Tablet identification using near-infrared spectroscopy (NIRS) for pharmaceutical quality control.

A need for more reliable and faster analytical methods for the identification of the active pharmaceutical ingredient (API) in finished pharmaceutical products is launched by the International Conference on Harmonisation (ICH) of Technical Requirements for Registration of Pharmaceuticals for Human Use, Test Procedures and Acceptance Criteria for New Drug Substances and New Drug Products: Chemical Substances, Q6A (1999). The use of infrared spectroscopy is suggested as a means to obtain specific identification. Near-infrared spectroscopy (NIRS) is a reliable method that offers important advantages for the large-scale production of tablets, such as high-throughput and accurate multiparametric data collection. Despite the grown number of reported NIRS identification methods, only a few methods have been approved by the regulatory authorities, which might be due to difficulties on clearly presenting the methods in official documents and audits. Motivated by the lack of clear protocols for the NIRS method's development, here we propose a process for building reliable identification NIRS methods. For illustration purposes, a method is described for the identification of API in coated tablets containing 2%, 4% and 8% of thiamazole. The method described was successfully validated according to the International Conference on Harmonisation (ICH) of Technical Requirement for Registration of Pharmaceuticals for Human Use, Validation of Analytical Procedures: Text and Methodology, Q2 (2005). The described method was subsequently approved by European national authorities and thus is suitable for use in cGMP environment.

Development of PLS calibration models from UV-Vis spectra for TOC estimation at the outlet of a fuel park wastewater treatment plant.

In the present work ultraviolet (UV)-visible spectra of water samples collected at the outlet of a fuel park wastewater treatment plant, including biological treatment, were acquired and used for the development of partial least squares (PLS) calibration models for the fast and simple estimation of total organic carbon (TOC). Three different PLS models were developed and compared on the basis of a common spectral range. The first model was obtained using spectra of raw samples, the second using spectra of diluted samples, to assess signal saturation in the UV region, and the third using spectra of both diluted and raw samples, in order to expand the narrow interval of TOC concentration values present in the original dataset. The root mean squared error of cross-validation values for the developed PLS models were 2.3, 1.0 and 4.4 mg Cl(-1), respectively, and the validation results where highly satisfactory (root mean squared error of prediction values of 1.8, 0.8 and 4.5 mg Cl(-1), respectively).

UV spectra analysis for water quality monitoring in a fuel park wastewater treatment plant.

In the context of the high application potentials for on-line measurements in wastewater quality monitoring, UV spectroscopy has received recent attention. In the present work UV spectrophotometric analyses were coupled to principal component analysis (PCA) and cluster analysis (CA) to characterize samples taken from a fuel park wastewater treatment plant and to attempt preliminary contaminant identification in the treated wastewater. The score plot resulting from PCA identified two different groups of spectra, one including the influents to the biological reactor and the other the treated wastewater samples. Among the latter, weekday and weekend samples could be further distinguished. The same groups of samples were identified in a dendrogram from CA. The score plot and the dendrogram also allowed the tentative identification of employed process chemicals (lubricant and detergents) as residual contaminants in the treated effluent.

Semi-quantitative prediction of a multiple API solid dosage form with a combination of vibrational spectroscopy methods.

Quality control (QC) in the pharmaceutical industry is a key activity in ensuring medicines have the required quality, safety and efficacy for their intended use. QC departments at pharmaceutical companies are responsible for all release testing of final products but also all incoming raw materials. Near-infrared spectroscopy (NIRS) and Raman spectroscopy are important techniques for fast and accurate identification and qualification of pharmaceutical samples. Tablets containing two different active pharmaceutical ingredients (API) [bisoprolol, hydrochlorothiazide] in different commercially available dosages were analysed using Raman- and NIR Spectroscopy. The goal was to define multivariate models based on each vibrational spectroscopy to discriminate between different dosages (identity) and predict their dosage (semi-quantitative). Furthermore the combination of spectroscopic techniques was investigated. Therefore, two different multiblock techniques based on PLS have been applied: multiblock PLS (MB-PLS) and sequential-orthogonalised PLS (SO-PLS). NIRS showed better results compared to Raman spectroscopy for both identification and quantitation. The multiblock techniques investigated showed that each spectroscopy contains information not present or captured with the other spectroscopic technique, thus demonstrating that there is a potential benefit in their combined use for both identification and quantitation purposes.

