Vibrational spectrometry for the assessment of active substance in metoprolol tablets: a comparison between transmission and diffuse reflectance near-infrared spectrometry

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.

A Comparative Approach to Screen the Capability of Raman and Infrared (Mid- and Near-) Spectroscopy for Quantification of Low-Active Pharmaceutical Ingredient Content Solid Dosage Forms: The Case of Alprazolam

Content uniformity is a critical attribute for potent and low-dosage formulations of active pharmaceutical ingredient (API) that, in addition to the formulation parameters, plays pivotal role during pharmaceutical development and production. However, when API content is low, implementing a vibrational spectroscopic analytical tool to monitor the content and blend uniformity remains a challenging task. The aim of this study was to showcase the potentials of mid-infrared (MIR), near-infrared (NIR), and Raman spectroscopy for quantitative analysis of alprazolam (ALZ) in a low-content powder blends with lactose, which is used as a common diluent for tablets produced by direct compression. The offered approach might be further scaled up and exploited for potential application in the process analytical technology (PAT). Partial least square and orthogonal PLS (OPLS) methodologies were employed to build the calibration models from raw and processed spectral data (standard normal variate, first and second derivatives). The models were further compared regarding their main statistical indicators: correlation coefficients, predictivity, root mean square error of estimation (RMSEE), and root mean square error of cross-validation (RMSEEcv). All statistical models presented high regression and predictivity coefficients. The RMSEEcv for the optimal models was 1.118, 0.08, and 0.059% for MIR, NIR, and Raman spectroscopy, respectively. The scarce information content extracted from the ALZ NIR spectra and the major band overlapping with those from lactose monohydrate was the main culprit of poor accuracy in the NIR model, whereas the subsampling instrumental setup (resulting in a non-representative spectral acquisition of the sample) was regarded as a main limitation for the MIR-based calibration model. The OPLS models of the Raman spectra of the powder blends manifested favorable statistical indicators for the accuracy of the calibration model, probably due to the distinctive ALZ Raman pattern resulting in the largest number of predictive spectral points that were used for the mathematical modeling. Furthermore, the Raman scattering calibration model was optimized in narrower scanning range (1700-700 cm^-1) and its prediction power was evaluated (root mean square error of prediction, RMSEP = 0.03%). Thus, the Raman spectroscopy presented the most favorable statistical indicators in this comparative study and therefore should be further considered as a PAT for the quantitative determination of ALZ in low-content powder blends.

Compilation of a Near-Infrared Library for Construction of Quantitative Models of Oral Dosage Forms for Amoxicillin and Potassium Clavulanate

The accuracy of quantitative models for near-infrared (NIR) spectroscopy is dependent upon calibration samples with concentration variations. Conventional sample-collection methods have shortcomings (especially time-consumption), which creates a “bottleneck” in the application of NIR models for Process Analytical Technology (PAT) control. We undertook a study to solve the problem of sample collection for construction of NIR quantitative models. Amoxicillin and potassium clavulanate oral dosage forms (ODFs) were used as examples. The aim of this study was to find an approach to construct NIR quantitative models rapidly using a NIR spectral library based on the idea of a universal model. The NIR spectral library of amoxicillin and potassium clavulanate ODFs was defined and comprised the spectra of 377 batches of samples produced by 26 domestic pharmaceutical companies, including tablets, dispersible tablets, chewable tablets, oral suspensions, and granules. The correlation coefficient (r_T) was used to indicate the similarities of the spectra. The calibration sets of samples were selected from a spectral library according to the median r_T of the samples to be analyzed. The r_T of the samples selected was close to the median r_T. The difference in r_T of these samples was 1.0–1.5%. We concluded that sample selection was not a problem when constructing NIR quantitative models using a spectral library compared with conventional methods of determining universal models. Sample spectra with a suitable concentration range in NIR models were collected rapidly. In addition, the models constructed through this method were targeted readily.

