Quality control of multi-component, intact pharmaceutical tablets with three different near-infrared apparatuses

The purpose of this study was to develop a robust and versatile near infrared (NIR) analysis protocol for the quality control of intact tablets containing two active pharmaceutical ingredients, acetylsalicylic acid (ASA) and caffeine, as well as three excipients. Reference samples were prepared and a calibration model built for each apparatus. All components of the formulation were characterized by transmission measurements with NIR spectroscopy (NIRS). The study was performed with three different Fourier transform NIR apparatuses and chemometric models. Calibration was carried out by the partial least squares regression method and a pre-processing technique to optimize the efficiency of the models. High performance liquid chromatography was the reference method for obtaining active pharmaceutical ingredient concentration values used in model building. It also served as a reference for chemometric model validation. Eighteen samples were analyzed by chemometric modeling to predict each component's concentration. Four out of five ingredients were quantified precisely with the three chemometric models developed. ASA quantification uncertainty ranges were between 1.0 and 1.1%, and the average error was less than 5% for caffeine. More than 99.9% of tablet content were analyzed and quantified. The results show that a versatile in-line or at-line NIRS method, with three different chemometric models built from three different acquisition apparatuses, can be developed without sample preparation for pharmaceutical tablet quality control of existing products.     

近红外光谱法鉴别普伐他汀钠片及其原料药晶型的一致性研究

目的 建立全覆盖抽样的普伐他汀钠片的近红外光谱法一致性检验模型,考察制剂工艺的差别和原料药晶型的差异,通过稳健、准确、代表性强的近红外光谱一致性模型实现普伐他汀钠片的快速检验和筛查。方法 对评价性抽验抽取的5个企业中的4个共65批样品建立普伐他汀钠片近红外一致性检验模型,并对4个厂家的原料药的近红外光谱图进行比较。结果 建立了4个厂家普伐他汀钠片剂的近红外一致性模型,预测成功率均为100%;4种原料药和1种无定型粉末的近红外光谱图显示不同晶型光谱图具有差异。结论 近红外光谱法能够用于快速鉴别质量工艺稳定的普伐他汀钠片产品,对制剂工艺进行考察,并能够区分不同晶型的原料药。     

Assay of effervescent tablets by near-infrared spectroscopy in transmittance and reflectance mode: acetylsalicylic acid in mono and combination formulations

Near-infrared spectroscopy (NIRS) was used to determine acetylsalicylic acid (ASA) in three different effervescent tablet formulations. The nominal ASA concentrations were 14.9% in the single substance formulation (ASA Mono), 17.4% in the combination with ascorbic acid (ASA+C) and 8.7% in the combination with paracetamol and ascorbic acid (ASA Combi). In each case the tablet matrix was composed of seven excipients typical of effervescent tablets. All three formulations were measured as intact tablets in diffuse transmittance and reflectance and as powdered tablets in diffuse reflectance. Calibration was carried out by partial least square (PLS) regression of second derivative spectra. High-performance liquid chromatography (HPLC) was used as the reference method. The relative standard errors of calibration (RSEC) achieved for the three NIR methods were between 1.20 and 2.01% for ASA Mono, between 1.91 and 2.21% for ASA+C and between 2.41 and 4.50% for ASA Combi. The results obtained in transmittance mode were comparable with those obtained in reflectance mode, which is normally used in NIRS. In the test sets of ASA Mono and ASA+C relative root mean square (RRMS) values between 2.21 and 3.13% were obtained. The three NIR methods applied are thus suitable for the quantitative determination of ASA in effervescent tablets and have the advantage over HPLC of being rapid and simply carried out with little sample preparation; they are nondestructive and do not require any environmentally harmful reagents.     

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.     

近红外光谱法测定药物崩解时限应用研究

研究安乃近片崩解时限的近红外快速分析方法.以崩解时限测定仪法分析值为参照,采用近红外透反射光谱技术采集光谱,对光谱进行波长选择和预处理,采用偏最小二乘回归建立校正模型,并使用建立好的PLSR定性模型对药物崩解进行快速检测.模型性能良好,安乃近的相关系数为0.9901,RMSECV值为0.0227.近红外透反射光谱技术可...     

