An evaluation of direct orthogonal signal correction and other preprocessing methods for the classification of clinical study lots of a dermatological cream

Different preprocessing methods (direct orthogonal signal correction (DOSC), standard normal variate (SNV), multiple scatter correction (MSC), first and second derivation, offset correction and detrend correction) are applied to two sets of NIR spectra of a dermatological cream with different concentrations of an active compound. The influence of these preprocessing methods on the classification of the samples into the right concentration class is evaluated using 1 and 3 nearest neighbour method (with Euclidean distance and correlation coefficient as distance parameters) as classification method. PLS and PCR modelling are also used to make a prediction of the concentration of the active compound. The direct orthogonal signal correction gives best results in most of the classification methods.     

司他夫定胶囊近红外一致性检验模型建立及验证

目的：本实验以司他夫定胶囊为研究对象,应用近红外光谱分析技术,建立司他夫定胶囊的近红外一致性检验模型,快速无损进行司他夫定的真伪鉴别。方法：以司他夫定为研究主体,收集上海迪赛诺生物医药有限公司多批次数量样品,采集原始建模光谱160张,不同人员验证光谱80张,不同仪器验证光谱80张,应用OPUS7.0分析软件,采取一阶导数+矢量归一化法在12000~4000 cm-1范围内对司他夫定胶囊采集光谱进行预处理,选择最佳建模谱段为9000 cm-1～7500cm-1、6900 cm-1～5600 cm-1和5000 cm-1～4250 cm-1,平滑点为17,CI限度设为7,建立一致性检验模型并进行验证。结果：本方法CI限度值设为7,意味着本厂生产的样品CI限度值应＜7,结果建模样品光谱的CI限度值均＜7,非本厂生产的样品CI限度值均＞7,与事实相符,代表本模型具有很好鉴别本厂产品的能力。同时,不同仪器及不同人员测定的相同批次样品验证光谱CI值均＜7,证明该模型分别通过了不同仪器、不同人员的验证。结论：使用一致性检验模型可正确区分正品及伪品司他夫定胶囊,并通过了不同人员和不同仪器的光谱验证,从而实现了精确有效的模型传递,大大提高了近红外校正模型的通用性。该方法快速、简便、准确,适用于药品快检车对司他夫定胶囊的一致性快速筛查。     

Carbonyl metallo immuno assay: a new application for Fourier transform infrared spectroscopy

We describe here the development of a new, non-isotopic immunological assay termed CMIA (carbonyl metallo immunoassay) that uses metal carbonyl complexes as tracers and Fourier transform infrared spectroscopy (FT-IR) as the detection method. This assay is based on the particular spectral features of these complexes, which show very strong absorption bands in the 1,800-2,200 cm(-1) spectral range where proteins and organic molecules do not absorb. In Section 1, the optimisation of the quantitative detection of these tracers is detailed. In Section 2, the implementation of mono-CMIA is described, including the CMIA assays of three antiepileptic drugs (carbamazepine, phenobarbital, phenytoin). Finally, extension to the simultaneous double- and triple-CMIA of these drugs is reported.     

Discrimination of legal and illegal Cannabis spp. according to European legislation using near infrared spectroscopy and chemometrics

Aerial parts containing cannabidiol can be purchased in a legal way but cannabis used as recreational drug is illegal in most European countries. Δ9‐tetrahydrocannabinol is one of the main cannabinoids responsible for the psychotropic effect. European Union countries and Switzerland authorize a concentration of THC of 0.2 % and 1.0 % w/w, respectively, for smoking products and industrial hemp. Public health inspectors and law enforcement officers need to check the legality of samples. Therefore there is a need for innovative approaches, allowing quality control of these products in an easy way and preferably on site. In many countries, cultivation of industrial hemp is permitted if the THC content does not exceed 0.2 % w/w. A portable equipment could be a useful measuring tool for farmers to check for the THC content at regular time. In this work, 189 samples were analysed with a benchtop and a handheld NIR device in order to create two classification methods according to European and Swiss laws. All samples were also analysed by GC‐FID to determine their THC concentration. Supervised analysis was applied in order to establish the best model. For the first classification, the accuracy was 91% for the test set with the benchtop data and 93 % for the test set with the handheld data. For the second classification, the accuracies were respectively 91 % and 95 %. The obtained models, hyphenating spectroscopic techniques and chemometrics, enable to discriminate legal and illegal cannabis samples according to European and Swiss laws.     

