NIR spectrometry for counterfeit drug detection

Fully Integrated Ultrathin Solid Immersion Grating Microspectrometer for Handheld Visible and Near-Infrared Spectroscopic Applications

Despite advances in microfabrication, compact spectrometers still face challenges in shrinking their size without sacrificing optical performance. Here,  the solid immersion grating microspectrometer (SIG-µSPEC) for high spectral resolution in a broad operational wavelength range is reported. The spectroscopic module incorporates a silicon microslit, index-matched lens, plane mirrors, solid immersion grating (SIG), and a CMOS line sensor within a small form factor. The SIG facilitates high angular dispersion of light on a planar focal plane, resulting in an average spectral resolution of 5.8 nm, with over 76% maximum sensitivity from 400 to 800 nm. SIG-µSPEC measures the spectral reflectance of fruits at different ripening stages, clearly revealing changes in the chlorophyll absorption band. The measured spectrum is further utilized for the precise prediction of the soluble solid content (SSC) levels, achieving a high correlation (R2 = 0.91) and a ratio of prediction-to-deviation of 2.36. This compact microspectrometer holds the potential for precise and non-invasive spectral analysis across point-of-care fields.

A Review of Pharmaceutical Robot based on Hyperspectral Technology

The quality and safety of medicinal products are related to patients’ lives and health. Therefore, quality inspection takes a key role in the pharmaceutical industry. Most of the previous solutions are based on machine vision, however, their performance is limited by the RGB sensor. The pharmaceutical visual inspection robot combined with hyperspectral imaging technology is becoming a new trend in the high-end medical quality inspection process since the hyperspectral data can provide spectral information with spatial knowledge. Yet, there is no comprehensive review about hyperspectral imaging-based medicinal products inspection. This paper focuses on the pivotal pharmaceutical applications, including counterfeit drugs detection, active component analysis of tables, and quality testing of herbal medicines and other medical materials. We discuss the technology and hardware of Raman spectroscopy and hyperspectral imaging, firstly. Furthermore, we review these technologies in pharmaceutical scenarios. Finally, the development tendency and prospect of hyperspectral imaging technology-based robots in the field of pharmaceutical quality inspection is summarized.

Discrimination of commercial ibuprofen tablets by using a button sample holder and mid-infrared spectroscopy

Infrared spectra obtained from commercial ibuprofen tablets are categorized by using principal component analysis. A stainless steel abrasive button is used to sample the coatings and interiors of ibuprofen tablets with three different formulations. Rubbing the button wire mesh surface across tablet surfaces removes material for analysis. Small fragments are retained within mesh void spaces and larger fragments are swept away prior to analyses. Infrared spectra for tablet coatings exhibit significant differences and can be used for identification. Tablet interior compositions consisting primarily of ibuprofen from different manufacturers are more distinguishable from pre-processed spectra than from spectrum second derivatives. The speed and sensitivity afforded by this methodology suggests that rapid detection of counterfeit pharmaceuticals based on mid-infrared spectroscopy measurements of microgram quantities of material removed with a button sample holder is feasible.

Establishment of instrument operation qualification and routine performance qualification procedures for handheld near-infrared spectrometers used at different locations within a laboratory network

Quality assurance of finished pharmaceuticals is a necessity in ensuring the safety of consumers. There is a need for low-cost and portable rapid screening methods of pharmaceuticals in resource limited areas. Recent advances in technology have made handheld and low-cost diffuse reflectance spectrometers available to the public. While these handheld spectrometers offer advantages over benchtop spectrometers, the accuracy and repeatability must be assessed before these instruments can be used for quality assurance screening. Here, five handheld spectrometers of the same model were purchased, where an in-house installation qualification and operational qualification (IQOQ) was subsequently established for the instruments. Wavelength and photometric accuracy (and repeatability), spectroscopic noise, stray light, and bandpass were assessed between instruments. Results were found to be consistent between the spectrometers, passing IQOQ procedures, and were determined to be ready for field use. Once the handheld spectrometer's performance was verified, a practical and low-cost daily performance verification was established using common high density polyethylene vial caps on location in South Africa, Thailand, and the United States. A Mahalanobis distance-based classifier found the five spectrometers to be in agreement.