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.     

Synthetic Calibration for Efficient Method Development: Analysis of Tablet API Concentration by Near-Infrared Spectroscopy

Near-infrared (NIR) spectroscopy is an important process analytical technology (PAT) tool for rapid characterization of pharmaceutical tablet quality. The time and expense required for calibration development has been a detriment to implementation of PAT sensors. While methods based on generalized least-squares and net analyte signal pure-component projection (PCP) have been demonstrated to be useful tools for efficient spectroscopic calibration, PCP methods are relatively difficult to deploy and maintain in industrial settings. Synthetic calibration based on augmentation of parallel-testing data with artificial interference spectra generated in silico is introduced as a method to achieve efficient NIR calibration using off-the-shelf chemometric algorithms. A method for estimating a slope correction factor using parallel test data is shown. The results of this work demonstrate that, by using efficient calibration methods, accurate quantitative NIR calibration models for characterization of drug tablet quality can be created using only pure-component spectra and production-scale tablet samples.     

Near InfraRed Spectroscopy homogeneity evaluation of complex powder blends in a small-scale pharmaceutical preformulation process, a real-life application

Near InfraRed Spectroscopy (NIRS) is a potentially powerful tool for assessing the homogeneity of industrial powder blends. In the particular context of hospital manufacturing, we considered the introduction of the technique at a small pharmaceutical process scale, with the objective of following blend homogeneity in mixtures of seven components. This article investigates the performance of various NIRS-based methodologies to assess powder blending.The formulation studied is prescribed in haematology unit, as part of the treatment for digestive decontamination in children receiving stem-cell transplantation. It is composed of the active pharmaceutical ingredients (APIs) colimycin and tobramycin and five excipients. We evaluated 39 different blends composing 14 different formulations, with uncorrelated proportions of constituents between these 14 formulations. The reference methods used to establish the NIRS models were gravimetry and a High Performance Liquid Chromatography method coupled to an Evaporative Light Scattering Detection.Unsupervised and supervised qualitative and quantitative chemometric methods were performed to assess powder blend homogeneity using a bench top instrument equipped with an optical fibre. For qualitative evaluations, unsupervised Moving Block Standard Deviation, autocorrelation functions and Partial Least Square Discriminant Analysis (PLS-DA) were used. For quantitative evaluations, Partial Least Square Cross-Validated models were chosen. Results are expressed as API, and major excipient percentages of theoretical values as a function of blending time. The 14 different formulations were only satisfactorily discriminated by supervised algorithms, such as an optimised PLS-DA model. The homogeneity state was demonstrated after 16 min of blending, quantifying three components with a precision between 1.2% and 1.4% w/w.This study demonstrates, for the first time, the effective implementation of NIRS for blend homogeneity evaluation, as early as the preformulation step in a small hospital manufacturing unit. It shows how NIRS involving sampling with an optic fibre can be useful to characterise, optimise and control a small-scale mixing processes on the basis of the distribution of APIs and excipients during blending.     

Development of a method for the determination of caffeine anhydrate in various designed intact tablets [correction of tables] by near-infrared spectroscopy: a comparison between reflectance and transmittance technique

Using near-infrared (NIR) spectroscopy, an assay method which is not affected by such elements of tablet design as thickness, shape, embossing and scored line was developed. Tablets containing caffeine anhydrate were prepared by direct compression at various compression force levels using different shaped punches. NIR spectra were obtained from these intact tablets using the reflectance and transmittance techniques. A reference assay was performed by high-performance liquid chromatography (HPLC). Calibration models were generated by the partial least-squares (PLS) regression. Changes in the tablet thickness, shape, embossing and scored line caused NIR spectral changes in different ways, depending on the technique used. As a result, noticeable errors in drug content prediction occurred using calibration models generated according to the conventional method. On the other hand, when the various tablet design elements which caused the NIR spectral changes were included in the model, the prediction of the drug content in the tablets was scarcely affected by those elements when using either of the techniques. A comparison of these techniques resulted in higher predictability under the tablet design variations using the transmittance technique with preferable linearity and accuracy. This is probably attributed to the transmittance spectra which sensitively reflect the differences in tablet thickness or shape as a result of obtaining information inside the tablets.     

