Assessment of powder blend uniformity: Comparison of real-time NIR blend monitoring with stratified sampling in combination with HPLC and at-line NIR Chemical Imaging

Machine Learning-Enabled NIR Spectroscopy in Assessing Powder Blend Uniformity: Clear-Up Disparities and Biases Induced by Physical Artefacts

NIR spectroscopy is a non-destructive characterization tool for the blend uniformity (BU) assessment. However, NIR spectra of powder blends often contain overlapping physical and chemical information of the samples. Deconvoluting the information related to chemical properties from that associated with the physical effects is one of the major objectives of this work. We achieve this aim in two ways. Firstly, we identified various sources of variability that might affect the BU results. Secondly, we leverage the machine learning-based sophisticated data analytics processes. To accomplish the aforementioned objectives, calibration samples of amlodipine as an active pharmaceutical ingredient (API) with the concentrations ranging between 67 and 133% w/w (dose ~ 3.6% w/w), in powder blends containing excipients, were prepared using a gravimetric approach and assessed using NIR spectroscopic analysis, followed by HPLC measurements. The bias in NIR results was investigated by employing data quality metrics (DQM) and bias-variance decomposition (BVD). To overcome the bias, the clustered regression (non-parametric and linear) was applied. We assessed the model's performance by employing the hold-out and k-fold internal cross-validation (CV). NIR-based blend homogeneity with low mean absolute error and an interval estimates of 0.674 (mean) ± 0.218 (standard deviation) w/w was established. Additionally, bootstrapping-based CV was leveraged as part of the NIR method lifecycle management that demonstrated the mean absolute error (MAE) of BU ± 3.5% w/w and BU ± 1.5% w/w for model generalizability and model transferability, respectively. A workflow integrating machine learning to NIR spectral analysis was established and implemented. Impact of various data learning approaches on NIR spectral data.

A hybrid model for multipoint real time potency observation in continuous direct compression manufacturing operations

The ongoing transition from batch to continuous manufacturing offers both challenges and opportunities in the field of oral solid dosage form production. In turn, Process Analytical Technology (PAT) offers a path towards the successful deployment of continuous tablet manufacturing in rotary tablet presses. One promising PAT tool for this endeavour is the NIR-derived potency measurement. However, the high degree of noise in the data may hamper the extraction of useful information. For this reason, this work focused on the implementation of an adaptive Kalman filter algorithm that incorporates and reconciles the potency prediction given by one or more NIR probes with those of a semi-mechanistic compartmental model developed for the application at hand. This approach allowed for more robust concentration estimations. Furthermore, it was observed that potency levels in multiple locations in the studied tablet press (including those in the finished tablets) could be appropriately inferred using a single in-line measurement data stream. This methodology thus opens the door to advanced process control applications.

Non-invasive detection technologies of solid foreign matter and their applications to lyophilized pharmaceutical products: A review

Good Manufacturing Practice Regulations, under the Food and Drug Administration (FDA), stipulate that all pharmaceutical products must be free of any contaminants, including, namely, any foreign solid objects. Lyophilization is a common manufacturing method that consists of several steps where foreign materials may enter the product. The presence of unintended particles in freeze drying, which will herein be referred to under the term 'Lyophilization', is of great concern to the authorities responsible for drug safety and effectiveness. In the pharmaceutical industry, presently, the inspection of lyophilized products for foreign matter particulates relies on visual inspection where only the outer surface of the lyophilized cake is visible. This review is motivated by the need for new control strategies for foreign matter (FM) detection in lyophilized products; more specifically, it assesses the reliability of non-destructive technologies for FM detection in dried samples. Emerging technologies applied in other industries, such as various types of spectroscopies and imaging (e.g. chemical, X-ray, ultrasound, thermal and terahertz), are evaluated based on compatibility with the intended application, with identification of the possible technical challenges.