Quantitation of drug content in a low dosage formulation by transmission near infrared spectroscopy

A transmission near infrared (NIR) spectroscopic method has been developed for the nondestructive determination of drug content in tablets with less than 1% weight of active ingredient per weight of formulation (m/m) drug content. Tablets were manufactured with drug concentrations of ∼0.5%, 0.7%, and 1.0% (m/m) and ranging in drug content from 0.71 to 2.51 mg per tablet. Transmission NIR spectra were obtained for 110 tablets that constituted the training set for the calibration model developed with partial least squares regression. The reference method for the calibration model was a validated UV spectrophotometric method. Several data preprocessing methods were used to reduce the effect of scattering on the NIR spectra and base the calibration model on spectral changes related to the drug concentration changes. The final calibration model included the spectral range from 11 216 to 8662 cm^-1 the standard normal variate (SNV), and first derivative spectral pretreatments. This model was used to predict an independent set of 48 tablets with a root mean standard error of prediction (RMSEP) of 0.14 mg, and a bias of only -0.05 mg per tablet. The study showed that transmission NIR spectroscopy is a viable alternative for nondestructive testing of low drug content tablets, available for the analysis of large numbers of tablets during process development and as a tool to detect drug agglomeration and evaluate process improvement efforts.

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.

Acquisition of reproducible transmission near-infrared (NIR) spectra of solid samples with inconsistent shapes by irradiation with isotropically diffused radiation using polytetrafluoroethylene (PTFE) beads

A bead-incorporated transmission scheme (BITS) has been demonstrated for collecting reproducible transmission near-infrared (NIR) spectra of samples with inconsistent shapes. Isotropically diffused NIR radiation was applied around a sample and the surrounding radiation was allowed to interact homogeneously with the sample for transmission measurement. Samples were packed in 1.40 mm polytetrafluoroethylene (PTFE) beads, ideal diffusers without NIR absorption, and then transmission spectra were collected by illuminating the sample-containing beads using NIR radiation. When collimated radiation was directly applied, a small portion of the non-fully diffused radiation (NFDR) propagated through the void space of the packing and eventually degraded the reproducibility. Pre-diffused radiation was introduced by placing an additional PTFE disk in front of the packing to diminish NFDR, which produced more reproducible spectral features. The proposed scheme was evaluated by analyzing two different solid samples: density determination for individual polyethylene (PE) pellets and identification of mining locality for tourmalines. Because spectral collection was reproducible, the use of the spectrum acquired from one PE pellet was sufficient to accurately determine the density of nine other pellets with different shapes. The differentiation of tourmalines, which are even more dissimilar in appearance, according to their mining locality was also feasible with the help of the scheme.

Variation in the transmission near-infrared signal with depth in turbid media

Transmission near-infrared (NIR) measurements of a 1 mm thick aspirin disk were made at different positions as it was moved through a stack of eight 0.5 mm thick disks of microcrystalline cellulose (Avicel). The magnitude of the first derivative of absorbance for the aspirin interlayer at 8934 cm(-1) was lower when the disk was placed at the top or bottom of the stack of Avicel disks, with the largest signal observed when the aspirin was positioned at the central positions. The variation in signal with depth is consistent with that observed previously for transmission Raman spectrometry. In both cases, the trend observed can be attributed to lower photon density at the air-sample interface, relative to the center of the sample, owing to loss of photons to the air. This results in a reduction in the number of photons absorbed or Raman photons generated and subsequently detected when the interlayer occupies a near-surface position.