A novel sample selection strategy by near-infrared spectroscopy-based high throughput tablet tester for content uniformity in early-phase pharmaceutical product development

This article proposes a new sample selection strategy to simplify the traditional content uniformity (CU) test in early research and development (R&D) with improved statistical confidence. This strategy originated from the prescreening of a large amount of tablets by a near-infrared spectroscopy (NIRS)-based high-volume tablet tester to the selection of extreme tablets with highest, medium, and lowest content of active pharmaceutical ingredient (API) for further high-performance liquid chromatography (HPLC) test. The NIRS-based high-volume tablet tester was equipped with an internally developed and integrated automated bagging and labeling system, allowing the traceability of every individual tablet by its measured physical and chemical signatures. A qualitative NIR model was used to translate spectral information to a concentration-related metric, that is scores, which allowed the selection of those extreme tablets. This sample selection strategy of extreme tablets was shown to provide equivalent representation of CU in the process compared with the traditional CU test using a large number of random samples. Because it only requires reference tests on three extreme samples per stratified location, the time- and labor-saving nature of this strategy is advantageous for CU test in early R&D. The extreme sampling approach is also shown to outperform random sampling with respect to statistical confidence for representing the process variation. In addition, a chemometric approach, which utilizes only pure component raw materials to develop an NIRS model sensitive to API concentration, is discussed with the advantage that it does not require tablets at multiple API levels. Prospective applications of this sample selection strategy are also addressed.     

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.     

Two new spectrophotometric approaches to the multicomponent analysis of the acetaminophen and caffeine in tablets by classical least-squares and principal component regression techniques

Classical least-squares (CLS) and principal component regression (PCR) techniques were proposed for the simultaneous analysis of tablets containing acetaminophen and caffeine without using a chemical separation procedure. The chemometric calibrations were prepared by measuring the absorbances values at the 15 wavelengths in the spectral region 215-285 nm and by using a training set of the mixtures of both drugs in 0.1 M HCI. The obtained chemometric calibrations were used for the estimation of acetaminophen and caffeine in samples. The numerical calculations were performed with the 'MAPLE V' software. By applying two techniques to synthetic mixtures, the mean recoveries and the relative standard deviations in the CLS and PCR techniques were found as 99.5 and 1.29, 99.7 and 1.00% for acetaminophen and 99.9 and 1.92, 100.0 and 1.178% for caffeine, respectively. Our results were compared with those obtained previously by one of us considering HPLC method as a reference method. These two methods were successfully applied to a pharmaceutical tablet formulation of two drugs.     

A near-infrared spectroscopic investigation of relative density and crushing strength in four-component compacts

Near-infrared spectroscopy (NIRS) is commonly employed for the analysis of chemical and physical attributes of intact pharmaceutical compacts. Specifically, NIRS has proven useful in the nondestructive measurement of tablet hardness or crushing strength. Near-infrared (NIR) reflectance and transmittance spectra were acquired for 174 13-mm compacts, which were produced according to a four-constituent mixture design (29 points) composed of anhydrous theophylline, lactose monohydrate, microcrystalline cellulose, and soluble starch. Six compacts were produced for each design point by compacting at multiple pressures. Physical testing and regression analyses were used to model the effect of variation in relative density (and crushing strength) on NIR spectra. Chemometric analyses demonstrated that the overall spectral variance was strongly influenced by anhydrous theophylline as a result of the experimental design and the component's spectroscopic signature. The calibration for crushing strength was more linear than the relative density model, although accuracy was poorer in comparison to the density model due to imprecision of the reference measurements. Based on the consideration of reflectance and transmittance measurements, a revised rationalization for NIR sensitivity to compact hardness is presented.     

