THz-TDS as a PAT tool for monitoring blend homogeneity in pharmaceutical manufacturing of solid oral dosage forms: A proof-of-concept study.

The process analytical technology (PAT) framework is well established and integral to facilitate process understanding, enable a transition from batch to continuous manufacturing, and improve product quality. Near-infrared (NIR) spectroscopy has been established as a standard PAT tool for many process analytical challenges, including monitoring powder blend homogeneity. However, alternative technologies for monitoring powder blending are of interest due to the importance of the blending step in manufacturing solid oral dosage forms. Terahertz time-domain spectroscopy (THz-TDS) is therefore explored in this study as an alternative tool for monitoring blend homogeneity with the potential for endpoint control in a batch blending process. Powder blends of microcrystalline cellulose (MCC) and dibasic calcium phosphate dihydrate and blends of MCC and granulated α-lactose monohydrate were investigated non-invasively at various compositions using THz-TDS in transmission mode for acquiring spectra from samples enclosed in the blending container. It was found that attenuation- and phase-related parameters acquired with THz-TDS could reliably resolve physical changes related to the homogeneity of the blend. Further evaluations revealed that changes in the bulk density of the blend, in addition to the intrinsic optical properties of the materials, played a critical role in the observed trends for both systems. In contrast, the scattering contribution of the powder was mainly crucial for the attenuation-related parameter in blends with materials of high refractive indices. Finally, THz-TDS measurements were acquired throughout a blending process mimicking a continuous acquisition. The method could follow blending dynamics and resulted in reasonable predictive errors of the content of 0.5 - 2.5 %. Relative standard deviations for high content blends (20 %) were acceptable (3 - 7 %) whereas at low contents (5 %) significantly higher values (9 - 35 %) were found. Based on these findings, THz-TDS is a feasible PAT tool for monitoring blend homogeneity and controlling high content blend processes, although precision and accuracy is considered to improve with a more suitable interface.

Terahertz time-domain spectroscopy for the investigation of tablets prepared from roller compacted granules.

Roller compaction before tableting is a common unit operation to increase the processability of powders. Terahertz time-domain spectroscopy (THz-TDS) has recently been introduced as a potential process analytical technology (PAT) for measuring tablet porosity based on the refractive index of the tablet. Tablet porosity is a governing parameter for tablet disintegration and dissolution. The first aim of this study was to investigate tablets prepared from roller-compacted materials with THz-TDS to explore its usefulness for particle size evaluation of granules in tablets. Secondly, the impact of roller compaction and granule size before tablet compression on the established THz-TDS based measurement of tablet porosity was investigated. Microcrystalline cellulose and α-lactose monohydrate were roller compacted separately at five specific compaction forces (2, 4, 8, 12, and 16 kN cm-1) and fractionated into three size fractions. Tablets were prepared from the fractionated and unfractionated granules at twelve tableting pressures and subjected to THz-TDS transmission measurements. It was possible to use the scattering behaviour of the tablets at terahertz frequencies to describe the granulated materials' particle size changes during tableting. At the same time, prediction of porosity was impaired due to the deviation of the refractive index in strongly scattering samples. A correction method was introduced in which the porosity error was corrected based on the tablet's scattering behaviour, resulting in an improved prediction of tablet porosity. In conclusion, THz-TDS is considered a promising technique for the process monitoring of tableting based on its sensitivity to porosity and particle size changes within the tablet non-destructively, with a possible application as part of an in-process control strategy of the tableting of granulated or non-granulated materials.

In-line Fluorescence Spectroscopy for Quantification of Low Amount of Active Pharmaceutical Ingredient.

The pharmaceutical industry is currently implementing new manufacturing principles and modernizing the related processing solutions. A key element in this development is implementation of process analytical technologies (PAT) for measuring product quality in a real-time mode, ideally for a continuously operating processing line. Near-infrared (NIR) spectroscopy is widely used for this purpose, but has limited use for low concentration formulations, due to its inherent detection limit. Light-induced fluorescence (LIF) spectroscopy is a PAT tool that can be used to quantify low concentrations of active pharmaceutical ingredient, and recent development of instrumentation has made it available for in-line applications. In this study, the content of tryptophan in a dynamic powder flow could be measured as low as 0.10 w/w % with LIF spectroscopy with good accuracy of RMSEP = 0.008 w/w %. Both partial least squares regression and support vector machines (SVM) were investigated, but we found SVM to be the better option due to non-linearities between the calibration test and the in-line measurements. With the use of SVM, LIF spectroscopy is a promising candidate for low concentration applications where NIR is not suitable.

Sampling Error of TOC swab in Pharmaceutical Cleaning Verification.