Diffuser-incorporated transmission NIR measurement for reliable analysis of packed granular samples

A diffuser-incorporated transmission near-infrared (NIR) scheme that enables direct spectral collection of packed granular samples with reliable sample representation and reproducibility has been demonstrated. The analytical utility of this method has been evaluated for the determination of polyethylene (PE) pellet density and the discrimination of the geographical origin of rice samples. Based on the preliminary observation of transmission spectral features acquired from spherical polyoxymethylene (POM) packings composed of different particle sizes as well as packing thickness, a portion of the radiation was propagated through the void space in the packing without fully interacting with the POM pellets. This type of radiation, so-called non-fully interacted radiation (NFIR), adversely affected the sample representation as well as the reproducibility of transmission measurements. To maximize the interaction of NIR radiation with granular samples, a polytetrafluoroethylene (PTFE) diffuser was positioned in front of the sample packing to introduce isotropically diffused radiation into the sample. This diffuser-incorporated scheme resulted in highly reproducible transmission spectra for both packed granular samples. Consequently, the density determination of PE pellets as well as discrimination of rice samples according to geographical origin was more accurate using the proposed scheme.

Towards better process understanding: chemometrics and multivariate measurements in manufacturing of solid dosage forms

The manufacturing of tablets involves many unit operations that possess multivariate and complex characteristics. The interactions between the material characteristics and process related variation are presently not comprehensively analyzed due to univariate detection methods. As a consequence, current best practice to control a typical process is to not allow process-related factors to vary i.e. lock the production parameters. The problem related to the lack of sufficient process understanding is still there: the variation within process and material properties is an intrinsic feature and cannot be compensated for with constant process parameters. Instead, a more comprehensive approach based on the use of multivariate tools for investigating processes should be applied. In the pharmaceutical field these methods are referred to as Process Analytical Technology (PAT) tools that aim to achieve a thorough understanding and control over the production process. PAT includes the frames for measurement as well as data analyzes and controlling for in-depth understanding, leading to more consistent and safer drug products with less batch rejections. In the optimal situation, by applying these techniques, destructive end-product testing could be avoided. In this paper the most prominent multivariate data analysis measuring tools within tablet manufacturing and basic research on operations are reviewed.

NIR spectroscopy applications in the development of a compacted multiparticulate system for modified release

The purpose of this study was to utilize near-infrared spectroscopy and chemical imaging to characterize extrusion-spheronized drug beads, lipid-based placebo beads, and modified release tablets prepared from blends of these beads. The tablet drug load (10.5-19.5 mg) of theophylline (2.25 mg increments) and cimetidine (3 mg increments) could easily be differentiated using univariate analyses. To evaluate other tablet attributes (i.e., compression force, crushing force, content uniformity), multivariate analyses were used. Partial least squares (PLS) models were used for prediction and principal component analysis (PCA) was used for classification. The PLS prediction models (R (2) >0.98) for content uniformity of uncoated compacted theophylline and cimetidine beads produced the most robust models. Content uniformity data for tablets with drug content ranging between 10.5 and 19.5 mg showed standard error of calibration (SEC), standard error of cross-validation, and standard error of prediction (SEP) values as 0.31, 0.43, and 0.37 mg, and 0.47, 0.59, and 0.49 mg, for theophylline and cimetidine, respectively, with SEP/SEC ratios less than 1.3. PCA could detect blend segregation during tableting for preparations using different ratios of uncoated cimetidine beads to placebo beads (20:80, 50:50, and 80:20). Using NIR chemical imaging, the 80:20 formulations showed the most pronounced blend segregation during the tableting process. Furthermore, imaging was capable of quantitating the cimetidine bead content among the different blend ratios. Segregation testing (ASTM D6940-04 method) indicated that blends of coated cimetidine beads and placebo beads (50:50 ratio) also tended to segregate.

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.