A PAT-based qualification of pharmaceutical excipients produced by batch or continuous processing.

Pharmaceutical excipients have an influence on the main requirements for medicinal products (viz., quality, safety and efficacy) but also on their manufacturability. During product lifecycle it may become necessary to introduce minor changes (e.g., to continuously improve it) or major changes in the validated process (e.g., moving it to a new production site, replacing process version or even disruptively changing processing type). Those changes can influence the critical to quality attributes of the product. Therefore, it is important to enhance process understanding to avoid the risk of any significant quality changes. Process analytical technology can support better decision making and risk-management as required in quality by design - viz., by many pharmaceutical regulatory authorities. This study compares the quality of the pharmaceutical excipient sodium carbonate (anhydrous) produced either in a batch or a continuous process. For continuous processing two different production lines were available that differed on the dryer and crystallizer types used. Therefore their influence on critical to quality attributes of sodium carbonate was investigated for each of the three processing alternatives. The overall goal was to identify which of the continuous processes ensures a similar product quality to batch processing. Namely, changes on chemical and physical attributes of the product were investigated with Raman spectroscopy, laser diffraction and X-ray powder diffraction. Principal component analysis, a very common multivariate analysis technique, was applied to extract relevant information from small differences at multiple spectral regions from samples from each process type and from each analytical technique used. Changing processing from batch to continuous improved consistency of certain attributes (e.g., particle size distribution) but affected others. However, the increased process/product knowledge gained can lead to an enhanced control strategy and ensure a similar product quality is obtained from distinct process versions.

Advanced qualification of pharmaceutical excipient suppliers by multiple analytics and multivariate analysis combined.

Pharmaceutical excipients have different functions within a drug formulation, consequently they can influence the manufacturability and/or performance of medicinal products. Therefore, critical to quality attributes should be kept constant. Sometimes it may be necessary to qualify a second supplier, but its product will not be completely equal to the first supplier product. To minimize risks of not detecting small non-similarities between suppliers and to detect lot-to-lot variability for each supplier, multivariate data analysis (MVA) can be used as a more powerful alternative to classical quality control that uses one-parameter-at-a-time monitoring. Such approach is capable of supporting the requirements of a new guideline by the European Parliament and Council (2015/C-95/02) demanding appropriate quality control strategies for excipients based on their criticality and supplier risks in ensuring quality, safety and function. This study compares calcium hydrogen phosphate from two suppliers. It can be assumed that both suppliers use different manufacturing processes. Therefore, possible chemical and physical differences were investigated by using Raman spectroscopy, laser diffraction and X-ray powder diffraction. Afterwards MVA was used to extract relevant information from each analytical technique. Both CaHPO4 could be discriminated by their supplier. The gained knowledge allowed to specify an enhanced strategy for second supplier qualification.

Real time monitoring biomass concentration in Streptomyces clavuligerus cultivations with industrial media using a capacitance probe.

On-line monitoring biomass concentration in mycelial fed-batch cultivations of Streptomyces clavuligerus grown with soluble and partially insoluble complex media, was investigated with an in-situ capacitance probe fitted to an industrial pilot-plant tank. Standard off-line and on-line biomass determinations, including cell dry weight, packed mycelial volume, viscosity, DNA concentration and total CO(2) evolution in the exhaust gases, were performed throughout the experiments and compared to on-line capacitance measurements. Linear relations between capacitance and all other measurements were developed for both media that hold only in defined process phases, depending on the biomass state and the amount of insoluble matter present. For the industrial complex culture media good linear relations were obtained in the fast growth phase between capacitance and DNA concentration and total CO(2) evolution, while in the subsequent transition and stationary phases only with apparent viscosity was a reasonable correlation found. The capacitance probe was shown to be a valuable tool for real-time monitoring biomass concentration in industrial-like cultivation of mycelial streptomycetes.

