Monitoring of Visible Particles in Parenteral Products by Manual Visual Inspection-Reassessing Size Threshold and Other Particle Characteristics that Define Particle Visibility.

Visible particles are a critical quality attribute for parenteral products and must be monitored. A carefully designed, executed, and controlled drug product manufacturing process including a final 100 % visual inspection and appropriate end-product controls ensures that visible particles are consistently minimized and demonstrates that the injectable DP is practically free from visible particles. Visual inspection, albeit appearing as a simple analytical procedure, requires several technical and operational controls to ensure adequate performance. To gather new data on particle visibility and shed light on this decade-old challenge, a multi-company blinded visual inspection threshold study was conducted. A major goal of the study was visual assessment of several particle types of different sizes in small volume vials, as a challenging configuration for visual inspection, across 9 biopharmaceutical companies in order to determine the visibility limit. The study results provide key insights into limitations and challenges of visual inspection, namely, no universal visibility limit can be applied to all particle types as the detectability varies with particle type, number, and size. The study findings underscore the necessity of setting realistic expectations on size-based visibility limits in visual inspection, robust procedures for analyst training and qualification, and harmonization of guidelines globally.

Image Classification of Degraded Polysorbate, Protein and Silicone Oil Sub-Visible Particles Detected by Flow-Imaging Microscopy in Biopharmaceuticals Using a Convolutional Neural Network Model.

Degradation of polysorbates in biopharmaceutical formulations can induce the formation of sub-visible particles (SvPs) in the form of free-fatty acids (FFAs) and potentially protein aggregates. Flow-imaging microscopy (FIM) is one of the most common techniques for enumerating and characterizing the SvPs, allowing for collection of image data of the SvPs in the size ranges of two to several hundred micrometers. The vast amounts of data obtained with FIM do not allow for rapid manual characterization by an experienced analyst and can be ambiguous. In this work, we present the application of a custom convolutional neural network (CNN) for classification of SvP images of FFAs, proteinaceous particles and silicon oil droplets, by FIM. The network was then used to predict the composition of artificially pooled test samples of unknown and labeled data with varying compositions. Minor misclassifications were observed between the FFAs and proteinaceous particles, considered tolerable for application to pharmaceutical development. The network is considered to be suitable for fast and robust classification of the most common SvPs found during FIM analysis.

An Interlaboratory Comparison on the Characterization of a Sub-micrometer Polydisperse Particle Dispersion.

The measurement of polydisperse protein aggregates and particles in biotherapeutics remains a challenge, especially for particles with diameters of ≈ 1 µm and below (sub-micrometer). This paper describes an interlaboratory comparison with the goal of assessing the measurement variability for the characterization of a sub-micrometer polydisperse particle dispersion composed of five sub-populations of poly(methyl methacrylate) (PMMA) and silica beads. The study included 20 participating laboratories from industry, academia, and government, and a variety of state-of-the-art particle-counting instruments. The received datasets were organized by instrument class to enable comparison of intralaboratory and interlaboratory performance. The main findings included high variability between datasets from different laboratories, with coefficients of variation from 13 % to 189 %. Intralaboratory variability was, on average, 37 % of the interlaboratory variability for an instrument class and particle sub-population. Drop-offs at either end of the size range and poor agreement on maximum counts of particle sub-populations were noted. The mean distributions from an instrument class, however, showed the size-coverage range for that class. The study shows that a polydisperse sample can be used to assess performance capabilities of an instrument set-up (including hardware, software, and user settings) and provides guidance for the development of polydisperse reference materials.

Identification of an Oxidizing Leachable from a Clinical Syringe Rubber Stopper.