Unlocking interpretation in near infrared multivariate calibrations by orthogonal partial least squares

Near infrared spectroscopy (NIR) was developed primarily for applications such as the quantitative determination of nutrients in the agricultural and food industries. Examples include the determination of water, protein, and fat within complex samples such as grain and milk. Because of its useful properties, NIR analysis has spread to other areas such as chemistry and pharmaceutical production. NIR spectra consist of infrared overtones and combinations thereof, making interpretation of the results complicated. It can be very difficult to assign peaks to known constituents in the sample. Thus, multivariate analysis (MVA) has been crucial in translating spectral data into information, mainly for predictive purposes. Orthogonal partial least squares (OPLS), a new MVA method, has prediction and modeling properties similar to those of other MVA techniques, e.g., partial least squares (PLS), a method with a long history of use for the analysis of NIR data. OPLS provides an intrinsic algorithmic improvement for the interpretation of NIR data. In this report, four sets of NIR data were analyzed to demonstrate the improved interpretation provided by OPLS. The first two sets included simulated data to demonstrate the overall principles; the third set comprised a statistically replicated design of experiments (DoE), to demonstrate how instrumental difference could be accurately visualized and correctly attributed to Wood's anomaly phenomena; the fourth set was chosen to challenge the MVA by using data relating to powder mixing, a crucial step in the pharmaceutical industry prior to tabletting. Improved interpretation by OPLS was demonstrated for all four examples, as compared to alternative MVA approaches. It is expected that OPLS will be used mostly in applications where improved interpretation is crucial; one such area is process analytical technology (PAT). PAT involves fewer independent samples, i.e., batches, than would be associated with agricultural applications; in addition, the Food and Drug Administration (FDA) demands "process understanding" in PAT. Both these issues make OPLS the ideal tool for a multitude of NIR calibrations. In conclusion, OPLS leads to better interpretation of spectrometry data (e.g., NIR) and improved understanding facilitates cross-scientific communication. Such improved knowledge will decrease risk, with respect to both accuracy and precision, when using NIR for PAT applications.

Evaluation of transmission and reflection modalities for measuring content uniformity of pharmaceutical tablets with near-infrared spectroscopy

This paper examines how one may assess spectral changes with instrument configuration (or composition), in combination with the spectral changes in the measurement that are caused by experimental effects, and subsequently select an appropriate measurement modality for tablet content uniformity determination with near-infrared (NIR) spectroscopy. Two NIR spectrometers furnished with three configurations in the sample measurement interface were evaluated. One spectrometer, Bruker MPA (multiple purpose analyzer), was equipped with two measurement modalities, diffuse transmission (DT) and diffuse reflection based on integrating sphere optics (DR/IS). The other spectrometer, Bruker StepOne, was equipped only with diffuse reflection mode based on a fiber-optic probe (DR/FO). The data were collected with each of the configurations for the tablets associated with two dosage strengths differing significantly in diameter and thickness. Spectral diagnosis was performed in terms of sensitivity and selectivity. The signal-to-noise ratio computed for the data collected with the DT and DR/IS spectrometers was approximately an order of magnitude greater than that computed for the DR/FO spectrometer. The net-analyte-signal-based selectivity analysis of NIR spectra associated with the sample tablet and the placebo tablet indicated that both transmission and reflection mode provided similar selectivity when the optimal spectral range was chosen. A partial least squares (PLS) calibration model was developed for each data set. The overall standard error of calibration for each DT and DR/IS measurement was approximately 0.3% in weight for each strength, significantly better than the value of 1.0% in weight produced by the DR/FO measurement. This result was consistent with the sensitivity analysis based on spectral noise characterization. The poor analytical performance of the DR/FO spectrometer was attributed to the small illumination spot size of the reflection probe and thus the sensitivity of the measurements to the tablet engraving. The PLS analysis and spectral diagnostics both showed that transmission and reflection modes based on the Bruker MPA provided similar measurement accuracy for each strength. However, the robustness study clearly revealed that the transmission mode would be more robust than the reflection mode when there is considerable variability in the chemical composition and physical properties of tablets.