Mathematical modelling of industrial pilot-plant penicillin-G fed-batch fermentations.

Penicillin-G fermentation with industrial media in 1 m3 stirred tank bioreactors was studied. A model based on the Bajpai-Reuss model structure was developed. Under typical production conditions catabolite repression is nonidentifiable and extensive mycelium differentiation occurs. Thus, the original model was reformulated, neglecting glucose repression of penicillin production and including biomass autolysis. The multi-substrate nature of industrial media was critically analysed. By combining the two most important carbon substrates present, a simple and applicable model was obtained. Model predictions agreed well with experimental data and reproduced the general characteristics observed in the fermentations. The predictive power of the model was tested for fermentations with different sugar feed rate profiles and raw materials (corn-steep liquor and sugar syrup). Several aspects of parameter estimation and model development are discussed on the basis of direct experimental data inspection and a sensitivity analysis of model parameters.

Synthesis and characterization of nickel nanoparticles prepared using the aquolif approach.

We report on the synthesis of nickel nanoparticles using a combination of chemical reduction and freezing-drying processes that we named the aquolif approach. The X-ray diffraction (XRD) patterns reveal that the synthesized nanoparticles were composed of a single metallic nickel phase. The average crystallite sizes of the nickel nanoparticles were determined using the Scherrer method. The average crystallite sizes increased from 8±3 to 16±3 nm as the annealing temperature increased, which is consistent with the XRD and transmission electron microscopy results. The zero-field-cooling and field-cooling (ZFC-FC) magnetization curves reveal that the nickel nanoparticles exhibited superparamagnetic behavior with a high blocking temperature and a surface effect at lower temperatures. Our experimental results demonstrate that the aquolif approach can be successfully scaled up to industrially prepare other types of metallic nanoparticles.

A novel in-line NIR spectroscopy application for the monitoring of tablet film coating in an industrial scale process.

Film coating of tablets is a multivariate pharmaceutical unit operation. In this study an innovative in-line Fourier-Transform Near-Infrared Spectroscopy (FT-NIRS) application is described which enables real-time monitoring of a full industrial scale pan coating process of heart-shaped tablets. The tablets were coated with a thin hydroxypropyl methylcellulose (HPMC) film of up to approx. 28 µm on the tablet face as determined by SEM, corresponding to a weight gain of 2.26%. For a better understanding of the aqueous coating process the NIR probe was positioned inside the rotating tablet bed. Five full scale experimental runs have been performed to evaluate the impact of process variables such as pan rotation, exhaust air temperature, spray rate and pan load and elaborate robust and selective quantitative calibration models for the real-time determination of both coating growth and tablet moisture content. Principal Component (PC) score plots allowed each coating step, namely preheating, spraying and drying to be distinguished and the dominating factors and their spectral effects to be identified (e.g. temperature, moisture, coating growth, change of tablet bed density, and core/coat interactions). The distinct separation of HPMC coating growth and tablet moisture in different PCs enabled a real-time in-line monitoring of both attributes. A PLS calibration model based on Karl Fischer reference values allowed the tablet moisture trajectory to be determined throughout the entire coating process. A 1-latent variable iPLS weight gain calibration model with calibration samples from process stages dominated by the coating growth (i.e. ≥ 30% of the theoretically applied amount of coating) was sufficiently selective and accurate to predict the progress of the thin HPMC coating layer. At-line NIR Chemical Imaging (NIR-CI) in combination with PLS Discriminant Analysis (PLSDA) verified the HPMC coating growth and physical changes at the core/coat interface during the initial stages of the coating process. In addition, inter- and intra-tablet coating variability throughout the process could be assessed. These results clearly demonstrate that in-line NIRS and at-line NIR-CI can be applied as complimentary PAT tools to monitor a challenging pan coating process.