Leaching of toxic or reactive chemicals from polymeric materials can adversely affect the quality and safety of biopharmaceuticals. It was therefore the aim of the present study to analyze leachables from a disposable clinical administration syringe using a polysorbate-containing surrogate solution and to assess their chemical reactivity. Analytical methods did include (headspace) GC-MS, Fourier-transform-infrared spectroscopy, a ferrous oxidation-xylenol orange assay, and nuclear magnetic resonance analysis. In the syringe leachables solution, the carcinogenic 1,1,2,2-tetrachloroethane (TCE) was detected in concentrations above the ICH M7-derived analytical evaluation threshold. TCE was shown to be an oxidation product of dichloromethane used during sample preparation. Since TCE was only isolated from incubations with the contained rubber stopper, we hypothesized that a stopper-derived leachable acted as a reactive oxidant promoting this chemical reaction. Subsequently, the leachable was identified to be the polymerization initiator Luperox® 101. Combining different analytical approaches led to the structural elucidation of a chemical reactive oxidant, which has the potential to interact and alter drug products. We conclude that chemically reactive compounds, such as the newly identified rubber stopper leachable Luperox® 101, may be of concern and therefore should be routinely considered if a prolonged exposure of polymers with drug products can be anticipated.

Characterization of Polymeric Syringes Used for Intravitreal Injection.

Intravitreal (IVT) injection is currently the state of the art for drug delivery to the back of the eye. Drug Products (DP) intended for IVT injections usually pose challenges such as a very low injection volume (e.g. 50 µL) and high injection forces. DPs in vials are typically transferred and injected using disposable polymer syringes, which can feature a silicone oil (SO) coating. In our syringe in-use study, we compared dead volume, total SO content and SO layer distributions of three IVT transfer injection syringes. We assessed multiple potential impact factors such as protein concentration, needle gauge, injection speed, surfactant type and the impact of the in-use hold time on sub-visible particle (SvP) formation and injection forces. Pronounced differences were observed between the syringes regarding SvP generation. Siliconized syringes showed higher SvP counts as compared to non-siliconized syringes. In some cases injection forces exceeded 20 N, which caused needles to burst off during injection. The syringes also showed relevant differences in total SO content and dead volume. In conclusion, specific consideration in the selection of an adequate transfer injection syringe are required. This includes extensive testing and characterization under intended and potential in-use conditions and the development of in-use handling procedures.

Evaluation of Different Quality-Relevant Aspects of Closed System Transfer Devices (CSTDs).

PURPOSE: Health care professionals can be exposed to hazardous drugs such as cytostatics during preparation of drugs for administration. Closed sytem transfer devices (CSTDs) were introduced to provide protection for healthcare professional against unintended exposure to hazardous drugs. The interest in CSTDs has significantly increased after USP <800> monograph was issued. The majority of the studies published so far on CSTDs have focused on their "containment" function. However, other important attributes for CSTDs with potential importance for product quality impact are not yet fully evaluated. METHODS: In the current study, we evaluated four sytems from different suppliers, in combination with different container closure systems (CCS), using solutions of different viscosity and surface tension. The different CSTD / CCS combinations were tested for (a) containment (integrity) using a highly sensitive helium leak test, (b) the force required for mounting the vial adaptor, (c) contribution to visible and subvisible particles as well as (d) the hold-up volume. RESULTS: Results show that the majority of CSTDs may have leaks varying in size, and that some of them generated visible particles due to stopper coring and subvisible particles, both due to silicon oil and particulate contaminations of the Devices. Finally, the holdup volume was up to 1 mL depending on the CSTD type, vial size and solution viscosity. CONCLUSION: These results show that there is a need to evaluate the compatibility of CSTD systems to select the best system for the intended use and that CSTDs may adversely impact product quality and delivered dose.

Method to Predict Glass Vial Fogging in Lyophilized Drug Products.

Glass fogging is a phenomenon occurring in lyophilized drug products and can be described as a thin product layer deposited on the inner surface of the glass container, in the area not covered by the lyo cake itself. It is often considered a cosmetic defect; however, the loss of container closure integrity is a potential consequence of the fogging's expansion to the vial neck region, making this a potential critical defect. Thus, a method for predicting the extent of vial fogging before the actual freeze-drying is of particular interest for the pharmaceutical industry. For that reason, we evaluated a simple method ("simulated fogging") applicable to drug product formulations in a specific container closure system. Two different vial types with different surface hydrophilicity were tested using 3 model protein formulations, comparing the simulated fogging test and the degree of fogging after actual lyophilization. The simulated fogging method could predict fogging and showed a correlation to fogging in lyophilized drug product glass vials. We observed that all formulations showed fogging in the hydrophilic vials. By contrast, hydrophobic vials prevented fogging, however, interestingly with remaining defects of so-called droplet formation. Other than extent of fogging, no additional differences of lyophilized cake properties or other product quality attributes were observed between products using the different glass vial types tested.