Cleaning verification is a critical process for patient safety in pharmaceutical manufacturing in order to keep cross-contamination below acceptable limits. A common cleaning verification method is the total organic carbon (TOC) swab. Others have studied the variances of different factors on the TOC swab in order to establish the best swab method. This paper attempts to quantify the sampling error of the TOC swab in the actual sampling situation using simulation. The study investigates the variability on the drug product recovery due to different analysts, concentration, steel finish and position, as well as the estimation of the given swab area. The results demonstrate that the sampling error leads to a large variation in TOC results. For areas estimated in the laboratory, it leads to an increase in limit of detection, LOD, with 60%, while for areas estimated in a tank, the LOD cannot be determined due to the large heteroscedasticity. Thus, this paper is also to be considered as an invitation to discuss and further investigate the TOC sampling error in the pharmaceutical industry.

Determination of Residence Time Distribution in a Continuous Powder Mixing Process With Supervised and Unsupervised Modeling of In-line Near Infrared (NIR) Spectroscopic Data.

Successful implementation of continuous manufacturing processes requires robust methods to assess and control product quality in a real-time mode. In this study, the residence time distribution of a continuous powder mixing process was investigated via pulse tracer experiments using near infrared spectroscopy for tracer detection in an in-line mode. The residence time distribution was modeled by applying the continuous stirred tank reactor in series model for achieving the tracer (paracetamol) concentration profiles. Partial least squares discriminant analysis and principal component analysis of the near infrared spectroscopy data were applied to investigate both supervised and unsupervised chemometric modeling approaches. Additionally, the mean residence time for three powder systems was measured with different process settings. It was found that a significant change in the mean residence time occurred when comparing powder systems with different flowability and mixing process settings. This study also confirmed that the partial least squares discriminant analysis applied as a supervised chemometric model enabled an efficient and fast estimate of the mean residence time based on pulse tracer experiments.

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 label-free methodology for selective protein quantification by means of absorption measurements.

The application of high throughput experimentation (HTE) in protein purification process development has created an analytical bottleneck. Using a new label-free and non-invasive methodology for analyzing multicomponent protein mixtures by means of spectral measurements, we show that the analytical throughput for selective protein quantification can be increased significantly. An analytical assay based on this new methodology was shown to generate very precise results. Further, the assay was successfully applied as analytics for a resin screening performed in HTE mode. The increase in analytical throughput was obtained without decreasing the level of information when compared to analytical chromatography. This proves its potential as a valuable analytical tool in conjugation with high throughput process development (HTPD). Further, fast selective protein quantification can enhance process control in a commercial production environment and, hence, minimize the need for off-line release analysis.

Fast assessment of the surface distribution of API and excipients in tablets using NIR-hyperspectral imaging.

The inclusion of hyperspectral imaging systems in the manufacturing and development of pharmaceutical products is allowing a successful improvement in the quality control of solid dosage forms. The correct distribution not only of active pharmaceutical ingredient (API) but also of the rest of excipients is essential to assure the correct behavior of the tablet when ingested. This is especially relevant in tablets with low content of potent APIs, in which the prescribed intake dosage frequently corresponds to half-a-tablet. Therefore, the aim of this work is to study the surface distribution of the compounds in tablets with low API content. The proposed procedure includes the scanning of the tablet surface using near infrared hyperspectral spectroscopy in association with multivariate curve resolution (MCR) techniques to obtain selective pictures for each individual compound and to allow the fast assessment of their distribution in the measured surface. As an example, a set of commercial Lorazepam tablets (approximately 1% mass fraction of API, and four excipients) were analyzed. The results obtained show the capacity of the proposed methodology as an expedite approach to evaluate the uniformity of the contents between and within tablets. A method to estimate the homogeneity distribution of API in the two halves of the tablet is also proposed.

Rapid solid-state analysis of freeze-dried protein formulations using NIR and Raman spectroscopies.

Noninvasive near-infrared (NIR) and Raman spectroscopies were applied to provide a fast and efficient insight into the formation of different mannitol solid forms occurring in freeze-dried formulations. Multivariate data analysis clearly showed the formation of δ-mannitol in the presence of protein, whereas ß-mannitol was observed in the absence of protein.The multivariate analysis of the NIR spectra also gave an indication for the formation of mannitol hemihydrate in the absence of protein. Spectroscopic techniques in combination with multivariate analysis can be applied for fast screening and identification of excipient solid-state properties in pharmaceutical formulations.

Towards a robust water content determination of freeze-dried samples by near-infrared spectroscopy.

The possibility for determination of the water content in pharmaceutical samples by near-infrared (NIR) spectroscopy has been more widely investigated in the past few years. However, many studies claim that changes in sample composition will require the establishment of a new method. The aim of this study was several fold: firstly to investigate validation aspects of water content determination in samples with varying composition and furthermore to see if a model based solely on freeze-dried mannitol-sucrose mixtures can be established that will be able to predict water contents for samples containing proteins, excipients or having a lower density of freeze-dried solids. Samples were measured by NIR, standard normal variate (SNV) corrected and the obtained spectra were compared with the results from a conventional Karl-Fischer titration by means of multivariate analysis, namely principal component analysis (PCA) and partial least square regression (PLS). For the overall sample set, a highly linear correlation between the NIR and the Karl-Fischer method with a slope of 1.00, an R(2) value of 0.98 and a root mean square error of cross-validation (RMSECV) of 0.15% were found. In a second step samples solely consisting of mannitol and sucrose mixtures were used to build a calibration set, which resulted in a RMSECV of 0.16%. The prediction of the remaining samples, which included protein or excipient containing samples, as well as lower density samples, resulted in a root mean square error of prediction (RMSEP) of 0.19%. Thus the present study demonstrated, that a general model for the determination of the water content by NIR could be established, within the limits investigated.