Investigating dehydration from compacts using terahertz pulsed, Raman, and near-infrared spectroscopy

The purpose of this study was to investigate the dehydration of piroxicam monohydrate (PRXMH) in compacts using terahertz pulsed spectroscopy (TPS), Raman spectroscopy, and reflectance near-infrared (NIR) spectroscopy. Compacts were prepared by using PRXMH and poly(tetrafluoro)ethylene powders and combining them in three different manners before compression to produce compacts in which the PRXMH was dispersed throughout the compact, deposited on one face of the compact, or included as a layer within the compact. TPS was a suitable technique to assess the effect of sample preparation on dehydration, whereas Raman and NIR spectroscopy were limited by their sampling depth and the interference of the polymer matrix. TPS revealed that the dehydration behavior depended largely on the compact preparation method. Non-isothermal dehydration was investigated with all three spectroscopic techniques, combined with principal component analysis (PCA) on samples where the PRXMH was deposited on one face of the compact. In addition, variable temperature X-ray powder diffractometry (VT-XRPD) was used to verify the transformation from PRXMH to anhydrous PRX form I, while thermogravimetric analysis (TGA) was used to monitor the water loss. All three spectroscopic techniques allowed in situ monitoring of the dehydration from the surface layers of the compacts. TPS and Raman spectroscopy detected structural changes of the crystal, while NIR spectroscopy was more sensitive to water loss. PCA of the TPS, Raman spectroscopy, and XRPD data revealed similar dehydration profiles. In contrast, the NIR spectroscopy profile was more similar to the TGA results. The spectroscopic techniques were more suitable than slower techniques such as VT-XRPD for monitoring rapid structural changes that occurred during the dehydration.

Quantitative transmission Raman spectroscopy of pharmaceutical tablets and capsules

Quantitative analysis of pharmaceutical formulations using the new approach of transmission Raman spectroscopy has been investigated. For comparison, measurements were also made in conventional backscatter mode. The experimental setup consisted of a Raman probe-based spectrometer with 785 nm excitation for measurements in backscatter mode. In transmission mode the same system was used to detect the Raman scattered light, while an external diode laser of the same type was used as excitation source. Quantitative partial least squares models were developed for both measurement modes. The results for tablets show that the prediction error for an independent test set was lower for the transmission measurements with a relative root mean square error of about 2.2% as compared with 2.9% for the backscatter mode. Furthermore, the models were simpler in the transmission case, for which only a single partial least squares (PLS) component was required to explain the variation. The main reason for the improvement using the transmission mode is a more representative sampling of the tablets compared with the backscatter mode. Capsules containing mixtures of pharmaceutical powders were also assessed by transmission only. The quantitative results for the capsules' contents were good, with a prediction error of 3.6% w/w for an independent test set. The advantage of transmission Raman over backscatter Raman spectroscopy has been demonstrated for quantitative analysis of pharmaceutical formulations, and the prospects for reliable, lean calibrations for pharmaceutical analysis is discussed.

Validation of manufacturing process of Diltiazem HCl tablets by NIR spectrophotometry (NIRS)

The goal of this study was to apply the Process Analytical Technology FDA's initiative in pharmaceutical tablets manufacturing. Near Infrared Spectrophotometry (NIRS) was used as a non-destructive, very fast technique requiring no sample preparation. Direct compression powder blends containing Diltiazem HCl as a model drug were pressed into tablets for the calibration and the validation steps. First, a partial least squares model was built to calibrate the NIR spectrometer. Then, this model was validated and compared with a validated UV spectrophotometry reference method. For this comparison, the Bland and Altman's statistical method was applied. The manufacturing process was validated by producing three batches at three different concentration levels. The NIR analysis of these batches was performed during 3 days. This study shows that NIRS can be used to validate the whole manufacturing process and not only as an analytical method for tablets assay. NIRS is an interesting tool to show possible variations during the manufacturing process which could lead the finished product to fall outside of specifications.