A multivariate approach for the statistical evaluation of near-infrared chemical images using Symmetry Parameter Image Analysis (SPIA).

Near-Infrared Chemical Imaging (NIR-CI) is rapidly gaining importance for the analysis of complex intermediate and final drug products. The availability of both spectral information from the sample and spatial information on the distribution of individual components offers access to greater understanding of manufacturing processes in many stages of pharmaceutical production. One major aspect in terms of chemical imaging is data analysis, since each measurement (image) generates a data cube containing several thousands of spectra (i.e., one spectrum per image pixel). The visual interpretation of component distribution (e.g., homogeneity) is an important issue but subjective. Chemometric methods are therefore required to extract qualitative and quantitative information from each image and enable comparison of several images. In this work, we describe a novel approach for the statistical evaluation of NIR-CI in terms of a multivariate treatment of univariate statistical descriptors characterizing image pixel (e.g., skewness and kurtosis). This technique was called by the authors "Symmetry Parameter Image Analysis" (SPIA), since it enables assessing the symmetry of pixel distributions in terms of different sample attributes. That approach is an innovative way of reporting results with a straightforward relation with attributes such as homogeneity, thus providing the basis for setting up acceptance criteria for good processing conditions or sample homogeneity. Furthermore, this procedure is applicable to determine product variability for large data sets without the need for explicit consideration of each image as its main attributes have been captured by the pixel distributions and their univariate descriptors. The approach is described by means of data obtained by NIR-CI on a powder blend case study (process application). Additionally, SPIA was used for the qualitative classification of tablets (sample application), showing that the approach can be generalized to set up criteria for sample-to-sample similarity and be useful in establishing criteria for e.g., counterfeiting.

A new PAT/QbD approach for the determination of blend homogeneity: combination of on-line NIRS analysis with PC Scores Distance Analysis (PC-SDA).

A novel and straightforward multivariate analytical tool for the qualitative determination of powder blend uniformity using on-line Near-Infrared Spectroscopy (NIRS) is presented. The approach combines current chemometric methods, e.g. spectral pre-processing and Principal Component Analysis (PCA), with (1) a new approach of data analysis to determine the end-point of the blending process, (2) building a design space (DS) for blend homogeneity and (3) developing a solid statistical rationale to stop blending according to Quality-by-Design (QbD) principles of FDA's Process Analytical Technology (PAT) initiative. The new approach comprises calculation of Euclidean distances between PCA scores in a multidimensional space and determination of Moving Block Standard Deviations (MBSDs) of successive Principal Component (PC) scores distances to estimate a time-window during blending where spectral variability decreases to a preset minimum. Hotelling's T(2) statistics is then used to monitor and report blend homogeneity. This technique is called "Principal Component Scores Distance Analysis" (PC-SDA). A Central Composite Design resulting in 10 batches mixed in a bin-blender (same composition, different blender fill level, different number of revolutions) was executed. NIR Chemical Imaging (NIR-CI) in combination with Symmetry Parameter Image Analysis (SPIA) was used to verify the NIRS analyzer response and assess homogeneity of all NIR-active components.

Near-infrared chemical imaging (NIR-CI) for counterfeit drug identification--a four-stage concept with a novel approach of data processing (Linear Image Signature).