Texture Analysis of Dried Droplets for the Quality Control of Medicines

The quality control of medicines guarantees the effectiveness of treatments for diseases. We explore the use of texture analysis of patterns in dried droplets as a tool to readily detect both impurities and changes in drug concentration. Four types of medicines associated with different routes of administration were analyzed: Methotrexate, Ciprofloxacin, Clonazepam, and Budesonide. We use NaCl and a hot substrate at 63 ∘C to promote aggregate formation and to reduce droplet drying time. Depending on the medicine, optical microscopy reveals different complex aggregates such as circular to oval splatters, fern-like islands, crown shapes, crown needle-like and bump-like patterns as well as dendritic branched and star-like crystals. We use some physical features of the stains (as the stain diameter and superficial area) and gray level co-occurrence matrix (GLCM) to characterize patterns of dried droplets. Finally, we show that structural analysis of stains can achieve 95% accuracy in identifying medicines with 30% water dilution, while it achieves 99% accuracy in detecting drugs with 10% other substances.

Authentication of Antibiotics Using Portable Near-Infrared Spectroscopy and Multivariate Data Analysis

Counterfeit medicines represent a global public health threat warranting the development of accurate, rapid, and nondestructive methods for their identification. Portable near-infrared (NIR) spectroscopy offers this advantage. This work sheds light on the potential of combining NIR spectroscopy with principal component analysis (PCA) and soft independent modelling of class analogy (SIMCA) for authenticating branded and generic antibiotics. A total of 23 antibiotics were measured "nondestructively" using a portable NIR spectrometer. The antibiotics corresponded to six different active pharmaceutical ingredients being: amoxicillin trihydrate and clavulanic acid, azithromycin dihydrate, ciprofloxacin hydrochloride, doxycycline hydrochloride, and ofloxacin. NIR spectra were exported into Matlab R2018b where data analysis was applied. The results showed that the NIR spectra of the medicines showed characteristic features that corresponded to the main excipient(s). When combined with PCA, NIR spectroscopy could distinguish between branded and generic medicines and could classify medicines according to their manufacturing sources. The PCA scores showed the distinct clusters corresponding to each group of antibiotics, whereas the loadings indicated which spectral features were significant. SIMCA provided more accurate classification over PCA for all antibiotics except ciprofloxacin which products shared many overlapping excipients. In summary, the findings of the study demonstrated the feasibility of portable NIR as an initial method for screening antibiotics.

Exploring the chemical profile of designer drugs by ESI(+) and PSI(+) mass spectrometry-An approach on the fragmentation mechanisms and chemometric analysis

The consumption of design drugs, frequently known as new psychoactive substances (NPS), has increased considerably worldwide, becoming a severe issue for the responsible governmental agencies. These illicit substances can be defined as synthetic compounds produced in clandestine laboratories in order to act as analogs of schedule drugs mimetizing its chemical structure and improving its pharmacological effects while hampering the control and making regulation more complicated. In this way, the development of new methodologies for chemical analysis of NPS drugs is indispensable to determine a novel class of drugs arising from the underground market. Therefore, this work shows the use of high-resolution mass spectrometry Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) applying different ionization sources such as paper spray ionization (PSI) and electrospray ionization (ESI) in the evaluation of miscellaneous of seized drugs samples as blotter paper (n = 79) and tablet (n = 100). Also, an elucidative analysis was performed by ESI(+)MS/MS experiments, and fragmentation mechanisms were proposed to confirm the chemical structure of compounds identified. Besides, the results of ESI(+) and PSI(+)-FT-ICR MS were compared with those of GC-MS, revealing that ESI(+)MS showed greater detection efficiency among the methodologies employed in this study. Moreover, this study stands out as a guide for the chemical analysis of NPS drugs, highlighting the differences between the techniques of ESI(+)-FT-ICR MS, PSI(+)-FT-ICR MS, and GC-MS.

