Comparison of near infrared and microwave resonance sensors for at-line moisture determination in powders and tablets

NIR quantitative model trans-scale calibration from small scale to pilot scale via directed DOSC-SBC algorithm

In order to solve the problem of inapplicability of NIR quantitative models due to the large difference between the modeling samples and the samples to be tested, Directed DOSC-SBC（DDOSC-SBC）algorithm is proposed in this paper based on Direct Orthogonal Signal Correction combined with Slope/Bias Correction (DOSC-SBC) algorithm. To obtain the suitable spectral matrix transfer parameters for the test set during DDOSC spectral preprocessing, several representative test samples in the test set were selected, then the spectral systematic errors between the modeling set and the test set were corrected with the SBC method in order to realize the trans-scale prediction of the NIR quantitative model. NIR data and the critical quality attributes（CQAs）were detected in the small scale and pilot scale pharmaceutical process of the fluidized bed granulation of dextrin and water extraction of honeysuckle. After the small scale model was calibrated via the directed DOSC-SBC algorithm which was guided by representative pilot scale samples, the small scale model was able to predict the pilot scale test samples more accurately. The NIR quantitative model trans-scale calibration from small scale to pilot scale was also successfully realized with a RPD value higher than 3.5 and RSEP value lower than 10%. DDOSC-SBC algorithm is a successful model trans-scale calibrated method that can be applied to NIR real-time monitoring of CQAs in the preparation process of Chinese herbal medicine.

Process Analytical Technology Tools for Monitoring Pharmaceutical Unit Operations: A Control Strategy for Continuous Process Verification

Various frameworks and methods, such as quality by design (QbD), real time release test (RTRT), and continuous process verification (CPV), have been introduced to improve drug product quality in the pharmaceutical industry. The methods recognize that an appropriate combination of process controls and predefined material attributes and intermediate quality attributes (IQAs) during processing may provide greater assurance of product quality than end-product testing. The efficient analysis method to monitor the relationship between process and quality should be used. Process analytical technology (PAT) was introduced to analyze IQAs during the process of establishing regulatory specifications and facilitating continuous manufacturing improvement. Although PAT was introduced in the pharmaceutical industry in the early 21st century, new PAT tools have been introduced during the last 20 years. In this review, we present the recent pharmaceutical PAT tools and their application in pharmaceutical unit operations. Based on unit operations, the significant IQAs monitored by PAT are presented to establish a control strategy for CPV and real time release testing (RTRT). In addition, the equipment type used in unit operation, PAT tools, multivariate statistical tools, and mathematical preprocessing are introduced, along with relevant literature. This review suggests that various PAT tools are rapidly advancing, and various IQAs are efficiently and precisely monitored in the pharmaceutical industry. Therefore, PAT could be a fundamental tool for the present QbD and CPV to improve drug product quality.

Process analytical technology tools for process control of roller compaction in solid pharmaceuticals manufacturing

This article presents an overview of using process analytical technology in monitoring the roller compaction process. In the past two decades, near-infrared spectroscopy, near-infrared spectroscopy coupled with chemical imaging, microwave resonance technology, thermal effusivity and various particle imaging techniques have been used for developing at-, off-, on- and in-line models for predicting critical quality attributes of ribbons and subsequent granules and tablets. The common goal of all these methods is improved process understanding and process control, and thus improved production of high-quality products. This article reviews the work of several researchers in this field, comparing and critically evaluating their achievements.

Confirmation of brand identification in infant formulas by using near-infrared spectroscopy fingerprints

In this study, a near infrared (NIR) spectroscopy fingerprinting method coupled with principal component analysis (PCA) was developed for the confirmation of brand identification in infant formulas. The NIR spectroscopy fingerprints of the Brand A infant formula were acquired in 12 000-4000 cm-1 at a sample temperature of 20 °C without pressing the sample. The contents of major nutrients of Stage 1, 2, and 3 infant formulas were compared within Brand A. The NIR spectroscopy fingerprints of Brand A Stage 1 samples were compared with those of four other brand-named Stage 1 samples, whereas the fingerprints of Brand A Stage 2 and 3 were compared with those of two of the four brands, to distinguish the differences between brands. The NIR spectroscopy fingerprinting results showed that the Brand A formula can be completely differentiated from the other brands at each stage. The combination of NIR spectroscopy fingerprinting and PCA is an effective method for the purpose of confirmation of brand identification and brand protection in infant formulas.