Quality by design approach of a pharmaceutical gel manufacturing process,part 2: Near infrared monitoring of composition and physical parameters

We applied the principles of quality by design to the production process of a pharmaceutical gel by using the near infrared spectroscopy (NIRS) technique in combination with multivariate chemometric tools. For this purpose, we constructed a D‐optimal experimental design having normal operational condition (NOC) batches as central point. The primary aim here was to develop an expeditious NIRS method for determining the composition of a pharmaceutical gel and assess the temporal changes in major physical factors affecting the quality of the product (specifically, viscosity and pH). Gel components were quantified by using partial least squares (PLS) calibration models of the PLS1 type. The study was completed by using the batch statistical process control method to compare product batches included in the experimental design with NOC batches. Similarities and differences between the two types of batches were identified by using control charts for residuals (Q‐statistic) and Hotteling's T2 (D‐statistic). The ensuing models, which were subject to errors less than 5%, allowed the gel production process to be effectively monitored. As shown in this work, the NIRS technique is a highly suitable tool for process analytical technology. © 2011 Wiley‐Liss, Inc. and the American Pharmacists Association J Pharm Sci 100:4442–4451, 2011     

Prediction of Dissolution Profiles From Process Parameters,Formulation, and Spectroscopic Measurements

This study utilized multiple modeling approaches to predict immediate release tablet dissolution profiles of 2 model drugs: theophylline and carbamazepine. Two sets of designs of experiments were applied based on individual drug characteristics to build in adequate dissolution variability. The tablets were scanned using a near-infrared (NIR) spectrometer and then subjected to in vitro dissolution test at critical time points. Because of the inherent difference in dissolution profiles, a hierarchical modeling approach was applied for theophylline data, whereas global models were constructed from carbamazepine data. The partial least squares models were trained using 3 predictor sets including (1) formulation, material, and process variables, (2) NIR spectra, and (3) a combination of both. The dependent variables of the models were the dissolution profiles, which were presented either as parameters of Weibull fitting curves or raw data. The comparison among the predictive models revealed that the incorporation of NIR spectral information in calibration reduced prediction error in the carbamazepine case but undermined the performance of theophylline models. It suggests that the modeling strategy for dissolution prediction of pharmaceutical tablets should not be universal but on a case-by-case basis.     

Near-Infrared Spectroscopy as a Nondestructive Alternative to Conventional Tablet Hardness Testing

Purpose. Near-infrared reflectance Spectroscopy (NIRS) was used to evaluate and quantify the effect of compression force on the NIR spectra of tablets. Methods. Flat, white tablets with no orientation (scoring, etc.) were manufactured on a Stokes Rotary Tablet Press. NIRS was used to predict tablet hardness on the following four formulations and one placebo matrix: hydrochlorothiazide (HCTZ) 15% and 20% in a placebo matrix (microcrystalline cellulose and magnesium stearate), and chlorpheniramine maleate (CTM) 2% and 6% in a placebo matrix. Five or six levels of tablet hardness from 2 to 12 kg were used for each formulation. Laboratory hardness data was compared to NIR reflectance data using a NIRSystems Rapid Content Analyzer^®. Multiple linear regression and partial least squares regression techniques were used to determine the relationship between tablet hardness and NIRS spectra. Results. An increase in tablet hardness produced an upward shift (increase in absorbance) in the NIRS spectra. A series of equations was developed by calibrating tablet hardness data against NIR reflectance response for each formulation. The results of NIRS hardness prediction were at least as precise as the laboratory hardness test (SE = 0.32). Conclusions. A NIRS method is presented which has the potential as an alternative to conventional hardness testing of tablets.     

A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies

Near-infrared spectroscopy (NIRS) is a fast and non-destructive analytical method. Associated with chemometrics, it becomes a powerful tool for the pharmaceutical industry. Indeed, NIRS is suitable for analysis of solid, liquid and biotechnological pharmaceutical forms. Moreover, NIRS can be implemented during pharmaceutical development, in production for process monitoring or in quality control laboratories.This review focuses on chemometric techniques and pharmaceutical NIRS applications. The following topics are covered: qualitative analyses, quantitative methods and on-line applications. Theoretical and practical aspects are described with pharmaceutical examples of NIRS applications.     