Spectroscopic techniques combined with chemometrics for fast on-site characterization of suspected illegal antimicrobials

The threats of substandard and falsified (SF) antimicrobials, posed to public health, include serious adverse drug effects, treatment failures and even development of antimicrobial resistance. Next to these issues, it has no doubt that efficient methods for on-site screening are required to avoid that SF antimicrobials reach the patient or even infiltrate the legal supply chain. This study aims to develop a fast on-site screening method for SF antimicrobials using spectroscopic techniques (mid infrared, benchtop near infrared, portable near infrared and Raman spectroscopy) combined with chemometrics. 58 real-life illegal antimicrobials (claiming 18 different antimicrobials and one beta-lactamase inhibitor) confiscated by the Belgian Federal Agency for Medicines and Health Products (FAMHP) and 14 genuine antimicrobials were analyzed and used to build and validate models. Two types of models were developed and validated using supervised chemometric tools. One was used for the identification of the active pharmaceutical ingredients (APIs) by applying partial least squares-discriminant analysis (PLS-DA) and another one was used for the detection of non-compliant (overdosed or underdosed) samples by applying PLS-DA, k-nearest neighbors (k-NN) and soft independent modelling by class analogy (SIMCA). The best model capable of identifying amoxicillin and clavulanic acid (co-amoxiclav), azithromycin, co-trimoxazole and amoxicillin was based on the mid-infrared spectra with a correct classification rate (ccr) of 100%. The optimal model capable of detecting non-compliant samples within the combined group of amoxicillin and co-amoxiclav via SIMCA showed a ccr for the test set of 88% (7/8) using mid infrared or benchtop near infrared spectroscopy. The best model for detecting non-compliant samples within the group of amoxicillin via SIMCA was obtained using mid-infrared or Raman spectra, resulting in a ccr of 80% for the test set (4/5) and a ccr for calibration of 100%. For the group of co-amoxiclav, the optimal models showed a ccr of 100% for the detection of non-compliant samples by applying mid-infrared, benchtop near infrared or portable near infrared spectroscopy. Taken together, the obtained models, hyphenating spectroscopic techniques and chemometrics, enable to easily identify suspected SF antimicrobials and to differentiate non-compliant samples from compliant ones.

Review of on-line and near real-time spectroscopic monitoring of processes relevant to nuclear material management

Spectroscopic chemometric based on-line monitoring of used nuclear fuel (UNF) reprocessing solutions and characterization of legacy nuclear waste (LNW) stored at Hanford is discussed in this manuscript. Utilizing on-line and near real-time monitoring, as opposed to traditional off-line monitoring, can significantly reduce the cost, risk and improve the efficiency of characterizing UNF and LNW processing streams. Specifically, this manuscript will highlight the benefits of spectroscopy-based monitoring approaches, which generally include the ability to collect data non-destructively. Furthermore, significant literature precedence supports the use of various real-time analysis methods, including chemometric analysis, that enable near-instantaneous conversion of spectroscopic data into information useable by process operators. This approach can accurately quantify and qualify nuclear material in near-real time enabling immediate condition characterization and potential diversion detection within UNF reprocessing streams and LNW. The ability to be applied in a real reprocessing plant and in an actual Hanford waste tank/transfer pipe has been demonstrated by applying this technique to accurately quantify analytes in real UNF streams and LNW samples. The future development of spectroscopy-based on-line monitoring is also discussed in this manuscript.