A new stage concept was developed to reliably identify counterfeit tablets which are very similar to the genuine drug product. This concept combines single-point near-infrared spectroscopy (NIRS) and near-infrared chemical imaging (NIR-CI) with statistical variance analysis. The advantage of NIR-CI over NIRS is the potential to determine not only the amount, but also the spatial distribution of ingredients within a single tablet. Previously published NIR-CI studies used homogeneity as a key indicator for the identification of counterfeits. The state of the art approach for estimating homogeneity is to record the average and % standard deviation of predicted classification scores (i.e. concentrations) for a given component within a specimen. A disadvantage of this approach is the partial loss of spatial information. In view of this, we developed a new method using much more of the spatial information for the estimation of homogeneity. The method is based on (1) summation and unfolding of multidimensional predicted classification scores, which results in a Linear Image Signature (LIS) and (2) multivariate LIS data analysis (LIS-MVA). It could be demonstrated that this kind of NIR-CI data analysis represents an innovative approach for the identification of counterfeit tablets. Moreover, this procedure is applicable to determine the product variability, i.e. process signature of a given product thus being a valuable tool within the Quality by Design (QbD) approach of the ICH Q8 guideline.

Dealing with gene expression missing data.

Compared evaluation of different methods is presented for estimating missing values in microarray data: weighted K-nearest neighbours imputation (KNNimpute), regression-based methods such as local least squares imputation (LLSimpute) and partial least squares imputation (PLSimpute) and Bayesian principal component analysis (BPCA). The influence in prediction accuracy of some factors, such as methods' parameters, type of data relationships used in the estimation process (i.e. row-wise, column-wise or both), missing rate and pattern and type of experiment [time series (TS), non-time series (NTS) or mixed (MIX) experiments] is elucidated. Improvements based on the iterative use of data (iterative LLS and PLS imputation--ILLSimpute and IPLSimpute), the need to perform initial imputations (modified PLS and Helland PLS imputation--MPLSimpute and HPLSimpute) and the type of relationships employed (KNNarray, LLSarray, HPLSarray and alternating PLS--APLSimpute) are proposed. Overall, it is shown that data set properties (type of experiment, missing rate and pattern) affect the data similarity structure, therefore influencing the methods' performance. LLSimpute and ILLSimpute are preferable in the presence of data with a stronger similarity structure (TS and MIX experiments), whereas PLS-based methods (MPLSimpute, IPLSimpute and APLSimpute) are preferable when estimating NTS missing data.

Effects of preculture variability on clavulanic acid fermentation.

The production profile of clavulanic acid by Streptomyces clavuligerus was shown to be strongly dependent on inoculum activity. Two sets of fermentations (A and B) were investigated at industrial pilot-plant scale using complex media. Type A fermentations were inoculated using late exponential growth phase mycelia. Type B fermentations were inoculated using mycelia harvested at stationary phase. Productivities throughout type A fermentations were consistently higher than type B, reaching a maximum at about 70 h and then decaying to the same final productivities at 140 h of type B runs. Several scheduling alternatives, based on combinations of the two inocula types and different fermentation lengths, were compared in terms of the overall process economics (fermentation and downstream). An increase of ca. 22% on the overall process profit is predicted using late exponential growth phase inocula and a fermentation duration of only 96 h. A new operating strategy was thus proposed for inoculum production based on the control of preculture activity using off-gas analysis. This method ensures higher productivity and better batch-to-batch reproducibility of clavulanic acid fermentations than traditional methods based on constant age inocula.

Capability index--a statistical process control tool to aid in udder health control in dairy herds.