Model-Based Scale-Up Methodologies for Pharmaceutical Granulation

In the pharmaceutical industry, it is a major challenge to maintain consistent quality of drug products when the batch scale of a process is changed from a laboratory scale to a pilot or commercial scale. Generally, a pharmaceutical manufacturing process involves various unit operations, such as blending, granulation, milling, tableting and coating and the process parameters of a unit operation have significant effects on the quality of the drug product. Depending on the change in batch scale, various process parameters should be strategically controlled to ensure consistent quality attributes of a drug product. In particular, the granulation may be significantly influenced by scale variation as a result of changes in various process parameters and equipment geometry. In this study, model-based scale-up methodologies for pharmaceutical granulation are presented, along with data from various related reports. The first is an engineering-based modeling method that uses dimensionless numbers based on process similarity. The second is a process analytical technology-based modeling method that maintains the desired quality attributes through flexible adjustment of process parameters by monitoring the quality attributes of process products in real time. The third is a physics-based modeling method that involves a process simulation that understands and predicts drug quality through calculation of the behavior of the process using physics related to the process. The applications of these three scale-up methods are summarized according to granulation mechanisms, such as wet granulation and dry granulation. This review shows that these model-based scale-up methodologies provide a systematic process strategy that can ensure the quality of drug products in the pharmaceutical industry.

Moisture Monitoring in Fluid-Bed Granulation by Multi-Resonance Microwave Sensor: Applicability on Crystal-Water Containing Donepezil Granules

Multi-resonance microwave sensors have recently been introduced for moisture monitoring of pharmaceutical particulates up to > 20% residual moisture. The extended measuring range compared to previous systems as well as the microwave moisture values independent of other physical attributes make them promising process analytical technology (PAT) tools for various pharmaceutical production processes. However, so far, research focused on measurements on raw materials or drug-free model granulates and has neither evaluated the applicability for materials with crystal water containing excipients nor for active ingredients. In this study, possible influence of crystal water was evaluated using lactose monohydrate and donepezil hydrochloride, an active pharmaceutical ingredient (API) against dementia. The study clearly showed that the contained hydrate does not cause interferences and is not monitored by the applied frequencies. Material-related limits measuring lactose monohydrate were only observed above typical granulation moistures and could be explained using raw resonance curves. Furthermore, the inclusion of donepezil hydrochloride into the monitored formulations and varied process parameters demonstrated the versatility of the microwave resonance sensor system. Inlet air temperature, spraying rate, and air flow were varied according to a 2³ full factorial experimental design. A predictive model (R² = 0.9699, RMSEC = 0.33%) could be established using samples produced with different process parameter settings adjusted according to the corner points of the full factorial design and validated on the center point granulation processes (RMSEV = 0.38%). Thereby, performance on actual formulations and conditions faced during process development could be thoroughly assessed, and hence, another key requirement for applicability in formulation development could be met.

Process analytical technologies and injectable drug products: Is there a future?

Parametric release was the first subset of real time release testing (RTRT), applied to terminally sterilised injectable drug products. The objective was to offer the industry an alternative to the time and money consuming sterility testing, without compromising the sterility of the products. The rationale was that quality cannot be tested into products, instead it must be planned (the principle of quality by design, QbD). This can be implemented by setting appropriate in-process controls supported on process analytical technologies (PAT). Two of the most versatile and promising PAT tools are the near infrared spectroscopy (NIRS) and the Raman spectroscopy. However, their application to injectable drug product development and manufacturing has been scarce. This review has the objective to provide a framework for the practical implementation of the QbD approach to injectable formulations, including application of diverse risk assessment and factorial design tools. Finally, the actual application of PAT, namely NIRS and Raman spectroscopy, to injectable drug product analysis is addressed.