Pharmaceutical application of multivariate modelling techniques: a review on the manufacturing of tablets

The tablet manufacturing process is a complex system, especially in continuous manufacturing (CM). It includes multiple unit operations, such as mixing, granulation, and tableting. In tablet manufacturing, critical quality attributes are influenced by multiple factorial relationships between material properties, process variables, and interactions. Moreover, the variation in raw material attributes and manufacturing processes is an inherent characteristic and seriously affects the quality of pharmaceutical products. To deepen our understanding of the tablet manufacturing process, multivariable modeling techniques can replace univariate analysis to investigate tablet manufacturing. In this review, the roles of the most prominent multivariate modeling techniques in the tablet manufacturing process are discussed. The review mainly focuses on applying multivariate modeling techniques to process understanding, optimization, process monitoring, and process control within multiple unit operations. To minimize the errors in the process of modeling, good modeling practice (GMoP) was introduced into the pharmaceutical process. Furthermore, current progress in the continuous manufacturing of tablets and the role of multivariate modeling techniques in continuous manufacturing are introduced. In this review, information is provided to both researchers and manufacturers to improve tablet quality.

Near infrared analysis of pharmaceutical powders with empirical target distribution optimization (ETDO)

Near infrared (NIR) spectroscopy is a well-established method for analysis of pharmaceutical products, and especially useful for process monitoring and control of continuous production due to high sample throughput. In this work, a previously established method called empirical target distribution optimization (ETDO) wherein reference sample values using information from model prediction of the calibration data was used as a tool to improve the performance of NIR partial least squares (PLS) models. Model performance was assessed using root mean square error (R²), bias and accuracy in prediction of test samples. A target value selection threshold was tested to assess the ETDO procedure for NIR analysis of powder samples. The amount of specific variation captured by the model was examined and compared for models calibrated with and without ETDO. The results reported in this work suggests that PLS models optimized with ETDO of reference values can provide more specific PLS models for NIR analysis for complex powder mixtures. In addition, the model optimization method could also be applied as a tool to verify the necessary amount of PLS components to produce robust models. The ETDO method presented in this work is an approach that could be applied in the development of continuous blending or tableting processes where robust in-line quantitative analysis of powder samples is needed.

A sampling system for flowing powders based on the theory of sampling

An innovative chute and stream sampler system for flowing powders has been developed and tested. The system is designed for representative sampling based on the principles of the Theory of Sampling (TOS). The sampling system was used in combination with near infrared (NIR) spectroscopy to determine the drug concentration of flowing powders. The system is comprised of three parts: a chute, a stream sampler and a sample collection port. The NIR spectra were obtained at the chute, before entering the sampler, and as the powder flowed through the stream sampler. Samples were also collected from the sample collection port to be analyzed using an ultraviolet-visible (UV-Vis) reference method to determine drug content. A total of eight pharmaceutical powder blends, ranging in concentration from 10.5(%w/w) to 19.5(%w/w) of caffeine, were used to test the sampling system. Materials were characterized before blends were made to provide information on flow properties. The throughput of the system was between 30 and 35 kg/h based on the flow properties of the blend. Drug concentration was effectively determined at the chute and stream sampler. The NIR calibration models showed low root mean squared errors of prediction, 0.65(%w/w) and 0.51(%w/w), for the chute and stream sampler respectively. The NIR calibration models also showed low bias values -0.36(%w/w) at the chute and 0.057(%w/w) at the stream sampler. Significant agreement was obtained between the results from the nondestructive NIR versus the destructive UV-Vis method. Variographic analysis was performed to estimate the analytical and sampling errors when determining the drug concentration at the chute and stream sampler respectively. The variographic analysis showed low analytical errors, 0.103(%w/w)² and 0.181(%w/w)² at the chute and stream sampler respectively. The analysis also showed that the minimum practical error (MPE) was around 0.2(%w/w)² at both chute and stream sampler.

Feed frame: The last processing step before the tablet compaction in pharmaceutical manufacturing

The feed frame is a force-feeding device used in the die filling process. The die filling process is crucial within pharmaceutical manufacturing to guarantee the critical quality attributes of the tablets. In recent years, interest in this unit has increased because it can affect the properties of the powder blend and tablets, and because of the success in real time monitoring of powder blend uniformity potential for Process Analytical Technology as described in this review. The review focuses on the recent advances in understanding the powder flow behavior inside the feed frame and how the residence time distribution of the powder within the feed frame is affected by the operating conditions and design parameters. Furthermore, this review also highlights the effect of the paddle wheel design and feed frame process parameters on the tablet weight, the principal variable for measuring die filling performance.

