Use of the near-infrared reflectance method for measurement of moisture content during granulation

The Use of Near-infrared as Process Analytical Technology (PAT) during 3D Printing Tablets at the Point-of-Care

Fused deposition modelling (FDM) is one of the most researched 3D printing technologies that holds great potential for low-cost manufacturing of personalised medicine. To achieve real-time release, timely quality control is a major challenge for applying 3D printing technologies as a point-of-care (PoC) manufacturing approach. This work proposes the use of a low-cost and compact near-infrared (NIR) spectroscopy modality as a process analytical technology (PAT) to monitor a critical quality attribute (drug content) during and after FDM 3D printing process. 3D printed caffeine tablets were used to manifest the feasibility of the NIR model as a quantitative analytical procedure and dose verification method. Caffeine tablets (0-40% w/w) were fabricated using polyvinyl alcohol and FDM 3D printing. The predictive performance of the NIR model was demonstrated in linearity (correlation coefficient, R²) and accuracy (root mean square error of prediction, RMSEP). The actual drug content values were determined using the reference high-performance liquid chromatography (HPLC) method. The model of full-completion caffeine tablets demonstrated linearity (R² = 0.985) and accuracy (RMSEP =1.4%), indicated to be an alternative dose quantitation method for 3D printed products. The ability of the models to assess caffeine contents during the 3D printing process could not be accurately achieved using the model built with complete tablets. Instead, by building a predictive model for each completion stage of 20%, 40%, 60% and 80%, the model of different completion caffeine tablets displayed linearity (R² of 0.991, 0.99, 0.987, and 0.983) and accuracy (RMSEP of 2.22%, 1.65%, 1.41%, 0.83%), respectively. Overall, this study demonstrated the feasibility of a low NIR model as a non-destructive, low-cost, compact, and rapid analysis dose verification method enabling the real-time release to facilitate 3D printing medicine production in the clinic.

Prediction Performance and Economic Efficiency of Soft Sensors for in-Line Water Content Monitoring in Fluidized Bed Granulation: PP-Based Model vs. NIRS-Based Model

Soft sensors play a crucial role as process analytical technology (PAT) tools. They are classified into physical models, statistical models, and their hybrid models. In general, statistical models are better estimators than physical models. In this study, two types of standard statistical models using process parameters (PPs) and near-infrared spectroscopy (NIRS) were investigated in terms of prediction accuracy and development cost. Locally weighted partial least squares regression (LW-PLSR), a type of nonlinear regression method, was utilized. Development cost was defined as the cost of goods required to construct an accurate model of commercial-scale equipment. Eleven granulation lots consisting of three laboratory-scale, two pilot-scale, and six commercial-scale lots were prepared. Three commercial-scale granulation lots were selected as a validation dataset, and the remaining eight granulation lots were utilized as calibration datasets. The results demonstrated that the PP-based and NIRS-based LW-PLSR models achieved high prediction accuracy without using the commercial-scale data in the calibration dataset. This practical case study clarified that the construction of accurate LW-PLSR models requires the calibration samples with the following two features: 1) located near the validation samples on the subspace spanned by principal components (PCs), and 2) having a wide range of variations in PC scores. In addition, it was confirmed that the reduction in cost and mass fraction of active pharmaceutical ingredient (API) made the PP-based models more cost-effective than the NIRS-based models. The present work supports to build accurate models efficiently and save the development cost of PAT.

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.

Scale-Free Soft Sensor for Monitoring of Water Content in Fluid Bed Granulation Process

In-line monitoring of granule water content during fluid bed granulation is important to control drug product qualities. In this study, a practical scale-free soft sensor to predict water content was proposed to cope with the manufacturing scale changes in drug product development. The proposed method exploits two key ideas to construct a scale-free soft sensor. First, to accommodate the changes in the manufacturing scale, the process parameters (PPs) that are critical to water content at different manufacturing scales were selected as input variables. Second, to construct an accurate statistical model, locally weighted partial least squares regression (LW-PLSR), which can cope with collinearity and nonlinearity, was utilized. The soft sensor was developed using both laboratory (approx. 4 kg) data and pilot (approx. 25 kg) scale data, and the prediction accuracy in the commercial (approx. 100 kg) scale was evaluated based on the assumption that the process was scaled-up from the pilot scale to the commercial scale. The developed soft sensor exhibited a high prediction accuracy, which was equivalent to the commonly used near-infrared (NIR) spectra-based method. The proposed method requires only standard instruments; therefore, it is expected to be a cost-effective alternative to the NIR spectra-based method.