Chemometric Methods for Spectroscopy-Based Pharmaceutical Analysis

Spectroscopy is widely used to characterize pharmaceutical products or processes, especially due to its desirable characteristics of being rapid, cheap, non-invasive/non-destructive and applicable both off-line and in-/at-/on-line. Spectroscopic techniques produce profiles containing a high amount of information, which can profitably be exploited through the use of multivariate mathematic and statistic (chemometric) techniques. The present paper aims at providing a brief overview of the different chemometric approaches applicable in the context of spectroscopy-based pharmaceutical analysis, discussing both the unsupervised exploration of the collected data and the possibility of building predictive models for both quantitative (calibration) and qualitative (classification) responses.

Infrared spectroscopy and spectroscopic imaging in forensic science

Infrared spectroscopy and spectroscopic imaging, are robust, label free and inherently non-destructive methods with a high chemical specificity and sensitivity that are frequently employed in forensic science research and practices. This review aims to discuss the applications and recent developments of these methodologies in this field. Furthermore, the use of recently emerged Fourier transform infrared (FT-IR) spectroscopic imaging in transmission, external reflection and Attenuated Total Reflection (ATR) modes are summarised with relevance and potential for forensic science applications. This spectroscopic imaging approach provides the opportunity to obtain the chemical composition of fingermarks and information about possible contaminants deposited at a crime scene. Research that demonstrates the great potential of these techniques for analysis of fingerprint residues, explosive materials and counterfeit drugs will be reviewed. The implications of this research for the examination of different materials are considered, along with an outlook of possible future research avenues for the application of vibrational spectroscopic methods to the analysis of forensic samples.

Rapid identification of oral solid dosage forms of counterfeit pharmaceuticals by discrimination using near-infrared spectroscopy

BACKGROUND

Since it can take an enormous amount of time and cost to discriminate counterfeit medicines by using conventional methods, counterfeit medicines has been spread in the world markets.

OBJECTIVE

The purpose of this study was to develop a rapid and simple analytical method to discriminate counterfeit drugs using near infrared (NIR) spectroscopy.

METHODS

Seven types of brand name tablet and generic tablets containing atorvastatin calcium sesquihydrate (AT) preparations were used as simulated counterfeit medicines. NIR spectra of 35 AT tablet products were measured using a diffuse reflection method.

RESULTS

The NIR spectral data were analyzed by principal component analysis (PCA). The PCA results suggested that the model had sufficient accuracy to discriminate the 7 types for AT tablets. The NIR spectral data were also analyzed using a soft independent modeling of class analogy (SIMCA) method. Predicting the classification of the AT tablet samples was performed based on all the validated AT tablet data using the SIMCA model, and the probability of classification of 7 types was 100%. The discrimination power spectrum of the SIMCA model indicated significant patterns based on diluents.

CONCLUSIONS

The PCA and SIMCA classification of the AT tablets were depended on the major excipient combinations.

Poly(aryleneethynylene) Tongue That Identifies Nonsteroidal Anti-Inflammatory Drugs in Water: A Test Case for Combating Counterfeit Drugs

We report a sensor array composed of a highly fluorescent positively charged poly(para-phenyleneethynylene) P1 and its complex C with a negatively charged pyridine-containing poly(para-aryleneethynylene) P2 (quencher) at pH 10 and pH 13; a sensor field composed of four elements, P1 (pH 10), P1 (pH 13), C (pH 10), and C (pH 13), results. The elements of this small sensor field experience either fluorescence turn on or fluorescence quenching upon exposure toward nonsteroidal anti-inflammatory drugs (NSAIDs), such as aspirin, ibuprofen, diclofenac, or naproxen. The combined responses of the sensor field are analyzed by linear discriminant analysis (LDA). All of the NSAIDs were identified and discriminated, and the sensing mechanism, hydrophobic versus electrostatic, was discussed.

