Near-infrared Spectroscopy for the In-line Characterization of Powder Voiding Part I: Development of the Methodology

The effect of process parameters on a continuous blending process monitored in-line by near-infrared spectroscopy

The continuous feeding-mixing system ensures the composition uniformity down to the tableting continuous manufacturing line so that a quality end-product is consistently delivered. Near-infrared spectroscopy (NIRS) enables in-line assessment of the blend's critical quality attributes in real-time. In this study, the effect of total feed rate and impeller speed on the continuous blending process monitored in-line by NIRS was examined by principal component analysis (PCA), ANOVA simultaneous component analysis (ASCA) and partial least squares (PLS) regression. Process data were generated by a factorial experimental design with process parameters and a constant formulation comprised of: 30 % (wt/wt) ibuprofen, 67.5 % (wt/wt) microcrystalline cellulose, 2 % (wt/wt) of sodium starch glycolate and 0.5 % (wt/wt) of magnesium stearate. The PCA hinted at the prevalence of impeller speed effect on ibuprofen concentration due to path length variation of the NIR light caused by the fluidized behaviour in the powder blend as a result of high speed ranges (>300 rpm). The ASCA model indicated that while both impeller speed and total feed rate effects were statistically significant (p-value=0.004), the impeller speed was the factor that contributed the most to the spectral variance (55.5 %). The PLS regression model for the ibuprofen content resulted in a RMSECV of 1.3 % (wt/wt) and showed that impeller speed was yet again the factor that exerted the major influence on spectral variance, owing to its wavelength-dependent effect that prevents common pre-processing techniques from eliminating it across the entire NIR range. The best sample presentation to the NIR probe was achieved at low impeller speed ranges (<600 rpm) and low total feed rates (<15 kg/h), such that it enhanced the PLS model ability to predict the ibuprofen concentration in the blend.

Influence of powder stream density on near infrared measurements upon scale-up of a simulated continuous process

Near-infrared (NIR) spectroscopy is a powerful process analytical tool for monitoring chemical constituents in continuous pharmaceutical processes. However, the density variation introduced when quantitative NIR measurements are performed on powder streams at different flow rates is a potential source of a lack of model robustness. Since different flow rates are often required to meet the production requirements (e.g., during scale-up) of a continuous process, the development of efficient strategies to characterize, understand, and mitigate the impact of powder density on NIR measurements is highly desirable. This study focused on assessing the effect of powder physical variation on NIR by enabling the in-line characterization of powder stream density in a simulated continuous system. The in-line measurements of powder stream density were facilitated through a unique analytical interface to a flowing process. Powder streams delivered at various design levels of flow rate and tube angle were monitored simultaneously by NIR diffuse reflectance spectroscopy, live imaging, and dynamic mass characterization. Statistical analysis and multivariate modeling confirmed powder density as a significant source of spectral variability due to flow rate. Besides providing broader process understanding, results elucidated potential mitigation strategies to facilitate effective continuous process scale-up while ensuring NIR model robustness against density.

In-Line Detection of Bed Fluidity in Gas-Solid Fluidized Beds Using Near-Infrared Spectroscopy

A novel approach was developed to detect bed fluidity in gas-solid fluidized beds using diffuse reflectance near-infrared (NIR) spectroscopy. Because the flow dynamics of gas and solid phases are closely associated with the fluidization state, the fluidization quality can be evaluated through hydrodynamic characterization. In this study, the baseline level of NIR spectra was used to quantify the voidage of the fluidized bed. Two indicators derived from the NIR baseline fluctuation profiles were investigated to characterize bed fluidity, named bubble proportion and skewness. To establish a robust fluidity evaluation method, the relationships between the indicators and bed fluidity were investigated under different conditions firstly, including static bed height and average particle size. Then, a generalized threshold was identified to distinguish poor and good bed fluidity, ensuring that the probability of the α- and β-errors was less than 15% regardless of material conditions. The results show that both indicators were sensitive to changes in bed fluidity under the investigated conditions. The indicator of skewness was qualified to detect bed fluidity under varied conditions with a robust threshold of 1.20. Furthermore, the developed NIR method was successfully applied to monitor bed fluidity and for early warning of defluidization in a laboratory-scale fluidized bed granulation process.

Challenges, opportunities and recent advances in near infrared spectroscopy applications for monitoring blend uniformity in the continuous manufacturing of solid oral dosage forms

Near infrared (NIR) spectroscopy has been widely recognized as a powerful PAT tool for monitoring blend uniformity in continuous manufacturing (CM) processes. However, the dynamic nature of the powder stream and the fast rate at which it moves, compared to batch processes, introduces challenges to NIR quantitative methods for monitoring blend uniformity. For instance, defining the effective sample size interrogated by NIR, selecting the best sampling location for blend monitoring, and ensuring NIR model robustness against influential sources of variability are challenges commonly reported for NIR applications in CM. This article reviews the NIR applications for powder blend monitoring in the continuous manufacturing of solid oral dosage forms, with a particular focus on the challenges, opportunities for method optimization and recent advances with respect three main aspects: effective sample size measured by NIR, probe location and method robustness.

