Study of pharmaceutical samples by NIR chemical-image and multivariate analysis

Infrared imaging spectroscopy and chemometric tools for in situ analysis of an imiquimod pharmaceutical preparation presented as cream

In the present work the homogeneity of a pharmaceutical formulation presented as a cream was studied using infrared imaging spectroscopy and chemometric methodologies such as principal component analysis (PCA) and multivariate curve resolution with alternating least squares (MCR-ALS). A cream formulation, presented as an emulsion, was prepared using imiquimod as the active pharmaceutical ingredient (API) and the excipients: water, vaseline, an emulsifier and a carboxylic acid in order to dissolve the API. After exposure at 45°C during 3 months to perform accelerated stability test, the presence of some crystals was observed, indicating homogeneity problems in the formulation. PCA exploratory analysis showed that the crystal composition was different from the composition of the emulsion, since the score maps presented crystal structures in the emulsion. MCR-ALS estimated the spectra of the crystals and the emulsion. The crystals presented amine and C-H bands, suggesting that the precipitate was a salt formed by carboxylic acid and imiquimod. These results indicate the potential of infrared imaging spectroscopy in conjunction with chemometric methodologies as an analytical tool to ensure the quality of cream formulations in the pharmaceutical industry.

Near-infrared spectroscopy and hyperspectral imaging: non-destructive analysis of biological materials

Principles, interpretation and applications of near-infrared (NIR) spectroscopy and NIR hyperspectral imaging are reviewed.

Living matter observations with a novel hyperspectral supercontinuum confocal microscope for VIS to near-IR reflectance spectroscopy

A broad range hyper-spectroscopic microscope fed by a supercontinuum laser source and equipped with an almost achromatic optical layout is illustrated with detailed explanations of the design, implementation and data. The real novelty of this instrument, a confocal spectroscopic microscope capable of recording high resolution reflectance data in the VIS-IR spectral range from about 500 nm to 2.5 μm wavelengths, is the possibility of acquiring spectral data at every physical point as defined by lateral coordinates, X and Y, as well as at a depth coordinate, Z, as obtained by the confocal optical sectioning advantage. With this apparatus we collect each single scanning point as a whole spectrum by combining two linear spectral detector arrays, one CCD for the visible range, and one InGaAs infrared array, simultaneously available at the sensor output channel of the home made instrument. This microscope has been developed for biomedical analysis of human skin and other similar applications. Results are shown illustrating the technical performances of the instrument and the capability in extracting information about the composition and the structure of different parts or compartments in biological samples as well as in solid statematter. A complete spectroscopic fingerprinting of samples at microscopic level is shown possible by using statistical analysis on raw data or analytical reflectance models based on Abelés matrix transfer methods.

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.

Raman imaging spectroscopic characterization of modified poly(dimethylsiloxane) for micro total analysis systems applications

Methacryloxypropyl-modified poly(dimethylsiloxane) rubbers were obtained from poly(dimethylsiloxane), PDMS, and methacryloxypropyltrimethoxysilane, MPTMS, by polycondensation reactions. The modified rubbers, prepared with 20 and 30% (v/v) of MPTMS, were used as substrates for microchannel fabrication by the CO(2) laser ablation technique. Raman imaging spectroscopy was used for the surface characterization, showing the homogeneity of the rubbery material, with uniform distribution of the crosslinking centers. Under the experimental conditions used, damage to the rubber from the CO(2) laser radiation used for the channel engraving was not observed. Correlation maps of the surface were obtained in order to spatially evaluate the modification inside and outside the channels. The correlations between the methacryloxypropyl-modified poly(dimethylsiloxane) rubbers and MPTMS (spectral range of 1800-1550 cm(-1)) and PDMS (spectral range of 820-670 cm(-1)) precursors were higher than 0.95 and 0.99, respectively. In addition, Raman imaging spectroscopy allows monitoring the topography of the fabricated microchannel.

Mapping lipid and collagen by multispectral photoacoustic imaging of chemical bond vibration

Photoacoustic microscopy using vibrational overtone absorption as a contrast mechanism allows bond-selective imaging of deep tissues. Due to the spectral similarity of molecules in the region of overtone vibration, it is difficult to interrogate chemical components using photoacoustic signal at single excitation wavelength. Here we demonstrate that lipids and collagen, two critical markers for many kinds of diseases, can be distinguished by multispectral photoacoustic imaging of the first overtone of C-H bond. A phantom consisting of rat-tail tendon and fat was constructed to demonstrate this technique. Wavelengths between 1650 and 1850 nm were scanned to excite both the first overtone and combination bands of C-H bonds. B-scan multispectral photoacoustic images, in which each pixel contains a spectrum, were analyzed by a multivariate curve resolution-alternating least squares algorithm to recover the spatial distribution of collagen and lipids in the phantom.