Quantitative X-Ray Microcomputed Tomography Assessment of Internal Tablet Defects.

Physical tablet defects are related to internal structural defects that are not easily assessed by the traditional methods, such as dusting, laminating, or fracturing during appearance, friability, or hardness testing. Also, these methods do not allow objective and quantitative investigation of the role of formulation and process variables, which is essential for quality-by-design drug product development. In this study, an X-ray microcomputed tomography (XµCT) method to analyze internal tablet defects is developed using tablets from a quality-by-design design-of-experiment study. The design of experiment investigated the effect of roller compaction roll force, filler composition, and the amount of magnesium stearate on tablet quality attributes. Average contiguous void volume by optical image processing and fracture size distribution and direction by artificial intelligence-based image processing quantified the internal tablet fracture severity. XµCT increased formulation and process knowledge in support of scale-up manufacturing. We demonstrated how XµCT can be incorporated as a part of a holistic approach to quantitatively identify and mechanistically assess the risks of internal tablet defects. Furthermore, expanding the use of XµCT with an artificial intelligence-based quantitative analysis can deepen our tableting knowledge from an empirical understanding to a mechanistic understanding of compaction phenomenon.

Characterising Drug Release from Immediate-Release Formulations of a Poorly Soluble Compound, Basmisanil, Through Absorption Modelling and Dissolution Testing.

The study aimed to characterise the mechanism of release and absorption of Basmisanil, a biopharmaceutics classification system (BCS) class 2 compound, from immediate-release formulations via mechanistic absorption modelling, dissolution testing, and Raman imaging. An oral absorption model was developed in GastroPlus® and verified with single-dose pharmacokinetic data in humans. The properties and drug release behaviour of different oral Basmisanil formulations were characterised via biorelevant dissolution and Raman imaging studies. Finally, an in vitro-in vivo correlation (IVIVC) model was developed using conventional and mechanistic deconvolution methods for comparison. The GastroPlus model accurately simulated oral Basmisanil exposure from tablets and granules formulations containing micronized drug. Absorption of oral doses below 200 mg was mostly dissolution rate-limited and thus particularly sensitive to formulation properties. Indeed, reduced exposure was observed for a 120-mg film-coated tablet and the slower dissolution rate measured in biorelevant media was attributed to differences in drug load. This hypothesis was confirmed when Raman imaging showed that the percolation threshold was exceeded in this formulation. This biorelevant dissolution method clearly differentiated between the formulations and was used to develop a robust IVIVC model. The study demonstrates the applicability and impact of mechanistic absorption modelling and biopharmaceutical in vitro tools for rational drug development.

Artificial Leaks in Container Closure Integrity Testing: Nonlinear Finite Element Simulation of Aperture Size Originated by a Copper Wire Sandwiched between the Stopper and the Glass Vial.

