Quantitative Evaluation of Insoluble Particulate Matters in Therapeutic Protein Injections Using Light Obscuration and Flow Imaging Methods

Examination of Particulate Contamination in Parenteral Injections and Infusions Following Fluid Withdrawal Utilizing Conventional Needles and Filter Needles: Assessment of Compliance and Comparative Analysis

Particulate contamination, the unintentional presence of particles in parenteral fluids, is associated with potential risks such as phlebitis and thrombophlebitis. Recent guidelines recommend the use of filter needles when withdrawing parenteral fluid from vials with a rubber stopper. However, the literature is limited and lacks clarity regarding the advantages of filter needles over conventional needles. The aim of this study was to assess the compliance of parenteral fluids regarding particulate contamination after withdrawing fluid using both conventional needles and filter needles, following the guidelines of European Pharmacopoeia (Ph. Eur.) and United States Pharmacopoeia (USP). Visible particles were counted through visual inspection and sub-visible particles were quantified utilizing the light obscuration particle count test. Particle counts for both types of needles were compared to Ph. Eur. and USP standards and differences in particle contamination were assessed using a Mann-Whitney U test. Both types of needles demonstrated compliance with Ph. Eur. and USP standards regarding particulate contamination of visible and sub-visible particles. However, filter needles exhibited a significantly higher particle count for particles with a size of ≥25 µm compared to conventional needles (p = 0.0029). In conclusion, both types of needles demonstrate suitability for aspirating fluid from vials featuring rubber stoppers regarding particulate contamination. Nevertheless, non-filter needles are preferred for withdrawing fluid from vials with a rubber stopper over filter needles due to their lower cost.

Evaluation of the In-Use Stability of Monoclonal Antibody IV Admixtures Prepared from Drug Products Containing Polysorbate 20 Degraded by Host-Cell Lipases

Host-cell lipases can be present in monoclonal antibody drug products and can degrade polysorbates present in the formulations as stabilizers. We hypothesized that the in-use stability of the IV admixture prepared from such a drug product might be impacted by decreasing levels of polysorbate 20. Host-cell lipase activity has, in fact, been observed during development of one of our therapeutic monoclonal antibody drug products. Throughout the course of the product shelf life, polysorbate 20 levels decreased but no other quality attributes of the drug product were impacted. An experimental approach was developed to simulate how the prepared IV admixture in-use stability is affected as polysorbate 20 concentration in the drug product decreased over the shelf life, and from that a minimum level of polysorbate 20 required in the drug product was determined to estimate the in-use stability of the IV admixture as the polysorbate 20 in the drug product degrades. The results indicate that although the observed degradation of polysorbate 20 does not affect quality attributes of this drug product, in-use stability of the IV admixture as a function of polysorbate degradation can be impacted and should be assessed to ensure sufficient quality.

Optimization of Flow Imaging Microscopy Setting Using Spherical Beads with Optical Properties Similar to Those of Biopharmaceuticals

Flow imaging microscopy (FIM) is widely used to characterize biopharmaceutical subvisible particles (SVPs). The segmentation threshold, which defines the boundary between the particle and the background based on pixel intensity, should be properly set for accurate SVP quantification. However, segmentation thresholds are often subjectively and empirically set, potentially leading to variations in measurements across instruments and operators. In the present study, we developed an objective method to optimize the FIM segmentation threshold using poly(methyl methacrylate) (PMMA) beads with a refractive index similar to that of biomolecules. Among several candidate particles that were evaluated, 2.5-µm PMMA beads were the most reliable in size and number, suggesting that the PMMA bead size analyzed by FIM could objectively be used to determine the segmentation threshold for SVP measurements. The PMMA bead concentrations measured by FIM were highly consistent with the indicative concentrations, whereas the PMMA bead size analyzed by FIM decreased with increasing segmentation threshold. The optimal segmentation threshold where the analyzed size was closest to the indicative size differed between an instrument with a black-and-white camera and that with a color camera. Inter-instrument differences in SVP concentrations in acid-stressed recombinant adeno-associated virus (AAV) and protein aggregates were successfully minimized by setting an optimized segmentation threshold specific to the instrument. These results reveal that PMMA beads can aid in determining a more appropriate segmentation threshold to evaluate biopharmaceutical SVPs using FIM.

Morphologically-Directed Raman Spectroscopy as an Analytical Method for Subvisible Particle Characterization in Therapeutic Protein Product Quality

Subvisible particles (SVPs) are a critical quality attribute of injectable therapeutic proteins (TPs) that needs to be controlled due to potential risks associated with drug product quality. The current compendial methods routinely used to analyze SVPs for lot release provide information on particle size and count. However, chemical identification of individual particles is also important to address root-cause analysis. Herein, we introduce Morphologically-Directed Raman Spectroscopy (MDRS) for SVP characterization of TPs. The following particles were used for method development: (1) polystyrene microspheres, a traditional standard used in industry; (2) photolithographic (SU-8); and (3) ethylene tetrafluoroethylene (ETFE) particles, candidate reference materials developed by NIST. In our study, MDRS rendered high-resolution images for the ETFE particles (> 90%) ranging from 19 to 100 μm in size, covering most of SVP range, and generated comparable morphology data to flow imaging microscopy. Our method was applied to characterize particles formed in stressed TPs and was able to chemically identify individual particles using Raman spectroscopy. MDRS was able to compare morphology and transparency properties of proteinaceous particles with reference materials. The data suggests MDRS may complement the current TPs SVP analysis system and product quality characterization workflow throughout development and commercial lifecycle.