Method transfer of a near-infrared spectroscopic method for blend uniformity in a poorly flowing and hygroscopic blend

The challenges in transferring and executing a near-infrared (NIR) spectroscopic method for croscarmellose (disintegrant) in binary blends for a continuous manufacturing (CM) process are presented. This work demonstrates the development of a NIR calibration model and its use to determine the blending parameters needed for binary blends at a development plant and later used to predict CM process blends. The calibration models were developed with laboratory scale powder blends ranging from 4.32%-64.77 (%w/w) of croscarmellose and evaluated using independent test blends. The selected model was then transferred to the continuous manufacturing development site to determine the croscarmellose concentration for spectra collected in real-time. A total of 18 development plant runs were monitored using an in-line NIR spectrometer, however, these spectra showed high baseline variations. The baseline variations were caused by the poor flow of the material within the system. An inconsistent bias which varied from 2.51 to 14.95 (%w/w) was observed in the predictions of croscarmellose. High baseline spectra were eliminated and the bias was significantly reduced by 42-51%. Experiments at lower flow rate speeds did not show significant changes in baseline and bias values showed more consistency. The calibration model was then transferred to two NIR spectrometers installed at-line at the commercial site, where powder samples were collected at the beginning middle and end of each CM plant run. The NIR calibration model predicted disintegrant concentration from the powder samples. Results showed the bias values for the NIR (1) varied from 0.74 to 2.21 (%w/w) and NIR (2) from 0.28 to 3.39 (%w/w). Average concentration values for both equipments were very close to the reference concentration values of 43.18 and 50.98 (%w/w). The study showed the model was able to identify flow issues, identified as baseline shifts, that could be used to alert to problems in the powder bed that may warrant diversion from a production line. These powder flow problems such as air gaps and inconsistent powder bed height affected the NIR spectra collected at the development plant and provided results with high bias. A lower bias was obtained in samples collected at line after blending.

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.

Near infrared spectroscopic transmittance measurements for pharmaceutical powder mixtures

This study describes the development of near infrared (NIR) calibration models using transmittance measurements in powder samples and compares the results obtained with those of tablet transmittance and diffuse reflectance of powders. Transmission near infrared spectroscopy is a method widely used for the analysis of tablets in the evaluation of drug concentration due to the larger sample volume analyzed, but not commonly used for the analysis of powder samples. Diffuse reflection near infrared spectroscopy is a method used in both powder and tablets for the evaluation of quality attributes. In this initial study NIR transmittance measurements were obtained using an off-line spectrometer equipped with a high intensity light source. Spectra were obtained with three different resolutions for the analysis of powder and tablet samples of 7.50-22.50% (w/w) acetaminophen. The Partial Least Squares (PLS) calibration models developed include pretreatments such as Standard Normal Variate (SNV) and first derivative in the region from 9500-7500 cm(-1). Transmittance in powder presented low Root Mean Square Error of Prediction (RMSEP) values that varied from 0.23-1.15% (w/w) APAP with resolution of 64 and 16 cm(-1). The lowest RMSEP values (0.23-0.39% (w/w) APAP) were obtained using a resolution of 64 cm(-1). The RMSEP values for powder transmittance measurements were 2.4-5.6 times lower than the diffuse reflectance measurements of the powder mixtures.

Near Infrared Spectroscopy: From Feasibility to Implementation in the Pharmaceutical Industry

Near infrared (NIR) spectroscopy will play an increasingly important role in pharmaceutical processes as the quality of pharmaceutical products is progressively defined on the basis of their performance and pharmaceutical quality control is transformed to meet this challenge. This new quality control will require a thorough understanding of the sources of error in NIR methods, an understanding that starts with fundamentals such as the physics of diffuse reflectance and the Theory of Sampling, and progresses to working with pharmaceutical engineers to implement online predictions and control of pharmaceutical operations. This article outlines the research areas that need to be integrated to advance the implementation of NIR spectroscopy in the pharmaceutical industry.

Use of near-infrared spectroscopy to quantify drug content on a continuous blending process: influence of mass flow and rotation speed variations

The aim of this study was to develop a quantitative Near-Infrared (NIR) method which monitors the homogeneity of a pharmaceutical formulation coming out of a continuous blender. For this purpose, a NIR diode array spectrometer with fast data acquisition was selected. Additionally, the dynamic aspects of a continuous blending process were studied; the results showed a well-defined cluster for the steady state, and the paths for the start-up and emptying stages were clearly identified. The end point of the start-up phase was detected by moving block of standard deviation, relative standard deviation, and principal component analysis. A partial least square (PLS) model was generated for the quantification of the drug, with a standard error of prediction of 0.2% m/m. The PLS model was successfully applied for monitoring the drug level at the outlet of the continuous blender. Furthermore, the PLS model was tested under different flow and stirring rates. Flow and stirring rate variations caused different powder flow dynamics, which were reflected on the NIR measurements. Therefore, the PLS model was sensitive to changes in mass flow and rotation speeds.