Accuracy Improvement of In-line Near-Infrared Spectroscopic Moisture Monitoring in a Fluidized Bed Drying Process

An exploratory analysis of a large representative dataset obtained in a fluidized bed drying process of a pharmaceutical powder has revealed a significant correlation of spectral intensity with granulate humidity in the whole studied range of 1091.8–2106.5 nm. This effect was explained by the dependence of powder refractive properties, and hence light penetration depth, on the water content. The phenomenon exhibited a close spectral similarity to the well-known stochastic variation of spectral intensities caused by the process turbulence (the so-called “scatter effect”). Therefore, any traditional scatter-corrective preprocessing incidentally eliminates moisture-correlated variance from the data. To preserve this additional information for a more precise moisture calibration, a time-domain averaging of spectral variables has been suggested. Its application resulted in a distinct improvement of prediction accuracy, as compared to the scatter-corrected data. Further improvement of the model performance was achieved by the application of a dynamic focusing strategy when adjusting the model to a drying process stage. Probe fouling was shown to have a minor effect on prediction accuracy. The study resulted in a considerable reduction of the root-mean-square error of in-line moisture monitoring to 0.1%, which is close to the reference method's reproducibility and significantly better than previously reported results.

Real-time process monitoring in a semi-continuous fluid-bed dryer - microwave resonance technology versus near-infrared spectroscopy

The trend towards continuous manufacturing in the pharmaceutical industry is associated with an increasing demand for advanced control strategies. It is a mandatory requirement to obtain reliable real-time information on critical quality attributes (CQA) during every process step as the decision on diversion of material needs to be performed fast and automatically. Where possible, production equipment should provide redundant systems for in-process control (IPC) measurements to ensure continuous process monitoring even if one of the systems is not available. In this paper, two methods for real-time monitoring of granule moisture in a semi-continuous fluid-bed drying unit are compared. While near-infrared (NIR) spectroscopy has already proven to be a suitable process analytical technology (PAT) tool for moisture measurements in fluid-bed applications, microwave resonance technology (MRT) showed difficulties to monitor moistures above 8% until recently. The results indicate, that the newly developed MRT sensor operating at four resonances is capable to compete with NIR spectroscopy. While NIR spectra were preprocessed by mean centering and first derivative before application of partial least squares (PLS) regression to build predictive models (RMSEP = 0.20%), microwave moisture values of two resonances sufficed to build a statistically close multiple linear regression (MLR) model (RMSEP = 0.07%) for moisture prediction. Thereby, it could be verified that moisture monitoring by MRT sensor systems could be a valuable alternative to NIR spectroscopy or could be used as a redundant system providing great ease of application.

Estimation of the critical quality attributes for hydroxypropyl methylcellulose with near-infrared spectroscopy and chemometrics

With the implementation of quality by design (QbD), critical attributes of raw material (drug substance and excipients) are of significantly importance in pharmaceutical manufacturing process. It is desirable for the quality control of critical material attributes (CMAs) of excipients to ensure the quality of end product. This paper explored the feasibility of an at-line method for the quantitative analysis of hydroxypropoxy group in hydroxypropyl methylcellulose (HPMC) with near infrared spectroscopy (NIRS). Hydroxypropoxy group content can be seen as a CMA of HPMC for quality control. The partial least squares (PLS) model was built with 61 samples including 47 samples as calibration set, 14 samples as validation set by sample set partitioning based on joint x-y distances (SPXY) method. Multiplicative scattering correction (MSC) combined with Savitzkye-Golay (SG) smoothing with first derivative was used as the appropriate pretreatment method. Three variable selection methods including interval partial least-squares (iPLS), competitive adaptive reweighted Sampling (CARS), and the combination of the two methods (iPLS-CARS) were performed for optimizing the model. The results indicated that NIRS could predict rapidly and effectively the content of hydroxypropoxy group in HPMC. NIRS could be a potential method for the quality control of CMAs.