Application of an AI image analysis and classification approach to characterise dissolution and precipitation events in the flow through apparatus

Imaging and artificial intelligence (AI) approaches have been used with increasing frequency in pharmaceutical industry in recent years. Characterisation of processes such as drug dissolution and precipitation is vital in quality control testing and drug manufacture. To support existing techniques like in vitro dissolution testing, novel process analytical technologies (PATs) can give an insight into these processes. The aim of this study was to create and explore the potential of an automated image classification model based on image analysis to identify events (dissolution and precipitation) occurring in the flow-through apparatus (FTA) test cell, and the ability to characterise a dissolution process over time. Several precipitation conditions were tested in a USP 4 FTA test cell with images recorded during early (plume formation) and late (particulate re-formation) stages of precipitation. An available MATLAB code was used as a base to develop and validate an anomaly classification model able to detect different events occurring during the precipitation process in the dissolution cell. Two variants of the model were tested on images from a dissolution test in the FTA, with a view to application of the image analysis system to quantitative characterization of the dissolution process over time. It was found that the classification model is highly accurate (>90%) in detecting events occurring in the FTA test cell. The model showed potential to be used to characterise the stages of dissolution and precipitation processes, and as a proof of concept demonstrates potential for deep machine learning image analysis to be applied to kinetics of other pharmaceutical processes.

Evaluation of subvisible particles in human immunoglobulin and lipid nanoparticles repackaged from a multi-dose vial using plastic syringes

The multi-dose vial (MDV) is widely used for most biopharmaceuticals that are repackaged in plastic syringes before use. However, subvisible particle formation with the use of plastic syringes containing silicone oil (SO syringes) for handling therapeutic proteins can be problematic. This study aimed to evaluate the extent of and trends in microparticle (>1 μm) formation and accumulation in repackaged syringes from MDVs containing human immunoglobulin (IgG) and lipid nanoparticles (LNPs). Light obscuration (LO) and flow imaging (FI) were used to analyze the microparticles. The number of microparticles observed with the use SO syringes was greater than that with SO-free syringes, and the number of microparticles continuously increased as did the number of times of repackaging in syringes for both drugs. However, a large variation was observed across different brands of SO syringes. In contrast, using a different technique of drug withdrawal from the vial significantly reduced the number of microparticles. Furthermore, the use of filter-integrated needles or the inclusion of stabilizers such as acetyl-arginine and Tween 20 into the formulation also helped reduce particle formation.

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.

Number Concentration Measurements of Polystyrene Submicrometer Particles

The number of techniques to measure number concentrations and size distributions of submicrometer particles has recently increased. Submicrometer particle standards are needed to improve the accuracy and reproducibility of these techniques. The number concentrations of fluorescently labeled polystyrene submicrometer sphere suspensions with nominal 100 nm, 200 nm and 500 nm diameters were measured using seven different techniques. Diameter values were also measured where possible. The diameter values were found to agree within 20%, but the number concentration values differed by as much as a factor of two. Accuracy and reproducibility related with the different techniques are discussed with the goal of using number concentration standards for instrument calibration. Three of the techniques were used to determine SI-traceable number concentration values, and the three independent values were averaged to give consensus values. This consensus approach is proposed as a protocol for certifying SI-traceable number concentration standards.

Fcγ Receptor-Dependent Internalization and Off-Target Cytotoxicity of Antibody-Drug Conjugate Aggregates

Purpose

Antibody-drug conjugates (ADCs), which are monoclonal antibodies (mAbs) conjugated with highly toxic payloads, achieve high tumor killing efficacy due to the specific delivery of payloads in accordance with mAbs’ function. On the other hand, the conjugation of payloads often increases the hydrophobicity of mAbs, resulting in reduced stability and increased aggregation. It is considered that mAb aggregates have potential risk for activating Fcγ receptors (FcγRs) on immune cells, and are internalized into cells via FcγRs. Based on the mechanism of action of ADCs, the internalization of ADCs into target-negative cells may cause the off-target toxicity. However, the impacts of aggregation on the safety of ADCs including off-target cytotoxicity have been unclear. In this study, we investigated the cytotoxicity of ADC aggregates in target-negative cells.

Methods

The ADC aggregates were generated by stirring stress or thermal stress. The off-target cytotoxicity of ADC aggregates was evaluated in several target-negative cell lines, and FcγR-activation properties of ADC aggregates were characterized using a reporter cell assay.

Results

Aggregation of ADCs enhanced the off-target cytotoxicity in several target-negative cell lines compared with non-stressed ADCs. Notably, ADC aggregates with FcγR-activation properties showed dramatically enhanced cytotoxicity in FcγR-expressing cells. The FcγR-mediated off-target cytotoxicity of ADC aggregates was reduced by using a FcγR-blocking antibody or Fc-engineering for silencing Fc-mediated effector functions.

Conclusions

These results indicated that FcγRs play an important role for internalization of ADC aggregates into non-target cells, and the aggregation of ADCs increases the potential risk for off-target toxicity.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11095-021-03158-x.