Development and validation of a method for the polymorphic analysis of pharmaceutical preparations using near infrared spectroscopy

A new method for the characterization and determination of crystalline miokamycin in a pharmaceutical preparation using near infrared spectroscopy is proposed. The procedure involves the identification against a spectral library of samples with contents above the legal limit (viz. 5% of the crystalline form in amorphous miokamycin) using the Mahalanobis distance as the discriminating criterion, and the determination of the total and crystalline contents using partial least squares models that provide errors <1%. The proposed method was validated following the ICH guidelines. Its simplicity and expeditiousness make it highly suitable for quality control analyses of solid dosage forms.     

Determination of residual moisture in lyophilized protein pharmaceuticals using a rapid and non-invasive method: near infrared spectroscopy

This study examined the application of near-infrared (NIR) spectroscopy to analyze residual moisture in lyophilized protein pharmaceuticals sealed in glass vials. We demonstrated that NIR was able to determine residual moisture in five marketed and clinical products with the same precision as Karl Fischer titration. We further investigated how changes in product configuration and protein formulation affected NIR measurement accuracy using a lyophilized monoclonal antibody rhuMAb E25 containing 1% to 5% residual moisture. The results indicated that the lyophilized cake porosity and dimensions had no effect on NIR measurement when the cake height and diameter exceeded the NIR penetration depth. In addition, changing the buffer and surfactant concentrations in the formulation did not affect moisture determination by NIR. However, doubling or halving the concentration of a disaccharide, which was used as a lyoprotectant, caused significant deviation between the NIR and Karl Fischer data because the NIR absorbance of the disaccharide overlapped with the moisture signal. Furthermore, complete removal of the disaccharide resulted in alteration of the protein NIR spectra, suggesting that NIR may be used to evaluate solid-state protein structure. The disaccharide concentration must be kept constant in this formulation to obtain accurate moisture results by NIR.     

Process analytical technology: nondestructive evaluation of cyclosporine A and phospholipid solid dispersions by near infrared spectroscopy and imaging

The objective of this study was to evaluate near infrared (NIR) spectroscopy and imaging as approaches to assess phospholipid compartment within its solid dispersion with cyclosporine A (CyA). By varying dimyristoyl phosphatidylcholine (DMPC) to CyA weight ratio, five batches were prepared by the kneading technique and characterized by DSC and FTIR. A drug/DMPC ratio of 50:1 provided an enhanced dissolution of CyA. FTIR spectra and DSC thermograms revealed a significant interaction between the drug and DMPC which suggested incorporation of CyA within the formed DMPC liposomes. The developed NIR calibration model was able to assess DMPC concentrations within the kneaded products. The calibration and prediction linear plots showed slopes of 0.9711 and 0.9915, offsets of 0.1247 and 0.1080, correlation coefficients of 0.9854 and 0.9889 and root mean square standard errors of 0.43% and 0.42%, respectively. In contrast, NIR spectral imaging was capable of clearly distinguishing the kneaded products, both qualitatively and quantitatively. NIR imaging revealed the poor powder blending efficiency of the method used to prepare physical mixture compared to the efficient distribution of the kneaded products. In conclusion, NIR spectral imaging system provides a rapid approach for acquiring high-resolution spatial and spectral information on solid dispersions.     

Nondestructive tablet hardness testing by near-infrared spectroscopy: a new and robust spectral best-fit algorithm

A new algorithm using common statistics was proposed for nondestructive near-infrared (near-IR) spectroscopic tablet hardness testing over a range of tablet potencies. The spectral features that allow near-IR tablet hardness testing were evaluated. Cimetidine tablets of 1-20% potency and 1-7 kp hardness were used for the development and testing of a new spectral best-fit algorithm for tablet hardness prediction. Actual tablet hardness values determined via a destructive diametral crushing test were used for construction of calibration models using principal component analysis/principal component regression (PCA/PCR) or the new algorithm. Both methods allowed the prediction of tablet hardness over the range of potencies studied. The spectral best-fit method compared favorably to the multivariate PCA/PCR method, but was easier to develop. The new approach offers advantages over wavelength-based regression models because the calculation of a spectral slope averages out the influence of individual spectral absorbance bands. The ability to generalize the hardness calibration over a range of potencies confirms the robust nature of the method.     

