photochemical reaction kinetics of Fe³⁺-citrates (aq) were expressed as two generalized consecutive reactions of with the experimental rate constants of j₁ ∼ 0.12 min^-1 and j₂ ∼ 0.05 min^-1, respectively. Molecular characterization results indicate that R and I consist of both water-soluble organic and Fe-organic species, while P compounds are a mixture of water-soluble and colloidal materials. The latter were identified as Fe-carbonaceous colloids formed at long photolysis times. The carbonaceous content of these colloids was identified as unsaturated organic species with low oxygen content and carbon with a reduced oxidation state, indicative of their plausible radical recombination mechanism under oxygen-deprived conditions typical for the extensively photolyzed mixtures. Based on the molecular characterization results, we discuss the comprehensive reaction mechanism of Fe^III-citrate photochemistry and report on the formation of previously unexplored colloidal reaction products, which may contribute to atmospheric and terrestrial light-absorbing materials in aquatic environments.

Utility of Three Flow Imaging Microscopy Instruments for Image Analysis in Evaluating four Types of Subvisible Particle in Biopharmaceuticals

Subvisible particles (SVPs) are a critical quality attribute of parenteral and ophthalmic products. United States Pharmacopeia recommends the characterizations of SVPs which are classified into intrinsic, extrinsic, and inherent particles. Flow imaging microscopy (FIM) is useful as an orthogonal method in both the quantification and classification of SVPs because FIM instruments provide particle images. In addition to the conventionally used FlowCam (Yokogawa Fluid Imaging Technologies) and Micro-Flow Imaging (Bio-Techne) instruments, the iSpect DIA-10 (Shimadzu) instrument has recently been released. The three instruments have similar detection principles but different optical settings and image processing, which may lead to different results of the quantification and classification of SVPs based on the information from particle images. The present study compares four types of SVP (protein aggregates, silicone oil droplets, and surrogates for solid free-fatty-acid particles, milled-lipid particles, and sprayed-lipid particles) to compare the results of size distributions and classification abilities obtained using morphological features and a deep-learning approach. Although the three FIM instruments were effective in classifying the four types of SVP through convolutional neural network analysis, there was no agreement on the size distribution for the same protein aggregate solution, suggesting that using the classifiers of the FIM instruments could result in different evaluations of SVPs in the field of biopharmaceuticals.

Particles in Biopharmaceutical Formulations, Part 2: An Update on Analytical Techniques and Applications for Therapeutic Proteins, Viruses, Vaccines and Cells

Particles in biopharmaceutical formulations remain a hot topic in drug product development. With new product classes emerging it is crucial to discriminate particulate active pharmaceutical ingredients from particulate impurities. Technical improvements, new analytical developments and emerging tools (e.g., machine learning tools) increase the amount of information generated for particles. For a proper interpretation and judgment of the generated data a thorough understanding of the measurement principle, suitable application fields and potential limitations and pitfalls is required. Our review provides a comprehensive overview of novel particle analysis techniques emerging in the last decade for particulate impurities in therapeutic protein formulations (protein-related, excipient-related and primary packaging material-related), as well as particulate biopharmaceutical formulations (virus particles, virus-like particles, lipid nanoparticles and cell-based medicinal products). In addition, we review the literature on applications, describe specific analytical approaches and illustrate advantages and drawbacks of currently available techniques for particulate biopharmaceutical formulations.

Towards quantification and differentiation of protein aggregates and silicone oil droplets in the low micrometer and submicrometer size range by using oil-immersion flow imaging microscopy and convolutional neural networks

Biopharmaceutical product characterization benefits from the quantification and differentiation of unwanted protein aggregates and silicone oil droplets to support risk assessment and control strategies as part of the development. Flow imaging microscopy is successfully applied to differentiate the two impurities in the size range larger than about 5 µm based on their morphological appearance. In our study we applied the combination of oil-immersion flow imaging microscopy and convolutional neural networks to extend the size range below 5 µm. It allowed to differentiate and quantify heat stressed therapeutic monoclonal antibody aggregates from artificially generated silicone oil droplets with misclassification rates of about 10% in the size range between 0.3 and 5 µm. By comparing the misclassifications across the tested size range, particles in the low submicron size range were particularly difficult to differentiate as their morphological appearance becomes very similar.

Plate Reader-Based Analytical Method for the Size Distribution of Submicron-Sized Protein Aggregates Using Three-Dimensional Homodyne Light Detection

The assessment of aggregates is essential in biopharmaceutical development. Although submicron-sized aggregates are considered to have a potential immunogenicity risk, analytical techniques are limited. In this study, we present a new analytical technique using three-dimensional homodyne light detection (3D-HLD). In this system, submicron-sized particles are quantified by combining the reflected light detection of each particle by high-speed 3D scan and then enhancing the amplitude of the reflected light using HLD. The particle concentrations and size distributions of human tetanus immune globulin (TIG) aggregates generated by stirring were measured using 3D-HLD. Both concentrations and distributions were comparable to those obtained via resonant mass measurement (RMM), a technique commonly used for submicron-sized particle measurement. Aiming at feasibility assessment of 3D-HLD for the high-through-put formulation development, 30 formulations of TIG and rituximab under agitation stress were analyzed by 3D-HLD. The results showed that 3D-HLD can automatically and simultaneously assess the aggregate concentrations and size distributions of at least 90 samples. This study demonstrates that 3D-HLD can be used for submicron-sized aggregate analysis as an orthogonal method to RMM and also as a screening tool during formulation development.