A criterion for assessing homogeneity distribution in hyperspectral images. Part 2: application of homogeneity indices to solid pharmaceutical dosage forms

This article is the second of a series of two articles detailing the application of mixing index to assess homogeneity distribution in oral pharmaceutical solid dosage forms by image analysis. Chemical imaging (CI) is an emerging technique integrating conventional imaging and spectroscopic techniques with a view to obtaining spatial and spectral information from a sample. Near infrared chemical imaging (NIR-CI) has proved an excellent analytical tool for extracting high-quality information from sample surfaces. The primary objective of this second part was to demonstrate that the approach developed in the first part could be successfully applied to near infrared hyperspectral images of oral pharmaceutical solid dosage forms such as coated, uncoated and effervescent tablets, as well as to powder blends. To this end, we assessed a new criterion for establishing mixing homogeneity by using four different methods based on a three-dimensional (M×N×λ) data array of hyperspectral images (spectral standard deviations and correlation coefficients) or a two-dimensional (M×N) data array (concentration maps and binary images). The four methods were used applying macropixel analysis to the Poole (M(P)) and homogeneity (H%(Poole)) indices. Both indices proved useful for assessing the degree of homogeneity of pharmaceutical samples. The results testify that the proposed approach can be effectively used in the pharmaceutical industry, in the finished products (e.g., tablets) and in mixing unit operations for example, as a process analytical technology tool for the blending monitoring (see part 1).

Hyperspectral imaging based method for fast characterization of kidney stone types

The formation of kidney stones is a common and highly studied disease, which causes intense pain and presents a high recidivism. In order to find the causes of this problem, the characterization of the main compounds is of great importance. In this sense, the analysis of the composition and structure of the stone can give key information about the urine parameters during the crystal growth. But the usual methods employed are slow, analyst dependent and the information obtained is poor. In the present work, the near infrared (NIR)-hyperspectral imaging technique was used for the analysis of 215 samples of kidney stones, including the main types usually found and their mixtures. The NIR reflectance spectra of the analyzed stones showed significant differences that were used for their classification. To do so, a method was created by the use of artificial neural networks, which showed a probability higher than 90% for right classification of the stones. The promising results, robust methodology, and the fast analytical process, without the need of an expert assistance, lead to an easy implementation at the clinical laboratories, offering the urologist a rapid diagnosis that shall contribute to minimize urolithiasis recidivism.

Characterization of semi-solid Self-Emulsifying Drug Delivery Systems (SEDDS) of atorvastatin calcium by Raman image spectroscopy and chemometrics

A methodology based on Raman image spectroscopy and chemometrics for homogeneity evaluation of formulations containing atorvastatin calcium in Gelucire(®) 44/14 is presented. In the first part of the work, formulations with high amounts of Gelucire(®) 44/14 (80%) and solvents of different polarities (diethylene glycol monoethyl ether, propyleneglycol, propylene glycol monocaprylate and glyceryl mono/dicaprylate/caprate) were prepared for miscibility screening evaluation by classical least squares (CLS). It was observed that Gelucire(®) 44/14 presented higher affinity for the lipophilic solvents glyceryl mono/dicaprylate/caprate and propylene glycol monocaprylate, whose samples were observed to be homogeneous, and lower affinity for the hydrophilic solvents diethylene glycol monoethyl ether and propyleneglycol, whose samples were heterogeneous. In the second part of the work, the ratio of glyceryl mono/dicaprylate/caprate and Gelucire(®) 44/14 was determined based on studies in water and allowed the selection of the proportions of these two excipients in the preconcentrate that provided supersaturation of atorvastatin upon dilution. The preconcentrate was then evaluated for homogeneity by partial least squares (PLS) and an excellent miscibility was observed in this proportion as well. Therefore, it was possible to select a formulation that presented simultaneously homogeneous preconcentrate and solubility enhancement in water by Raman image spectroscopy and chemometrics.

Visualizing excipient composition and homogeneity of Compound Liquorice Tablets by near-infrared chemical imaging

This study demonstrated that near-infrared chemical imaging (NIR-CI) was a promising technology for visualizing the spatial distribution and homogeneity of Compound Liquorice Tablets. The starch distribution (indirectly, plant extraction) could be spatially determined using basic analysis of correlation between analytes (BACRA) method. The correlation coefficients between starch spectrum and spectrum of each sample were greater than 0.95. Depending on the accurate determination of starch distribution, a method to determine homogeneous distribution was proposed by histogram graph. The result demonstrated that starch distribution in sample 3 was relatively heterogeneous according to four statistical parameters. Furthermore, the agglomerates domain in each tablet was detected using score image layers of principal component analysis (PCA) method. Finally, a novel method named Standard Deviation of Macropixel Texture (SDMT) was introduced to detect agglomerates and heterogeneity based on binary image. Every binary image was divided into different sizes length of macropixel and the number of zero values in each macropixel was counted to calculate standard deviation. Additionally, a curve fitting graph was plotted on the relationship between standard deviation and the size length of macropixel. The result demonstrated the inter-tablet heterogeneity of both starch and total compounds distribution, simultaneously, the similarity of starch distribution and the inconsistency of total compounds distribution among intra-tablet were signified according to the value of slope and intercept parameters in the curve.