NIR hyperspectral imaging to evaluate degradation in captopril commercial tablets

Pharmaceutical quality control is important for improving the effectiveness, purity and safety of drugs, as well as for the prevention or control of drug degradation. In the present work, near infrared hyperspectral images (HSI-NIR) of tablets with different expiration dates were employed to evaluate the degradation of captopril into captopril disulfide in different layers, on the top and on the bottom surfaces of the tablets. Multivariate curve resolution (MCR) models were used to extract the concentration distribution maps from the hyperspectral images. Afterward, multivariate image techniques were applied to the concentration distribution maps (CDMs), to extract features and build models relating the main characteristics of the images to their corresponding manufacturing dates. Resolution methods followed by extracting features were able to estimate the tablet manufacture date with a prediction error of 120days. The model developed could be useful to evaluate whether a sample shows a degradation pattern consistent with the date of manufacturing or to detect abnormal behaviors in the natural degradation process of the sample. The information provided by the HIS-NIR is important for the development of the process (QbD), looking inside the formulation, revealing the behavior of the active pharmaceutical ingredient (API) during the product's shelf life.

Chemometrics and the identification of counterfeit medicines-A review

This review article provides readers with a number of actual case studies dealing with verifying the authenticity of selected medicines supported by different chemometric approaches. In particular, a general data processing workflow is discussed with the major emphasis on the most frequently selected instrumental techniques to characterize drug samples and the chemometric methods being used to explore and/or model the analytical data. However, further discussion is limited to a situation in which the collected data describes two groups of drug samples - authentic ones and counterfeits.

A rapid Fourier-transform infrared (FTIR) spectroscopic method for direct quantification of paracetamol content in solid pharmaceutical formulations

A transmission FTIR spectroscopic method was developed for direct, inexpensive and fast quantification of paracetamol content in solid pharmaceutical formulations. In this method paracetamol content is directly analyzed without solvent extraction. KBr pellets were formulated for the acquisition of FTIR spectra in transmission mode. Two chemometric models: simple Beer's law and partial least squares employed over the spectral region of 1800-1000 cm(-1) for quantification of paracetamol content had a regression coefficient of (R(2)) of 0.999. The limits of detection and quantification using FTIR spectroscopy were 0.005 mg g(-(1) and 0.018 mg g(-1), respectively. Study for interference was also done to check effect of the excipients. There was no significant interference from the sample matrix. The results obviously showed the sensitivity of transmission FTIR spectroscopic method for pharmaceutical analysis. This method is green in the sense that it does not require large volumes of hazardous solvents or long run times and avoids prior sample preparation.

PAT: From Western solid dosage forms to Chinese materia medica preparations using NIR-CI

Near-infrared chemical imaging (NIR-CI) is an emerging technology that combines traditional near-infrared spectroscopy with chemical imaging. Therefore, NIR-CI can extract spectral information from pharmaceutical products and simultaneously visualize the spatial distribution of chemical components. The rapid and non-destructive features of NIR-CI make it an attractive process analytical technology (PAT) for identifying and monitoring critical control parameters during the pharmaceutical manufacturing process. This review mainly focuses on the pharmaceutical applications of NIR-CI in each unit operation during the manufacturing processes, from the Western solid dosage forms to the Chinese materia medica preparations. Finally, future applications of chemical imaging in the pharmaceutical industry are discussed.

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.

Estimation of ibuprofen in urine and tablet formulations by transmission Fourier Transform Infrared spectroscopy by partial least square

A rapid, reliable and cost effective analytical procedure for the estimation of ibuprofen in pharmaceutical formulations and human urine samples was developed using transmission Fourier Transform Infrared (FT-IR) spectroscopy. For the determination of ibuprofen, a KBr window with 500 μm spacer was used to acquire the FT-IR spectra of standards, pharmaceuticals as well as urine samples. Partial least square (PLS) calibration model was developed based on region from 1807 to 1,461 cm(-1) using ibuprofen standards ranging from 10 to 100 μg ml(-1). The developed model was evaluated by cross-validation to determine standard error of the models such as root mean square error of calibration (RMSEC), root mean square error of cross validation (RMSECV) and root mean square error of prediction (RMSEP). The coefficient of determination (R(2)) achieved was 0.998 with minimum errors in RMSEC, RMSECV and RMSEP with the value of 1.89%, 1.63% and 4.07%, respectively. The method was successfully applied to urine and pharmaceutical samples and obtained good recovery (98-102%).