Process analytical technology: Non-destructive assessment of anastrozole entrapment within PLGA microparticles by near infrared spectroscopy and chemical imaging

The objective of this study was to evaluate near-infrared (NIR) spectroscopy and imaging as approaches to assess anastrozole entrapment within PLGA microparticles. By varying the polymer concentration, three batches containing the same amount of the drug were prepared. The spectral features that allow NIR drug quantitation were evaluated and compared with a best fit line algorithm. Actual entrapment efficiencies (EEF) determined via a destructive method were used for construction of calibration models using partial least square regression (PLS) or the algorithm. On the other hand, a chemical imaging system based on array detector technology was used to rapidly collect high contrast NIR images of the formulated microparticles. A quantitative measure of anastrozole entrapped was determined by calculating the percentage standard deviation of the distribution of pixel intensities in the PLS score images and histograms. Concerning conventional NIR analysis, both methods were equivalent for the prediction of EEF over the range of polymer levels studied. Correlation coefficients of more than 0.992 were obtained for either the calibration or prediction of EEF by the two methods; 0.392% and 0.374% were the standard errors of calibration and prediction (SEC and SEP) obtained for the prediction of EEF using the fit line, respectively, whereas the prediction of the EEF by the partial least square regression showed a SEC of 0.195% and SEP of 0.179%. As a result, the spectral best fit algorithm method compared favourably to the multivariate PLS method, but was easier to develop. In contrast, NIR spectral imaging was capable of clearly differentiating the three batches, both qualitatively and quantitatively. The percentage standard deviation increased progressively by increasing the ratio of drug-to-polymer concentrations. In conclusion, both NIR approaches were capable of accurate assessment of drug entrapment within microparticles. In addition, the NIR spectral imaging system provides a rapid approach for acquiring spatial and spectral information on microparticles.     

Determination of the thickness of plastic sheets used in blister packaging by near infrared spectroscopy: development and validation of the method.

A near infrared (NIR) quantitative analysis method was developed for determining the thickness of PVC-based plastic sheets used as pharmaceutical packs. Samples that can be analyzed are transparent films made of polyvinyl chloride (PVC), PVC coated with polyvinylidene dichloride (PVDC) or PVC coated with Thermoelast (TE) and PVDC. The method, based on a partial least squares (PLS) algorithm, is used together with a previously developed NIR identification method to acquire simultaneously qualitative and quantitative information about the samples. Validation of the quantitative method was conducted according to the very recent European Agency for the Evaluation of Medicinal Products (EMEA) guidance on the use of NIR spectroscopy. Suggestions were made for a better statistical evaluation of the calibration model prior to validation. Validation consisted of the study of specificity, accuracy (mean recovery from the reference values was 99.56%), precision (repeatability and intermediate precision were <0.6%), linearity, quantification limit (41 microm), and robustness of the method. This demonstration of the applicability of NIR spectroscopy as a validated quality control tool for pharmaceutical packaging films will hopefully facilitate the acceptance of NIR spectroscopy in pharmaceutical laboratories.     

Process analytical technology: non-destructive assessment of anastrozole entrapment within PLGA microparticles by near infrared spectroscopy and chemical imaging

The objective of this study was to evaluate near-infrared (NIR) spectroscopy and imaging as approaches to assess anastrozole entrapment within PLGA microparticles. By varying the polymer concentration, three batches containing the same amount of the drug were prepared. The spectral features that allow NIR drug quantitation were evaluated and compared with a best fit line algorithm. Actual entrapment efficiencies (EEF) determined via a destructive method were used for construction of calibration models using partial least square regression (PLS) or the algorithm. On the other hand, a chemical imaging system based on array detector technology was used to rapidly collect high contrast NIR images of the formulated microparticles. A quantitative measure of anastrozole entrapped was determined by calculating the percentage standard deviation of the distribution of pixel intensities in the PLS score images and histograms. Concerning conventional NIR analysis, both methods were equivalent for the prediction of EEF over the range of polymer levels studied. Correlation coefficients of more than 0.992 were obtained for either the calibration or prediction of EEF by the two methods; 0.392% and 0.374% were the standard errors of calibration and prediction (SEC and SEP) obtained for the prediction of EEF using the fit line, respectively, whereas the prediction of the EEF by the partial least square regression showed a SEC of 0.195% and SEP of 0.179%. As a result, the spectral best fit algorithm method compared favourably to the multivariate PLS method, but was easier to develop. In contrast, NIR spectral imaging was capable of clearly differentiating the three batches, both qualitatively and quantitatively. The percentage standard deviation increased progressively by increasing the ratio of drug-to-polymer concentrations. In conclusion, both NIR approaches were capable of accurate assessment of drug entrapment within microparticles. In addition, the NIR spectral imaging system provides a rapid approach for acquiring spatial and spectral information on microparticles.     