In-line monitoring and interpretation of an indomethacin anti-solvent crystallization process by near-infrared spectroscopy (NIRS)

PAT (process analytical technology) has been emphasized as one of key elements for the full implementation of QbD (quality-by-design) in the pharmaceutical area. NIRS (near-infrared spectroscopy) has been studied intensively as an in-line/on-line monitoring tool in chemical and biomedical industries. A precise and reliable monitoring of the particle characteristics during crystallization along with a suitable control strategy should be highly encouraged for the conformance to new quality system of pharmaceutical products. In this study, the anti-solvent crystallization process of indomethacin (IMC) was monitored using an in-line NIRS. IMC powders were produced via anti-solvent crystallization using two schemes; ‘S-to-A’ (solvent-to-antisolvent) and ‘A-to-S’ (antisolvent-to-solvent). In-line NIR spectra were analyzed by a PCA (principal component analysis) method. Although pure α-form IMC powder was resulted under A-to-S scheme, a mixture of the α-form and γ-form was produced for S-to-A case. By integrating the PCA results with off-line characterization (SEM, XRD, DSC) data, the crystallization process under each scheme was elucidated by three distinct consecutive steps. It was demonstrated that in-line NIRS, combined with PCA, can be very useful to monitor in real time and interpret the anti-solvent crystallization process with respect to the polymorphism and particle size.     

Near-infrared reflection spectroscopy (NIRS) as a successful tool for simultaneous identification and particle size determination of amoxicillin trihydrate

A successful application of NIR spectroscopy (NIRS) in combination with multivariate data analysis (MVA) for the simultaneous identification and particle size determination of amoxicillin trihydrate particles was developed. Particle size analysis was ascertained by NIRS in diffuse reflection mode on different particle size fractions of amoxicillin trihydrate with D90 particle diameters ranging from 6.9 to 21.7 μm. The present problem of fractionating the powder into good enough size fractions to achieve a stable calibration model was solved. By probing dried suspensions measurement parameters were optimized and further combined with the best suitable chemometric operations. Thereby the quality of established regression models could be improved considerably. A linear coherence between particle size and absorbance signal was found at specific wavenumbers. Satisfactory clustering by particle size was achieved by principal component analysis (PCA) whereas partial least squares regression (PLSR) and principal component regression (PCR) was compared for quantitatively calibrating the NIRS data. PLSR turned out to predict unknown test samples slightly better than PCR.     

Assessment of Robustness for a Near-Infrared Concentration Model for Real-Time Release Testing in a Continuous Manufacturing Process

This study describes the robustness test of a transmission near-infrared spectroscopic (NIRS) model for prediction of drug concentration in core tablets as part of real-time release testing (RTRt) efforts for a continuous manufacturing process. Seven calibration blend samples were prepared spanning a concentration range from 70 to 130% of the active pharmaceutical ingredient (API) target level with tablets prepared with laboratory-scale equipment, and their NIR spectra were obtained to develop a partial least squares (PLS) calibration model. The calibration model’s accuracy was assessed with an independent set of tablets obtaining a root mean standard error of prediction (RMSEP) of less than 1.5% label claim at each concentration level. However, a decrease in the prediction of API concentration of tablets exposed to the production environment was observed indicating lack of robustness as a RTRt method. The API is known to interchange solvate molecules with water molecules from the environment. Even though this exchange does not affect product quality, it affects the NIR spectra. The calibration model was then optimized by excluding O–H bands from the spectral range and shown to predict accurately the drug concentration in tablets for up to 113 h after tablet compaction. The calibration model was updated by including tablets produced in the continuous manufacturing line within the calibration model. The updated calibration model was used to predict tablets from three different continuous manufacturing runs, involving different lots of excipients and drug. The results from the updated calibration model showed excellent agreement with reference HPLC results.