Overall uncertainty measurement for near infrared analysis of cryptotanshinone in tanshinone extract

This study presented a new strategy of overall uncertainty measurement for near infrared (NIR) quantitative analysis of cryptotanshinone in tanshinone extract powders. The overall uncertainty of NIR analysis from validation data of precision, trueness and robustness study was fully investigated and discussed. Quality by design (QbD) elements, such as risk assessment and design of experiment (DOE) were utilized to organize the validation data. An "I×J×K" (series I, the number of repetitions J and level of concentrations K) full factorial design was used to calculate uncertainty from the precision and trueness data. And a 2(7-4) Plackett-Burmann matrix with four different influence factors resulted from the failure mode and effect analysis (FMEA) analysis was adapted for the robustness study. The overall uncertainty profile was introduced as a graphical decision making tool to evaluate the validity of NIR method over the predefined concentration range. In comparison with the T. Saffaj's method (Analyst, 2013, 138, 4677.) for overall uncertainty assessment, the proposed approach gave almost the same results, demonstrating that the proposed method was reasonable and valid. Moreover, the proposed method can help identify critical factors that influence the NIR prediction performance, which could be used for further optimization of the NIR analytical procedures in routine use.

Moisture determination of tritium tracers utilizing near-infrared spectroscopy

Tritium tracers are frequently used in biological assays during the drug discovery process because of their high specific activity and relative ease of synthesis. However, this high specific activity, along with other contributing factors, can lead to an increased rate of radiolytic decomposition. As a result, following long-term storage tritium tracers often require purification. Understanding the elements that cause radiolytic decomposition is extremely important to extend the storage life, and consequently reduce unnecessary inventory purifications. One of these elements is the presence of water in tritium tracers. Upon investigation, it was discovered that aside from the relatively common tritium/water exchange that could occur, residual water could also contribute significantly to the decomposition of tritium tracers. A near-infrared method was developed utilizing a portable device to measure the water content in tritium tracers rapidly and without sample destruction. This method proved to be quick, efficient, and achieved an error less than 5% compared to that of traditional Karl Fischer titration. Method validation was performed and good accuracy, linearity, limit of detection and quantitation were all established.

Tablet Velocity Measurement and Prediction in the Pharmaceutical Film Coating Process

The purpose of this study was to measure the tablet velocity in pan coating machines during the film coating process in order to understand the impact of the batch size (laboratory to commercial scale), coating machine type (DRIACOATER, HICOATER® and AQUA COATER®) and manufacturing conditions on tablet velocity. We used a high speed camera and particle image velocimetry to measure the tablet velocity in the coating pans. It was observed that increasing batch sizes resulted in increased tablet velocities under the same rotation number because of the differences in circumferential rotation speeds. We also observed the tendency that increase in the filling ratio of tablets resulted in an increased tablet velocity for all coating machines. Statistical analysis was used to make a tablet velocity predictive equation by employing the filling ratio and rotation speed as the parameters from these measured values. The correlation coefficients of predicted value and experimental value were more than 0.959 in each machine. Using the predictive equation to determine tablet velocities, the manufacturing conditions of previous products were reviewed, and it was found that the tablet velocities of commercial scales, in which tablet chipping and breakage problems had occurred, were higher than those of pilot scales or laboratory scales.

Multipoint near-infrared spectrometry for real-time monitoring of protein conformational stability in powdered infant formula

Powdered infant formula (PIF) can be the sole source of nutrition for babies and infants. Monitoring conformational changes in protein during manufacture of PIF is critical in order to maintain its nutritional value. This study presents the development of a calibration model for monitoring conformational changes in PIF protein by applying a novel multipoint near-infrared (NIR) spectrometry. NIR spectra were collected for PIF and PIF proteins, casein and whey protein isolate, before and after heat treatment. Results show that principal component analysis showed discrimination between native protein at room temperature and protein conformational changes caused at elevated temperature. Partial least squares regression analysis showed good calibration models with correlation coefficients ranging between 87% and 99% for the prediction of protein quality. This novel multipoint NIR spectrometry could serve as a simple in-line tool to rapidly monitor protein quality during processing stages, contributing to product nutritional value.