Tablet potency of Tianeptine in coated tablets by near infrared spectroscopy: model optimisation, calibration transfer and confidence intervals

A near infrared (NIR) method was developed for determination of tablet potency of active pharmaceutical ingredient (API) in a complex coated tablet matrix. The calibration set contained samples from laboratory and production scale batches. The reference values were obtained by high performance liquid chromatography (HPLC) and partial least squares (PLS) regression was used to establish a model. The model was challenged by calculating tablet potency of two external test sets. Root mean square errors of prediction were respectively equal to 2.0% and 2.7%. To use this model with a second spectrometer from the production field, a calibration transfer method called piecewise direct standardisation (PDS) was used. After the transfer, the root mean square error of prediction of the first test set was 2.4% compared to 4.0% without transferring the spectra. A statistical technique using bootstrap of PLS residuals was used to estimate confidence intervals of tablet potency calculations. This method requires an optimised PLS model, selection of the bootstrap number and determination of the risk. In the case of a chemical analysis, the tablet potency value will be included within the confidence interval calculated by the bootstrap method. An easy to use graphical interface was developed to easily determine if the predictions, surrounded by minimum and maximum values, are within the specifications defined by the regulatory organisation.     

Augmentation of near infrared diffuse reflectance and transmittance spectral data for the development of robust PLSBC models for classifying double blind clinical trial tablets

The water content of clinical trial tablets can be different between and within different tablet batches, depending on the relative humidity conditions during their production, packaging, storage and analysis. These water variations lead to important spectral variations in the near infrared spectral region which can lead to a wrong identification if the classification model was based on unrepresentative data towards the water content. As model development for clinical trial studies needs to be extremely fast - within one working day - with generally only one batch available, the principle of data augmentation has to be applied to render more robust classification models. Therefore, tablets available for constructing the model are being processed in order to increase or decrease their water content and to make them more representative for tablets to be tested in the future. The inclusion of a deliberate water variation is the most efficient way to develop a model, for which no additional model redevelopment will be required to pass the system suitability tests and to obtain a correct identification.     

Construction of universal quantitative models for determination of roxithromycin and erythromycin ethylsuccinate in tablets from different manufacturers using near infrared reflectance spectroscopy

Universal quantitative models using NIR reflectance spectroscopy were developed for the analysis of API contents (active pharmaceutical ingredient) in roxithromycin and erythromycin ethylsuccinate tablets from different manufacturers in China. The two quantitative models were built from 78 batches of roxithromycin samples from 18 different manufacturers with the API content range from 19.5% to 73.9%, and 66 batches erythromycin ethylsuccinate tablets from 36 manufacturers with the API content range from 28.1% to 70.9%. Three different spectrometers were used for model construction in order to have robust and universal models. The root mean square errors of cross validation (RMSECV) and the root mean square errors of prediction (RMSEP) of the model for roxithromycin tablets were 1.84% and 1.45%, respectively. The values of RMSECV and RMSEP of the model for erythromycin ethylsuccinate tablets were 2.31% and 2.16%, respectively. Based on the ICH guidelines and characteristics of NIR spectroscopy, the quantitative models were then evaluated in terms of specificity, linearity, accuracy, precision, robustness and model transferability. Our study has shown that it is feasible to build a universal quantitative model for quick analysis of pharmaceutical products from different manufacturers. Therefore, the NIR method could be used as an effective method for quick, non-destructive inspection of medicines in the distribution channels or open market.     

Choice and validation of a near infrared spectroscopic application for the identity control of starting materials. practical experience with the EU draft Note for Guidance on the use of near infrared spectroscopy by the pharmaceutical industry and the data to be forwarded in part II of the dossier for a marketing authorization.

Recently the CPMP/CVMP sent out for consultation the draft Note for Guidance (dNfG) on the use of near infrared spectroscopy (NIRS) by the pharmaceutical industry and the data to be forwarded in part II of the dossier for a marketing authorization. We explored the practicability of this dNfG with respect to the verification of the correct identity of starting materials in a generic tablet-manufacturing site. Within the boundaries of the dNfG, a release procedure was developed for 12 substances containing structurally related compounds and substances differing only in particle size. For the method development literature data were also taken into consideration. Good results were obtained with wavelength correlation (WC), applied on raw spectra or second derivative spectra both without smoothing. The defined threshold of 0.98 for raw spectra differentiated between all molecular structures. Both methods were found to be robust over a period of 1 year. For the differentiation between the different particle sizes a subsequent second chemometric technique had to be used. Soft independent modelling of class analogy (SIMCA) with a probability level of 0.01 proved suitable. Internal and external validation I according to the dNfG showed no incorrect rejections or false acceptances. External validation II according to the dNfG was carried out with 95 potentially interfering substances from which 46 were tested experimentally. Macrogol 400 was not distinguished from macrogol 300. For the complete verification of the identity of macrogol 300 test A of the European Pharmacopoeia is needed in addition to the NIRS application. A release procedure developed with WC applied on raw spectra and SIMCA as a second method, which is different from the preferred method of the dNfG, was tested in practice with good results. We conclude that the dNfG has good practicability and that deviations from the preferred methods of the dNfG can also give good differentiation.     