Comparison of FT-NIR transmission and UV-vis spectrophotometry to follow the mixing kinetics and to assay low-dose tablets containing riboflavin

For several years, near-infrared spectroscopy (NIRS) has become an analytical technique of great interest for the pharmaceutical industry, particularly for the non-destructive analysis of dosage forms. The goal of this study is to show the capacity of this new technique to assay the active ingredient in low-dosage tablets. NIR spectroscopy is a rapid, non-destructive technique and does not need any sample preparation. As an example, a binary mixture of microcrystalline cellulose and riboflavin was used to prepare tablets of different weights by direct compression. A prediction model was built by using a partial least square regression fit method. The NIR assay was performed by transmission. The results obtained by NIR spectroscopy were compared with a conventional UV-vis spectrophotometry method. The study showed that tablets can be individually analysed by NIR with high accuracy. It was shown that the variability of this new technique is less important than that of the conventional method which is the UV-vis spectrophotometry.

Net Analyte Signal Based Statistical Quality Control

Net analyte signal statistical quality control (NAS-SQC) is a new methodology to perform multivariate product quality monitoring based on the net analyte signal approach. The main advantage of NAS-SQC is that the systematic variation in the product due to the analyte (or property) of interest is separated from the remaining systematic variation due to all other compounds in the matrix. This enhances the ability to flag products out of statistical control. Using control charts, the analyte content, variation of other compounds, and residual variation can be monitored. As an example, NAS-SQC is used to appreciate the control content uniformity of a commercially available pharmaceutical tablet product measured with near-infrared spectroscopy. Using the NAS chart, the active pharmaceutical ingredient (API) content is easily monitored for new tablets. However, since quality is a multivariate property, other quality parameters of the tablets are also monitored simultaneously. It will be demonstrated that, besides the API content, the water content of the tablets as well as the homogeneity of the other compounds is monitored.

Scatter correction of transmission near-infrared spectra by photon migration data: quantitative analysis of solids

The scope of this work is a new methodology to correct conventional near-infrared (NIR) data for scattering effects. The technique aims at measuring the absorption coefficient of the samples rather than the total attenuation measured in conventional NIR spectroscopy. The main advantage of this is that the absorption coefficient is independent of the path length of the light inside the sample and therefore independent of the scattering effects. The method is based on time-resolved spectroscopy and modeling of light transport by diffusion theory. This provides an independent measure of the scattering properties of the samples and therefore of the path length of light. This yields a clear advantage over other preprocessing techniques, where scattering effects are estimated and corrected for by using the shape of the measured spectrum only. Partial least squares (PLS) calibration models show that, by using the proposed evaluation scheme, the predictive ability is improved by 50% as compared to a model based on conventional NIR data alone. The method also makes it possible to predict the concentration of active substance in samples with other physical properties than the samples included in the calibration model.

Evaluation of basic algorithms for transferring quantitative multivariate calibrations between scanning grating and FT NIR spectrometers

A key issue in near infrared spectroscopy (NIR) is the possibility to use calibrations generated on one instrument for predictions on others. A number of methods for calibration transfer have been proposed, but which method to choose is typically not straightforward. An evaluation of a number of methods for transferring quantitative calibrations between different instruments was carried out on near infrared diffuse-reflectance data from a pharmaceutical formulation. Six instruments were included in the study, five of which were scanning grating instruments, both with and without fibre-optic probe configuration, and one of which was a Fourier-transform instrument, equipped with a fibre-optic probe. The results show that it is possible to transfer calibrations between different instruments, provided that a structured procedure is used. Simple techniques for calibration transfer, such as slope/bias correction on the predicted results, as well as standard normal variate transformation and local centring of the raw spectra, gave considerably lower prediction errors on transfer than did standardisation with a certified diffuse-reflectance standard, or direct transfer without any transfer function. Notably, including more than one instrument in the calibration also improved the prediction ability of the models on calibration transfer. No significant differences in wavelength scale were found when a certified diffuse-reflectance wavelength standard was measured on the instruments studied. Nor did simulated wavelength scale differences below +/-0.3 nm cause any significant change in the prediction errors.