Determination of drug, excipients and coating distribution in pharmaceutical tablets using NIR-CI

The growing interest of the pharmaceutical industry in Near Infrared-Chemical Imaging (NIR-CI) is a result of its high usefulness for quality control analyses of drugs throughout their production process (particularly of its non-destructive nature and expeditious data acquisition). In this work, the concentration and distribution of the major and minor components of pharmaceutical tablets are determined and the spatial distribution from the internal and external sides has been obtained. In addition, the same NIR-CI allowed the coating thickness and its surface distribution to be quantified. Images were processed to extract the target data and calibration models constructed using the Partial Least Squares (PLS) algorithms. The concentrations of Active Pharmaceutical Ingredient (API) and excipients obtained for uncoated cores were essentially identical to the nominal values of the pharmaceutical formulation. But the predictive ability of the calibration models applied to the coated tablets decreased as the coating thickness increased.

Content uniformity studies in tablets by NIR-CI

Near infrared chemical imaging (NIR-CI) is attracting growing interest in pharmaceutical analysis by virtue of its ability to provide a wealth of information from a single sample. Among others, NIR-CI has enabled the determination of the quantitative composition and distribution of acetylsalicylic (ASA) from the analysis of commercial tablets. In this work, we analyzed ASA commercial tablets of four different brands purchased at local chemists. The nominal ASA concentration for the brands was calculated from the nominal content and averaged weight of tablets. The tablets were found to span an ASA concentration range of 71-82%, and to differ in size and composition between brands. The API content and its homogeneity distribution were determined by applying quantitative algorithm to global hyperspectral image of ten tablets. Multivariate curve resolution-alternating least squares (MCR-ALS) is used to quantify each pixel in the images to obtain appropriate concentration maps. No prior calibration or reference data were needed for quantitation and results are close to the nominal content used as reference. Application to an image for 10 tablets and an individual tablet quantitation of the API allowed us to obtain the Accepted Value (AV) as defined by the European Pharmacopoeia. We conclude that all brands meet the pharmacopoeia specifications.

Confocal micro-X-ray fluorescence analysis as a new tool for the non-destructive study of the elemental distributions in pharmaceutical tablets

Chemical imaging studies of pharmaceutical tablets are currently an important emerging field in the pharmaceutical industry. Finding the distribution of the different compounds inside the tablet is an important issue for production quality control but also for counterfeit detection. Most of the currently used techniques are limited to the study of the surface of the compacts, whereas the study of the bulk requires a time-consuming sample preparation. In this paper, we present the use of 3D micro-X-ray fluorescence analysis (3D μXRF) for the non-destructive study of pharmaceutical tablets. Based on two different examples, it was shown that it was possible to measure the distribution of several inorganic elements (Zn, Fe, Ti, Mn, Cu) from the surface to a depth of several hundred microns under the surface. The X-ray absorption, depending on both matrix composition and energy, is one of the most critical factors of this analytical method while performing depth profiling or mapping. Therefore, an original method to correct the absorption, in order to accurately measure the true elemental distribution, was proposed. Moreover, by using the presence of titanium dioxide in a pharmaceutical coating, we proved that this technique is also suited to the non-destructive measurement of coating thickness.

Raman mapping of pharmaceuticals

Raman spectroscopy may be implemented through a microscope to provide fine scale axial and lateral chemical maps. The molecular structure of many drugs makes Raman spectroscopy particularly well suited to the investigation of pharmaceutical systems. Chemometric methods currently used to assess bulk Raman spectroscopic data are typically applied to Raman mapping data from pharmaceuticals; few reports exist where the spatial information inherent to a mapped dataset is used for the calculation of chemical maps. Both univariate and multivariate methods have been applied to Raman mapping data to determine the distribution of active pharmaceutical ingredients (APIs) in tablets, solid dispersions for increased solubility and controlled release devices. The ability to axially (depth) profile using Raman mapping has been used in studies of API penetration through membranes, cellular uptake of drug delivery liposomes, and initial API distribution and subsequent elution from coatings of medical devices. New instrumental developments will increase the efficiency of Raman mapping and lead to greater utilisation of Raman mapping for analyses of pharmaceutical systems.