Bulk milk somatic cell count (BMSCC) averages have been used to evaluate udder health both at the individual or the herd level as well as milk quality and hygiene. The authors show that the BMSCC average is not the best tool to be used in udder health control programs and that it can be replaced with advantage by the capability index (Cpk). The Cpk is a statistical process control tool traditionally used by engineers to validate, monitor, and predict the expected behavior of processes or machines. The BMSCC data of 13 consecutive months of production from 414 dairy herds as well as SCC from all cows in the DHI program from 264 herds in the same period were collected. The Cpk and the annual BMSCC average (AAVG) of all the herds were calculated. Confronting the herd's performance explained by the Cpk and AAVG with the European Union (EU) official limit for BMSCC of 400,000 cells/mL, it was noticed that the Cpk accurately classified the compliance of the 414 farms, whereas the AAVG misclassified 166 (40%) of the 414 selected farms. The annual prevalence of subclinical mastitis (SMP) of each herd was calculated with individual SCC data from the same 13-mo period. Cows with more than 200,000 SCC/mL were considered as having subclinical mastitis. A logistic regression model to relate the Cpk and the herd's subclinical mastitis prevalence was calculated. The model is: SMPe = 0.475 e(-0.5286 x Cpk). The validation of the model was carried out evaluating the relation between the observed SMP and the predicted SMPe, in terms of the linear correlation coefficient (R2) and the mean difference between SMP and SMPe (i.e., mean square error of prediction). The validation suggests that our model can be used to estimate the herd's SMP with the herd's Cpk. The Cpk equation relates the herd's BMSCC with the EU official SCC limit, thus the logistic regression model enables the adoption of critical limits for subclinical mastitis, taking into consideration the legal standard for SCC.

Multiblock PLS analysis of an industrial pharmaceutical process.

The performance of an industrial pharmaceutical process (production of an active pharmaceutical ingredient by fermentation, API) was modeled by multiblock partial least squares (MBPLS). The most important process stages are inoculum production and API production fermentation. Thirty batches (runs) were produced according to an experimental planning. Rather than merging all these data into a single block of independent variables (as in ordinary PLS), four data blocks were used separately (manipulated and quality variables for each process stage). With the multiblock approach it was possible to calculate weights and scores for each independent block. It was found that the inoculum quality variables were highly correlated with API production for nominal fermentations. For the nonnominal fermentations, the manipulations of the fermentation stage explained the amount of API obtained (especially the pH and biomass concentration). Based on the above process analysis it was possible to select a smaller set of variables with which a new model was built. The amount of variance predicted of the final API concentration (cross-validation) for this model was 82.4%. The advantage of the multiblock model over the standard PLS model is that the contributions of the two main process stages to the API volumetric productivity were determined.

Morphology and viability analysis of Streptomyces clavuligerus in industrial cultivation systems.

The effects of varying inoculum age and production scale upon the morphology and viability of Streptomyces clavuligerus were studied by analyzing visible and fluorescent light images acquired throughout pilot-plant and pre-industrial scale fermentations. Changes in production scale reveal that in 5 m(3) fermentors, the maximum hyphal area obtained is double the value obtained in 0.5 m(3) fermentors. It is probably due to the higher shear stresses acting upon hyphae in the 0.5 m(3) fermentor caused by higher tip speeds observed in these. The morphological quantification based on elongation and branching rates allowed fermentations to be pattern classified into distinct physiological time zones namely elongation, branching, fragmentation, etc. The general pattern observed for fermentations inoculated with late exponential phase inocula was similar to the pattern of fermentations run with stationary phase inocula except that both the elongation and branching periods started earlier in the former case. Using the available staining technique and image acquisition system, the viability seemed to be generally high and constant throughout the time course of all the studied fermentations.

Influência do estresse alimentar na digestibilidade em cães / Influence of feeding stress on digestibility in dogs

O objetivo deste trabalho foi avaliar a influência do estresse alimentar sobre a digestibilidade aparente de uma dieta comercial em cãs. Foram utilizados 12 animais, sem raça definida, divididos em dois grupos de seis, submetidos a: tratamento 1 (T1) - caracterizado por indução o estresse alimentar pela irregularidade do horário de alimentação e provocação por estímulos visuais, olfatórios e auditivos, e tratamento 2 (T2) - caracterizado por regularidade do horário de alimentação e ausência de provocação (grupo-controle). As fezes para o ensaio de digestibilidade foram colhidas na primeira e na quarta semana após o início dos estímulos. Não foram encontradas diferenças entre tratamentos (grupos) e entre períodos quanto aos coeficientes de digestibilidade aparente da matéria seca, proteína bruta, extrato etéreo, extrato não nitrogenado, fibra detergente neutra e energia bruta.