Fluidised bed granulation of two APIs: QbD approach and development of a NIR in-line monitoring method

The study focused on the fluid-bed granulation process of a product with two active pharmaceutical ingredients, intended for coated tablets preparation and further transfer to industrial scale. The work aimed to prove that an accurate control of the critical granulation parameters can level the input material variability and offer a user-friendly process control strategy. Moreover, an in-line Near-Infrared monitoring method was developed, which offered a real time overview of the moisture level along the granulation process, thus a reliable supervision and control process analytical technology (PAT) tool. The experimental design's results showed that the use of apparently interchangeable active pharmaceutical ingredients (APIs) and filler sorts that comply with pharmacopoeial specifications, lead to different end-product critical attributes. By adapting critical granulation parameters (i.e. binder spray rate and atomising pressure) as a function of material characteristics, led to granules with average sizes comprised in a narrow range of 280–320 µm and low non-granulated fraction of under 5%. Therefore, the accurate control of process parameters according to the formulation particularities achieved the maintenance of product within the design space and removed material related variability. To complete the Quality by design (QbD) strategy, despite its limited spectral domain, the microNIR spectrometer was successfully used as a robust PAT monitoring tool that offered a real time overview of the moisture level and allowed the supervision and control of the granulation process.

Trends in Process Analytical Technology: Present State in Bioprocessing

Process analytical technology (PAT), the regulatory initiative for incorporating quality in pharmaceutical manufacturing, is an area of intense research and interest. If PAT is effectively applied to bioprocesses, this can increase process understanding and control, and mitigate the risk from substandard drug products to both manufacturer and patient. To optimize the benefits of PAT, the entire PAT framework must be considered and each elements of PAT must be carefully selected, including sensor and analytical technology, data analysis techniques, control strategies and algorithms, and process optimization routines. This chapter discusses the current state of PAT in the biopharmaceutical industry, including several case studies demonstrating the degree of maturity of various PAT tools. Graphical Abstract Hierarchy of QbD components.

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.

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.

Near-infrared spectroscopy monitoring and control of the fluidized bed granulation and coating processes-A review

The fluidized bed granulation and pellets coating technologies are widely used in pharmaceutical industry, because the particles made in a fluidized bed have good flowability, compressibility, and the coating thickness of pellets are homogeneous. With the popularization of process analytical technology (PAT), real-time analysis for critical quality attributes (CQA) was getting more attention. Near-infrared (NIR) spectroscopy, as a PAT tool, could realize the real-time monitoring and control during the granulating and coating processes, which could optimize the manufacturing processes. This article reviewed the application of NIR spectroscopy in CQA (moisture content, particle size and tablet/pellet thickness) monitoring during fluidized bed granulation and coating processes. Through this review, we would like to provide references for realizing automated control and intelligent production in fluidized bed granulation and pellets coating of pharmaceutical industry.

Real-time release monitoring for water content and mean particle size of granules in lab-sized fluid-bed granulator by near-infrared spectroscopy

Simultaneous real-time monitoring of water content and mean particle size in the powder bed of a fluidized-bed granulator was performed by near-infrared (NIR) spectroscopy through a window, and the findings were used to evaluate the granular properties.

On-line application of near-infrared spectroscopy for monitoring water levels in parts per million in a manufacturing-scale distillation process

An on-line analytical method based on transmission near-infrared spectroscopy (NIRS) for the quantitative determination of water concentrations (in parts per million) was developed and applied to the manufacture of a pharmaceutical intermediate. Calibration models for water analysis, built at the development site and applied at the manufacturing site, were successfully demonstrated during six manufacturing runs at a 250-gallon scale. The water measurements will be used as a forward-processing control point following distillation of a toluene product solution prior to use in a Grignard reaction. The most significant impact of using this NIRS-based process analytical technology (PAT) to replace off-line measurements is the significant reduction in the risk of operator exposure through the elimination of sampling of a severely lachrymatory and mutagenic compound. The work described in this report illustrates the development effort from proof-of-concept phase to manufacturing implementation.