Classification of lyophilised mixtures using multivariate analysis of NIR spectra.

Excipient selection is critically affecting the processing and the stability of a lyophilised product. Near infra-red (NIR) spectroscopy was applied to investigate freeze-dried samples containing varying ratios of the commonly used excipients mannitol and sucrose. Further variation in the formulation was achieved by adding NaCl, CaCl(2) and histidine and by exposing the samples to different conditions. Untreated NIR spectra are strongly affected by the physical nature of samples and can thus be useful for detecting production outliers. Applying standard normal variate (SNV) transformation highlights chemical information. The obtained NIR spectra of the freeze-dried samples were clustered by principal component analysis (PCA) after applying SNV correction in the range from 4200 to 7400cm(-1) (1350-2380nm). Relative humidity under storage and the mannitol/sucrose ratio were clearly represented in the first two principal components, while influence of other excipients was observed in the 3rd and 4th principal component. It was investigated whether this could be due to an influence of the excipients on the mannitol crystallisation behavior. Performing PCA with two principal components of SNV-corrected spectra in the range 4200-4500cm(-1) (2220-1380nm) led to the following observation: while the 1st principal component closely resembled the spectra of beta-mannitol, the 2nd principal component contained additional features that were not attributable to beta-mannitol but correlated well to the main absorbance band of delta-mannitol and mannitol hemihydrate. Therefore, it seems feasible that NIR can analyse versatile freeze-dried samples and classify these according to composition, water content and solid-state properties.

Role of excipients in the quantification of water in lyophilised mixtures using NIR spectroscopy.

The ratio between mannitol and sucrose in a freeze-dried formulation has a major impact on the processing and the stability of a lyophilised product. The ratio of these common excipients influences a critical quality attribute of the system, namely the overall amount of water, due to the different nature of their water-solid interactions. For this experiment samples containing various ratios of mannitol and sucrose and several other additives were freeze-dried, stored under different conditions and measured by NIR. Different spectral pre-processing methods and wavelength selections were tested. Multivariate analysis was applied to correlate the Karl Fischer titration to the NIR spectra. It was found that standard normal variate (SNV) transformation of the wavenumber range 4200-7400 cm(-1) yielded prediction errors close to the accepted measurement error of the Karl Fischer titration, when measuring samples of up to 5.5% (w/w) water. It was further found that there was a slight tendency for samples containing inorganic salts or histidine to be underestimated in the NIR measurements. However, no influence was found to be caused by the varying mannitol-sucrose ratio. By reducing the sample set to those samples containing up to around 2% of water, the error was found to be below the uncertainty originating from the reference method. Due to this it can no longer be determined whether the deviation originates from the NIR method or the reference method. It can therefore be concluded the NIR is a suitable tool for quantification of the water content in lyophilised samples with varying mannitol-sucrose ratios.

Near-infrared chemical imaging (NIR-CI) on pharmaceutical solid dosage forms-comparing common calibration approaches.

Near-infrared chemical imaging (NIR-CI) is the fusion of near-infrared spectroscopy and image analysis. It can be used to visualize the spatial distribution of the chemical compounds in a sample (providing a chemical image). Each sample measurement generates a hyperspectral data cube containing thousands of spectra. An important part of a NIR-CI analysis is the data processing of the hyperspectral data cube. The aim of this study was to compare the ability of different commonly used calibration methods to generate accurate chemical images. Three common calibration approaches were compared: (1) using single wavenumber, (2) using classical least squares regression (CLS) and (3) using partial least squares regression (PLS1). Each method was evaluated using two different preprocessing methods. A calibration data set of tablets with five constituents was used for analysis. Chemical images of the active pharmaceutical ingredient (API) and the two major excipients cellulose and lactose in the formulation were made. The accuracy of the generated chemical images was evaluated by the concentration prediction ability. The most accurate predictions for all three compounds were generated by PLS1. The drawback of PLS1 is that it requires a calibration data set and CLS, which does not require a calibration data set, therefore proved to be an excellent alternative. CLS also generated accurate predictions and only requires the pure compound spectrum of each constituent in the sample. All three calibration approaches were found applicable for hyperspectral image analysis but their relevance of use depends on the purpose of analysis and type of data set. As expected, the single wavenumber method was primarily found useful for compounds with a distinct spectral band that was not overlapped by bands of other constituents. This paper also provides guidance for hyperspectral image (or NIR-CI) analysis describing each of the typical steps involved.