Implementation of a simple semi-quantitative near-infrared method for the classification of clinical trial tablets

Near infrared transmission spectroscopy combined with chemometrical methods can be applied for identity confirmation of double-blind clinical trial tablets. Samples of two clinical studies, investigating the dose and placebo effect of an experimental drug, were studied. The identity of the blistered tablets was checked using partial least squares beta classification (PLSBC) applied to their NIR transmission spectra. PLSBC is a new supervised classification approach based on partial least squares (PLS) regression combined with beta-error driven class boundaries. It has the ability to limit the probability for misclassification to a known number and therefore providing the method developer a tool for deciding whether the NIR spectra of the different strengths of tablets are specific enough to obtain a robust classification model. The presented approach has the advantage to be applicable on most commercial available near infrared spectroscopy (NIRS) instrumentation software and it can be applied in a GMP environment since validation according to the ICH Q2A and Q2B guidelines on analytical method validation is fast and relatively easy.

Time-Resolved NIR Spectroscopy for Quantitative Analysis of Intact Pharmaceutical Tablets

Near-infrared (NIR) spectroscopy is a useful technique for quantitative measurements of intact tablets, but it suffers from limitations due to the fact that changes in the physical properties of a sample strongly affect the recorded spectrum. In this work, time-resolved transmission NIR spectroscopy was utilized to conduct quantitative measurements of intact tablets. The technique enables separation of the absorption properties of the sample from the scattering properties and can therefore handle changes of the physical parameters of the samples in a better way than conventional NIR transmission spectroscopy. The experiments were conducted using a pulsed Ti:sapphire laser coupled into a nonlinear photonic crystal fiber as light source. The light transmitted through the sample was measured by a time-resolving streak camera. A comparison of the results from the time-resolved technique with the results from conventional transmission NIR spectroscopy was made using tablets containing different concentrations of iron oxide and manufactured with different thicknesses. A PLS model made with data from the time-resolved technique predicted samples 5 times better than a PLS model made data from the conventional NIR transmission technique. Furthermore, an improvement to predict samples with physical properties outside those included in the calibration set was demonstrated.

Analysis of ecstasy tablets: comparison of reflectance and transmittance near infrared spectroscopy

Calibration models for the quantitation of commonly used ecstasy substances have been developed using near infrared spectroscopy (NIR) in diffuse reflectance and in transmission mode by applying seized ecstasy tablets for model building and validation. The samples contained amphetamine, N-methyl-3,4-methylenedioxy-amphetamine (MDMA) and N-ethyl-3,4-methylenedioxy-amphetamine (MDE) in different concentrations. All tablets were analyzed using high performance liquid chromatography (HPLC) with diode array detection as reference method. We evaluated the performance of each NIR measurement method with regard to its ability to predict the content of each tablet with a low root mean square error of prediction (RMSEP). Best calibration models could be generated by using NIR measurement in transmittance mode with wavelength selection and 1/x-transformation of the raw data. The models build in reflectance mode showed higher RMSEPs using as data pretreatment, wavelength selection, 1/x-transformation and a second order Savitzky-Golay derivative with five point smoothing was applied to obtain the best models. To estimate the influence of inhomogeneities in the illegal tablets, a calibration of the destroyed, i.e. triturated samples was build and compared to the corresponding data of the whole tablets. The calibrations using these homogenized tablets showed lower RMSEPs. We can conclude that NIR analysis of ecstasy tablets in transmission mode is more suitable than measurement in diffuse reflectance to obtain quantification models for their active ingredients with regard to low errors of prediction. Inhomogeneities in the samples are equalized when measuring the tablets as powdered samples.