Low level drug product API form analysis - Avalide tablet NIR quantitative method development and robustness challenges

Avalide(@), a medication used for the treatment of hypertension, is a combination of Irbesartan, and Hydrochlorothiazide. Irbesartan, one of the active pharmaceutical ingredients (API) in Avalide products, exists in two neat crystalline forms: Form A and Form B. Irbesartan Form A is the API form used in a wet granulation for the preparation of Avalide tablets. The presence of the less soluble Irbesartan Form B in Avalide tablets may result in the slower dissolution. In this paper, we have presented our work on the method development, verification and challenges of quantitatively detecting, via NIR and ssNMR, very small amounts of Irbesartan Form B in Avalide tablets. As part of the NIR method development and qualification, limit of detection, linearity and accuracy were examined. In addition, a limited study of the robustness of the method was conducted and a bias in the level of Form B was correlated to the ambient humidity. ssNMR, a primary method for the determination of polymorphic composition, was successfully used as an orthogonal technique to verify the accuracy of the NIR method and added to the confidence in the NIR method. The speed and efficiency of the NIR method make it a suitable and convenient tool for routine analysis of Avalide tablets for Form B in a QC environment.

Application of in-line near infrared spectroscopy and multivariate batch modeling for process monitoring in fluid bed granulation

Fluid bed is an important unit operation in pharmaceutical industry for granulation and drying. To improve our understanding of fluid bed granulation, in-line near infrared spectroscopy (NIRS) and novel environmental temperature and RH data logger called a PyroButton(®) were used in conjunction with partial least square (PLS) and principal component analysis (PCA) to develop multivariate statistical process control charts (MSPC). These control charts were constructed using real-time moisture, temperature and humidity data obtained from batch experiments. To demonstrate their application, statistical control charts such as Scores, Distance to model (DModX), and Hotelling's T(2) were used to monitor the batch evolution process during the granulation and subsequent drying phase; moisture levels were predicted using a validated PLS model. Two data loggers were placed one near the bottom of the granulator bowl plenum where air enters the granulator and another inside the granulator in contact with the product in the fluid bed helped to monitor the humidity and temperature levels during the granulation and drying phase. The control charts were used for real time fault analysis, and were tested on normal batches and on three batches which deviated from normal processing conditions. This study demonstrated the use of NIRS and the use of humidity and temperature data loggers in conjunction with multivariate batch modeling as an effective tool in process understanding and fault determining method to effective process control in fluid bed granulation.

Near infrared spectroscopy in the development of solid dosage forms

The use of near infrared (NIR) spectroscopy has rapidly grown partly due to demands of process analytical applications in the pharmaceutical industry. Furthermore, newest regulatory guidelines have advanced the increase of the use of NIR technologies. The non-destructive and non-invasive nature of measurements makes NIR a powerful tool in characterization of pharmaceutical solids. These benefits among others often make NIR advantageous over traditional analytical methods. However, in addition to NIR, a wide variety of other tools are naturally also available for analysis in pharmaceutical development and manufacturing, and those can often be more suitable for a given application. The versatility and rapidness of NIR will ensure its contribution to increased process understanding, better process control and improved quality of drug products. This review concentrates on the use of NIR spectroscopy from a process research perspective and highlights recent applications in the field.

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.

Granule Characterization During Fluid Bed Drying by Development of a Near Infrared Method to Determine Water Content and Median Granule Size

PURPOSE

Water content and granule size are recognized as critical process and product quality parameters during drying. The purpose of this study was to enlighten the granule behavior during fluid bed drying by monitoring the major events i.e. changes in water content and granule size.

METHODS

NIR spectra collected during drying and water content of sampled granules were correlated by principal component analysis (PCA) and partial least squares regression (PLSR). NIR spectra of dried granules were correlated to median granule size in a second PCA and PLSR.

RESULTS

The NIR water model discriminates between various stages in fluid-bed drying. The water content can be continuously predicted with errors comparable to the reference method. The four PLS factors of the granule size model are related to primary particle size of lactose, median granule size exceeding primary particle size and amorphous content of granules. The small prediction errors enable size discrimination between fines and granules.

CONCLUSION

For product quality reasons, discrimination between drying stages and end-point monitoring is highly important. Together with the possibilities to determine median granule size and to distinguish fines this approach provides a tool to design an optimal drying process.