Container closure integrity (CCI) testing is required by different regulatory authorities in order to provide assurance of tightness of the container closure system against possible contamination, for example, by microorganisms. Microbial ingress CCI testing is performed by incubation of the container closure system with microorganisms under specified testing conditions. Physical CCI uses surrogate endpoints, such as coloration by dye solution ingress or gas flow (helium leakage testing). In order to correlate microbial CCI and physical CCI test methods and to evaluate the methods' capability to detect a given leak, artificial leaks are being introduced into the container closure system in a variety of different ways. In our study, artificial leaks were generated using inserted copper wires between the glass vial opening and rubber stopper. However, the insertion of copper wires introduces leaks of unknown size and shape. With nonlinear finite element simulations, the aperture size between the rubber stopper and the glass vial was calculated, depending on wire diameter and capping force. The dependency of the aperture size on the copper wire diameter was quadratic. With the data obtained, we were able to calculate the leak size and model leak shape. Our results suggest that the size as well as the shape of the artificial leaks should be taken into account when evaluating critical leak sizes, as flow rate does not, independently, correlate to hole size. Capping force also affected leak size. An increase in the capping force from 30 to 70 N resulted in a reduction of the aperture (leak size) by approximately 50% for all wire diameters. From 30 to 50 N, the reduction was approximately 33%. LAY ABSTRACT: Container closure integrity (CCI) testing is required by different regulatory authorities in order to provide assurance of tightness of the container closure system against contamination, for example, by microorganisms. Microbial ingress CCI testing is performed by incubation of the container closure system with microorganisms under specified testing conditions. Physical CCI uses surrogate endpoints, such as coloration by dye solution ingress or gas flow. In order to correlate microbial ingress CCI and physical CCI test methods and to evaluate the methods' capability to detect a given leak, artificially created defects (artificial leaks) are being introduced into the container closure system in a variety of different ways. In our study, artificial leaks were generated using inserted copper wires between the glass vial opening and rubber stopper. Up to date, the insertion of copper wires introduced leaks of unknown size and shape. With nonlinear finite element simulations, the effective aperture size between the rubber stopper and the glass vial was calculated, depending on wire diameter and capping force, and the leak shape was modelled. Our results suggest that the size as well as the shape of the artificial leaks should be taken into account when evaluating critical leak sizes, as flow rate does not, independently, correlate to the hole size.

A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies.

Near-infrared spectroscopy (NIRS) is a fast and non-destructive analytical method. Associated with chemometrics, it becomes a powerful tool for the pharmaceutical industry. Indeed, NIRS is suitable for analysis of solid, liquid and biotechnological pharmaceutical forms. Moreover, NIRS can be implemented during pharmaceutical development, in production for process monitoring or in quality control laboratories. This review focuses on chemometric techniques and pharmaceutical NIRS applications. The following topics are covered: qualitative analyses, quantitative methods and on-line applications. Theoretical and practical aspects are described with pharmaceutical examples of NIRS applications.

Combined wavelet transform-artificial neural network use in tablet active content determination by near-infrared spectroscopy.

The pharmaceutical industry faces increasing regulatory pressure to optimize quality control. Content uniformity is a basic release test for solid dosage forms. To accelerate test throughput and comply with the Food and Drug Administration's process analytical technology initiative, attention is increasingly turning to nondestructive spectroscopic techniques, notably near-infrared (NIR) spectroscopy (NIRS). However, validation of NIRS using requisite linearity and standard error of prediction (SEP) criteria remains a challenge. This study applied wavelet transformation of the NIR spectra of a commercial tablet to build a model using conventional partial least squares (PLS) regression and an artificial neural network (ANN). Wavelet coefficients in the PLS and ANN models reduced SEP by up to 60% compared to PLS models using mathematical spectra pretreatment. ANN modeling yielded high-linearity calibration and a correlation coefficient exceeding 0.996.

Near-infrared determination of active substance content in intact low-dosage tablets.

Near-infrared (NIR) spectroscopy can be applied to determine the active substance content of tablets. Its great advantage lies in the minimal sample preparation required, which helps to reduce the potential for error. The aim of this study is to show the feasibility of this method on low-dosage tablets. The influence of various spectral pretreatments [standard normal variate (SNV), multiplicative scatter correction (MSC), second derivative (D2), orthogonal signal correction (OSC), separately and combined] and regression methods on prediction error are compared. Partial least square (PLS) regression provided better prediction than principal component regression (PCR). SNV was applied to the first data set and SNV and a second derivative to the second set to maximise model accuracy for quantifying the active substance of intact pharmaceutical products using diffuse reflectance NIR. The models yielded standard errors of prediction (SEP) of 0.1768 and 0.0682mg for the two products. The experiments were conducted with two low-dosage pharmaceutical forms and results of NIR predictions were comparable to currently approved methods. Diffuse reflectance NIR has the potential to become a reliable and robust quality control method for determining active tablet content.