One-carbon metabolism and other biochemical correlates of cognitive impairment as visualized by principal component analysis

In the present report, 101 ambulatory elderly patients complaining about cognitive disturbances were investigated using the Mini-Mental State Examination (MMSE). Laboratory investigations, brain imaging, and electroencephalography were performed. Twelve patients were diagnosed with subjective memory complaints (SMC), 32 with mild cognitive impairment (MCI), 43 with dementia of the Alzheimer type (DAT), and 14 with vascular dementia (VAD). Thirty-three percent of the SMC group, 31% of the MCI group, 45% of the DAT group, and 62% of the VAD group had increased serum homocysteine (s-HCY). Principal component analysis of 19 variables showed 3 significant principal components by cross-validation. The cognitive impairment in the patients (MMSE) was explained to 50%. According to the principal component analysis, the population followed two different routes to cognitive impairment: one correlated with disturbance of one-carbon metabolism (cerebrospinal fluid vitamin B12, plasma B12, plasma folate, and s-HCY) and the other correlated with more classic dementia, as marked by cerebrospinal fluid tau, vascular risk factors, atrophy on brain imaging, possession of the apolipoprotein E4 allele, and age. There was poor discrimination between DAT and VAD.

A novel method for analyzing thick tablets by near infrared spectroscopy

A near-infrared (NIR) spectroscopic method to determine content uniformity of a large, thick tablet using an approach that could facilitate future validations has been developed. A CT ibuprofen 800-mg tablet weighs about 1150 mg and is about 18.6 mm wide and 7.6 mm thick. The FT NIR spectrometer was optimized for transmission spectra of the tablets by moving it to the sample compartment and placing it immediately behind the tablet. In spite of this dedicated setup, the transmission spectra obtained were very poor, indicating that the NIR radiation was not reaching the detector. The spectra of the tablet improved with use of a simple preparation in which a flat-face die applies pressure of 20 000 psi to the tablet; this reduced the thickness of the tablet from 7.6 mm to 3.6 mm. A calibration model was developed for tablets with drug content ranging from 70% to 130% of label. The calibration model was tested using a validation set of tablets with a drug content of 752, 800, and 848 mg. The results obtained were within 1.5% of the known drug content of the validation set tablets. Even with the sample preparation, the content uniformity results of 10 tablets could be determined using this method in less than 1 hour. The approach described in this article could also be used to validate NIR content uniformity methods for other formulations.

A comparison of reflectance and transmittance near-infrared spectroscopic techniques in determining drug content in intact tablets

Drug contents of intact tablets were determined using non-destructive near infrared (NIR) reflectance and transmittance spectroscopic techniques. Tablets were compressed from blends of Avicel PH-101 and 0.5% w/w magnesium stearate with varying concentrations of anhydrous theophylline (0, 1, 2, 5, 10, 20 and 40% w/w). Ten tablets from each drug content batch were randomly selected for spectral analysis. Both reflectance and transmittance NIR spectra were obtained from these intact tablets. Actual drug contents of the tablets were then ascertained using a UV-spectrophotometer at 268 nm. Multiple linear regression (MLR) models at 1116 nm and partial least squares (PLS) calibration models were generated from the second derivative spectral data of the tablets in order to predict drug contents of intact tablets. Both the reflectance and the transmittance techniques were able to predict the drug contents in intact tablets over a wide range. However, a comparison of the results of the study indicated that the lowest percent errors of prediction were provided by the PLS calibration models generated from spectral data obtained using the transmittance technique.

Adaptable multivariate calibration models for spectral applications

Multivariate calibration techniques have been used in a wide variety of spectroscopic situations. In many of these situations, spectral variation can be partitioned into separate classes. For example, suppose that multiple spectra are obtained from each of a number of different objects wherein the level of the analyte of interest varies within each object over time. In such situations, the total spectral variation observed across all measurements has two distinct general sources of variation: intraobject and interobject. One might want to develop a global multivariate calibration model that predicts the analyte of interest accurately both within and across objects, including new objects not involved in developing the calibration model. However, this goal might be hard to realize if the interobject spectral variation is complex and difficult to model. If the intraobject spectral variation is consistent across objects, an effective alternative approach might be to develop a generic intraobject model that can be adapted to each object separately. This paper contains recommendations for experimental protocols and data analysis in such situations. The approach is illustrated with an example involving the noninvasive measurement of glucose using near-infrared reflectance spectroscopy. Extensions to calibration maintenance and calibration transfer are discussed.