Process analytical technology case study part I: feasibility studies for quantitative near-infrared method development

This article is the first of a series of articles detailing the development of near-infrared (NIR) methods for solid-dosage form analysis. Experiments were conducted at the Duquesne University Center for Pharmaceutical Technology to qualify the capabilities of instrumentation and sample handling systems, evaluate the potential effect of one source of a process signature on calibration development, and compare the utility of reflection and transmission data collection methods. A database of 572 production-scale sample spectra was used to evaluate the interbatch spectral variability of samples produced under routine manufacturing conditions. A second database of 540 spectra from samples produced under various compression conditions was analyzed to determine the feasibility of pooling spectral data acquired from samples produced at diverse scales. Instrument qualification tests were performed, and appropriate limits for instrument performance were established. To evaluate the repeatability of the sample positioning system, multiple measurements of a single tablet were collected. With the application of appropriate spectral preprocessing techniques, sample repositioning error was found to be insignificant with respect to NIR analyses of product quality attributes. Sample shielding was demonstrated to be unnecessary for transmission analyses. A process signature was identified in the reflection data. Additional tests demonstrated that the process signature was largely orthogonal to spectral variation because of hardness. Principal component analysis of the compression sample set data demonstrated the potential for quantitative model development. For the data sets studied, reflection analysis was demonstrated to be more robust than transmission analysis.

In-Line Monitoring of Moisture Content in Fluid Bed Dryers Using Near-IR Spectroscopy with Consideration of Sampling Effects on Method Accuracy

In-line near-IR moisture monitoring of the dynamic, fluid bed drying environment has been reported in recent years by several research groups; however, analytical figures of merit with regard to prediction accuracy are discussed in only a subset of this work, and issues with sampling and sample presentation are scarcely addressed at all. In this study, experiments were performed at 65-, 300-, and 600-L drying scales using several different sampling configurations in an effort to better understand and improve in-line near-IR method accuracy. Findings from this work demonstrate that process heterogeneity plays a major role in determination of apparent prediction accuracy. This aspect is general to all in-line measurements and plays an especially important role in solids and slurry systems that are prone to heterogeneity. In addition to experimental results, simulations based on these findings and sampling theory demonstrate an interesting paradox: depending on the sampling configuration employed, the method with the smallest apparent error is not necessarily optimal for process monitoring and control. Furthermore, sampling configuration influences the number of samples necessary to define an adequate calibration set. Finally, process understanding that was gained as a result of temporally rich, in-line measurements will be presented.

Determination of fluidized bed granulation end point using near‐infrared spectroscopy and phenomenological analysis

Simultaneous real-time monitoring of particle size and moisture content by near-infrared spectroscopy through a window into the bed of a fluidized bed granulator is used to determine the granulation end point. The moisture content and particle size determined by the near-infrared monitor correlates well with off-line moisture content and particle size measurements. The measured particle size is modeled using a population balance approach, and the moisture content is shown to follow accepted models during drying. Given a known formulation, with predefined parameters for peak moisture content, final moisture content, and final granule size, the near-infrared monitoring system can be used to control a fluidized bed granulation by determining when binder addition should be stopped and when drying of the granules is complete.

Determination and differentiation of surface and bound water in drug substances by near infrared spectroscopy

Near infrared spectroscopy (NIRS) was utilized to determine the water content during the drying of a drug substance with Karl Fisher titration as the reference measurement. NIRS calibration models were built with Partial Least Squares (PLS) regression based on spectral region of 1822-1948 nm for samples with 1-40% (w/w) water from five batches. A standard error of prediction (SEP) of 1.85% (w/w) was obtained from validation of the model with additional batches. A second NIRS calibration model using PLS was constructed in the region of 1-10% (w/w) water with samples from the same five calibration batches. This calibration model improved the accuracy of the prediction in the critical region around the end point of drying and provided a standard error of prediction 0.42% (w/w). In addition, direct spectral analyses with Principal Component Analysis (PCA) and peak ratios were applied to distinguish between surface (unbound) water and bound water incorporated into the crystal lattice of the drug substance. Direct spectral analysis indicated the existence of significant numerical and graphical differences between samples containing both surface and bound water, and those containing bound water only. Applying this method to monitor an actual drying process with the graphical assistance of spectral analysis, the drying process can be controlled, and the end point of drying clearly determined to ensure the desired hydrate form of the product. This study has demonstrated the in-line monitoring capability of NIRS to differentiate the surface and bound water simultaneously in addition to the determination of the water level.