Methods to Assess Mixing of Pharmaceutical Powders

The pharmaceutical manufacturing process consists of several steps, each of which must be monitored and controlled to ensure quality standards are met. The level of blending has an impact on the final product quality; therefore, it is important to be able to monitor blending progress and identify an end-point. Currently, the pharmaceutical industry assesses blend content and uniformity through the extraction of samples using thief probes followed by analytical methods, such as spectroscopy, to determine the sample composition. The development of process analytical technologies (PAT) can improve product monitoring with the aim of increasing efficiency, product quality and consistency, and creating a better understanding of the manufacturing process. Ideally, these are inline methods to remove issues related to extractive sampling and allow direct monitoring of the system using various sensors. Many technologies have been investigated, including spectroscopic techniques such as near-infrared spectroscopy, velocimetric techniques that may use tracers, tomographic techniques, and acoustic emissions monitoring. While some techniques have demonstrated potential, many have significant disadvantages including the need for equipment modification, specific requirements of the material, expensive equipment, extensive analysis, the location of the probes may be critical and/or invasive, and lastly, the technique may only be applicable to the development phase. Both the advantages and disadvantages of the technologies should be considered in application to a specific system.

Macro-Raman spectroscopy for bulk composition and homogeneity analysis of multi-component pharmaceutical powders

A new macro-Raman system equipped with a motorized translational sample stage and low-frequency shift capabilities was developed for bulk composition and homogeneity analysis of multi-component pharmaceutical powders. Different sampling methods including single spot and scanning measurement were compared. It was found that increasing sample volumes significantly improved the precision of quantitative composition analysis, especially for poorly mixed powders. The multi-pass cavity of the macro-Raman system increased effective sample volumes by 20 times from the sample volume defined by the collection optics, i.e., from 0.02μL to about 0.4μL. A stochastic model simulating the random sampling process of polydisperse microparticles was used to predict the sampling errors for a specific sample volume. Comparison of fluticasone propionate mass fractions of the commercial products Flixotide^® 250 and Seretide^® 500 simulated for different sampling volumes with experimentally measured compositions verified that the effective sample volume of a single point macro-Raman measurement in the multi-pass cavity of this instrument was between 0.3μL and 0.5μL. The macro-Raman system was also successfully used for blend uniformity analysis. It was concluded that demixing occurred in the binary mixture of l-leucine and d-mannitol from the observation that the sampling errors indicated by the standard deviations of measured leucine mass fractions increased during mixing, and the standard deviation values were all larger than the theoretical lower limit determined by the simulation. Since sample volume was shown to have a significant impact on measured homogeneity characteristics, it was concluded that powder homogeneity analysis results, i.e., the mean of individual test results and absolute and relative standard deviations, must be presented together with the effective sample volumes of the applied testing techniques for any measurement of powder homogeneity to be fully meaningful.

Process Analytical Quality Control of Tailored Drug Release Formulation Prepared via Hot-Melt Extrusion Technology

The objective of the present study was to compare the influence of Eudragit^® RS PO and RL PO blends on the release of water-soluble and insoluble drugs from hot-melt extruded formulations. In addition, we aimed to evaluate drug content uniformity and distribution by Fourier transform-infrared (FT-IR) chemical imaging. Theophylline (TP) and carbamazepine (CBZ) were selected as the water-soluble and insoluble model drugs, respectively. Eudragit^® RS PO and RL PO were selected as the polymeric matrices. FT-IR chemical imaging clearly demonstrated the content uniformity and distribution for both drugs in the extrudates, which was confirmed by HPLC. Increasing the ratio of Eudragit^® RL PO led to an increase in the in vitro drug release, whereas an increase in the ratio of Eudragit^® RS PO sustained the drug release for up to 12 h. The hot-melt extrusion of TP and CBZ with varying ratios of Eudragit^® RS PO and RL PO can be employed to tailor the drug release profiles. In this study, we demonstrated, for the first time, the use of FT-IR chemical imaging as a process analytical technique to determine the drug content uniformity and distribution. Our data correlated well with the results of HPLC analysis in the study of tailored drug release from the prepared hot-melt extruded formulation.