A novel microwave sensor for real-time online monitoring of roll compacts of pharmaceutical powders online--a comparative case study with NIR

Control of particulate processes is hard to achieve because of the ease with which powders tend to segregate. Thus, proper sensing methods must be employed to ensure content uniformity during operation. The role of sensing schemes becomes even more critical while operating the process continuously as measurements are essential for implementation of feedback control (Austin et al. 2013. J Pharm Sci 102(6):1895-1904; Austin et al. 2014. Anal Chim Acta 819:82-93). A microwave sensor was developed and shown to be effective in online measurement of active pharmaceutical ingredient (API) concentration in a powder blend. During powder transport and hopper storage before processing, powder blends may segregate and cause quality deviations in the subsequent tableting operation. Therefore, it is critical to know the API concentration in the ribbons as the content uniformity is fixed once the ribbon is processed. In this study, a novel microwave sensor was developed that could provide measurement of a roller compacted ribbon's API concentration online, along with its density and moisture content. The results indicate that this microwave sensor is capable of increased accuracy compared with a commercially available near-IR probe for the determination of content uniformity and density in roller compacted ribbons online.

The use of near-infrared and microwave resonance sensing to monitor a continuous roller compaction process

Roller compaction is commonly used in the pharmaceutical and nutraceutical industries to increase and narrow the size distribution of a particulate material, making it easier to process. Both the moisture content of the material and the density of the roller compacted ribbon affect the uniformity and physical properties of the resultant granules. Without process analytical technologies, these parameters cannot be determined on-line or in real time. In this study, the more commonly used near-infrared (NIR) spectroscopy was compared and contrasted with microwave resonance for the determination of roller-compacted ribbons' envelope density and moisture content. Results indicate that microwave resonance can offer improved accuracy, robustness, and ease-of-use compared with NIR spectroscopy for these property measurements.

Critical review of near-infrared spectroscopic methods validations in pharmaceutical applications

Based on the large number of publications reported over the past five years, near-infrared spectroscopy (NIRS) is more and more considered an attractive and promising analytical tool regarding Process Analytical Technology and Green Chemistry. From the reviewed literature, few of these publications present a thoroughly validated NIRS method even if some guidelines have been published by different groups and regulatory authorities. However, as any analytical method, the validation of NIRS method is a mandatory step at the end of the development in order to give enough guarantees that each of the future results during routine use will be close enough to the true value. Besides the introduction of PAT concepts in the revised document of the European Pharmacopoeia (2.2.40) dealing with near-infrared spectroscopy recently published in Pharmeuropa, it agrees very well with this mandatory step. Indeed, the latter suggests to use similar analytical performance characteristics than those required for any analytical procedure based on acceptance criteria consistent with the intended use of the method. In this context, this review gives a comprehensive and critical overview of the methodologies applied to assess the validity of quantitative NIRS methods used in pharmaceutical applications.

Simple modification of karl-Fischer titration method for determination of water content in colored samples

The most commonly used technique for water content determination is Karl-Fischer titration with electrometric detection, requiring specialized equipment. When appropriate equipment is not available, the method can be performed through visual detection of a titration endpoint, which does not enable an analysis of colored samples. Here, we developed a method with spectrophotometric detection of a titration endpoint, appropriate for moisture determination of colored samples. The reaction takes place in a sealed 4 ml cuvette. Detection is performed at 520 nm. Titration endpoint is determined from the graph of absorbance plotted against titration volume. The method has appropriate reproducibility (RSD = 4.3%), accuracy, and linearity (R(2) = 0.997).