An advanced multivariate approach for processing X-ray fluorescence spectral and hyperspectral data from non-invasive in situ analyses on painted surfaces

In the last decades, in situ non-invasive analytical techniques have been widely used for the analysis of paintings. These techniques are useful to extensively map the surface in a non-invasive way, in order to identify the most representative areas to be sampled. When spectroscopic investigations, such as X ray fluorescence (XRF), are conducted, they usually imply the acquisition of a huge amount of measurements. Subsequently, all these data should be processed in situ, in order to immediately support the sampling strategies. To this aim, an appropriate and fast strategy for multivariate treatment of XRF spectral and hyperspectral data sets is presented, able to account for inter-correlation among variables, which is an issue of high importance for elemental analyses. The main advantage of the approach is that XRF spectral profiles are analysed directly, without computation of derived parameters, by means of principal component analysis (PCA). This procedure allows a fast interpretation of results that can be accomplished in situ. Particular attention was paid to the selection of proper spectral pre-treatments to be applied on data together with the use of several chemometric tools (peak alignment, spectra normalisation and exploratory analysis) aimed at improving the interpretation of XRF results. In addition, the application of multivariate exploratory analysis on XRF hyperspectral maps was studied by using an interactive brushing procedure. The multivariate approach was validated on data obtained from the analysis of the famous Renaissance panel painting "The Ideal City", exhibited in Palazzo Ducale of Urbino, Italy.

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).

In-line prediction of drug release profiles for pH-sensitive coated pellets

A new method for the prediction of the drug release profiles during a running pellet coating process from in-line near infrared (NIR) measurements has been developed. The NIR spectra were acquired during a manufacturing process through an immersion probe. These spectra reflect the coating thickness that is inherently connected with the drug release. Pellets sampled at nine process time points from thirteen designed laboratory-scale coating batches were subjected to the dissolution testing. In the case of the pH-sensitive Acryl-EZE coating the drug release kinetics for the acidic medium has a sigmoid form with a pronounced induction period that tends to grow along with the coating thickness. In this work the autocatalytic model adopted from the chemical kinetics has been successfully applied to describe the drug release. A generalized interpretation of the kinetic constants in terms of the process and product parameters has been suggested. A combination of the kinetic model with the multivariate Partial Least Squares (PLS) regression enabled prediction of the release profiles from the process NIR data. The method can be used to monitor the final pellet quality in the course of a coating process.

Poor quality drugs: grand challenges in high throughput detection, countrywide sampling, and forensics in developing countries

Throughout history, poor quality medicines have been a persistent problem, with periodical crises in the supply of antimicrobials, such as fake cinchona bark in the 1600s and fake quinine in the 1800s. Regrettably, this problem seems to have grown in the last decade, especially afflicting unsuspecting patients and those seeking medicines via on-line pharmacies. Here we discuss some of the challenges related to the fight against poor quality drugs, and counterfeits in particular, with an emphasis on the analytical tools available, their relative performance, and the necessary workflows needed for distinguishing between genuine, substandard, degraded and counterfeit medicines.

Near-infrared spectroscopic applications for diagnosis of endometrial carcinoma

NIR spectra of 77 endometrium sections (malignant, hyperplasia, and normal samples) are collected. Partial least squares discriminant analysis (PLS-DA) and fuzzy rule-building expert systems (FuRES) are used for classification based on the NIR spectral data. The classification ability of two classifiers is evaluated by using ten bootstraps and five Latin partitions. The results indicate that the classification ability of FuRES is better than that of PLS-DA. The sensitivity, specificity, and accuracy obtained from FuRES for malignant endometrium diagnosis are 90.0±0.7, 95.0±0.8, and 93.1±0.8%, respectively. The results demonstrate that NIR spectroscopy combined with the FuRES technique is promising for the classification of endometrial specimens and for practical diagnostic applications.