A process analytical technology approach based on near infrared spectroscopy: tablet hardness, content uniformity, and dissolution test measurements of intact tablets

Near infrared spectroscopy (NIRS) is a nondestructive analytical technique that enables simultaneous measurements of chemical composition (viz. the content in active pharmaceutical ingredient, API) and various physical properties (viz. tablet hardness and dissolution profile) in pharmaceutical tablets. In this work, partial least squares (PLS) calibration models and discriminant partial least squares (DPLS) classification models were constructed by using calibration sets consisting of laboratory samples alone. The laboratory samples were mixtures of the API and excipients that were pressed into tablets. API content, tablet hardness, and dissolution measurements of intact tablets were made by using three different calibration models that are fast--results can be obtained within a few seconds--, simple and robust--they involve minimal analyst intervention--, and clean--they use no toxic reagent and produce no toxic waste. Based on the results, the proposed NIR method is an effective alternative to current reference methods for the intended purpose. The advantages provided by NIR spectroscopy in this context confirm its potential for inclusion in process analytical technologies in the pharmaceutical industry.     

Determination of binary polymorphic mixtures of fluconazole using near infrared spectroscopy and X-ray powder diffraction: a comparative study based on the pre-validation stage results

The aim of the present study was to develop near infrared (NIR) and X-ray powder diffraction methods (XRPD) able to determine pure crystalline form II of fluconazole in a binary polymorphic mixtures containing forms II and III. In order to give a first performance estimation of both methods, these latters were pre-validated using accuracy profiles, a statistical approach based on β-expectation tolerance intervals. Both methods showed a good trueness, precision and accuracy and their β-expectation tolerance intervals were fully included within the acceptance limits. The comparative study was carried out using statistical analysis based on the work of Bland and Altman. A good agreement between the two methods was demonstrated indicating the interchangeability of NIR method with XRPD method.     

Drug penetration as studied by noninvasive methods: fourier transform infrared-attenuated total reflection, fourier transform infrared, and ultraviolet photoacoustic spectroscopy

The penetration of the drugs dithranol and methoxsalen from semisolid Vaseline formulation into an artificial dodecanol-collodion membrane was followed by three spectroscopic methods; they are, step-scan Fourier transform infrared (FTIR) photoacoustic spectroscopy (PAS) with phase modulation, FTIR-attenuated total reflection (FTIR-ATR), and ultraviolet (UV) PAS. The uptake of the drug in the membrane was quantified by monitoring the dependence of an appropriate drug band on the penetration time. The PAS experiments were carried out with various modulation frequencies for generating various sampling depths. Based on Fick's second law, the diffusion coefficient was derived by numerical fitting of the experimental data. It appears that the diffusion coefficient for the drug in the membrane depends on the distance. The comparative studies demonstrate that FTIR-ATR is favored for permeation studies, whereas the PAS techniques are capable of providing the drug penetration profile in the membrane. Thus, extended experimental data are available for new insight into the penetration process. However, because of the photacoustic cells at hand, PAS is only suitable for in vitro studies.     

Analysis of low content drug tablets by transmission near infrared spectroscopy: selection of calibration ranges according to multivariate detection and quantitation limits of PLS models

The content uniformity of low dose products is a major concern in the development of pharmaceutical formulations. Near infrared spectroscopy may be used to support the design and optimization of potent drug manufacturing processes through the analysis of blends and tablets in a relatively short time. A strategy for the selection of concentration ranges in the development of multivariate calibration is presented, evaluating the detection and quantitation limits of the obtained multivariate models. The strategy has been applied to the determination of an active principle in pharmaceutical tablets of low concentration (0-5%, w/w), using Fourier Transform Near Infrared (FT-NIR) transmission spectroscopy. The quantitation and detection limits decreased as the upper concentration level of the calibration models was reduced. The results obtained show that the selection of concentration ranges is a critical aspect during model design. The selection of wide concentration ranges with high levels is not recommended for the determination of analytes at minor levels (<1%, w/w), even when the concentration of interest is within the range of the model.