Spectroscopic Techniques for Nondestructive Quality Inspection of Pharmaceutical Products: A Review

Kandpal, Lalit Mohan,Park, Eunsoo,Tewari, Jagdish,Cho, Byoung-Kwan Korean Society for Agricultural Machinery 2015 바이오시스템공학 Vol.40 No.4

Spectroscopy is an emerging technology for the quality assessment of pharmaceutical samples, from tablet manufacturing to final quality assurance. The traditional methods for the quality management of pharmaceutical tablets are time consuming and destructive, while spectroscopic techniques allow rapid analysis in a non-destructive manner. The advantage of spectroscopy is that it collects both spatial and spectral information (called hyperspectral imaging), which is useful for the chemical imaging of pharmaceutical samples. These chemical images provide both qualitative and quantitative information on tablet samples. In the pharmaceutics, spectroscopic techniques are used for a variety of applications, such as analysis of the homogeneity of powder samples as well as determination of particle size, product composition, and the concentration, uniformity, and distribution of the active pharmaceutical ingredient in solid tablets. This review paper presents an introduction to the applications of various spectroscopic techniques such as hyperspectroscopy and vibrational spectroscopies (Raman spectroscopy, FT-NIR, and IR spectroscopy) for the quality and safety assessment of pharmaceutical solid dosage forms. In addition, various chemometric techniques that are highly essential for analyzing the spectroscopic data of pharmaceutical samples are also reviewed.

Short wave infrared (SWIR) hyperspectral imaging technique for examination of aflatoxin B₁ (AFB₁) on corn kernels

Kandpal, L.M.,Lee, S.,Kim, M.S.,Bae, H.,Cho, B.K. Butterworths ; Taylor Francis ; Elsevier Science 2015 FOOD CONTROL Vol.51 No.-

Aflatoxins are toxic metabolites produced by the fungi Aspergillus flavus and Aspergillus parasiticus. They can contaminate a wide range of crops before harvest and during storage. Contaminated grains are associated with economic losses for cultivators as well as potential health hazards to both humans and animals. In this study, a short-wave infrared (SWIR) hyperspectral imaging technique was utilized to detect aflatoxin contamination on corn kernels. Corn samples were inoculated with four different aflatoxin B<SUB>1</SUB> (AFB1) concentrations (10, 100, 500 and 1000 μg/kg) while control samples were surface-disinfected with a PBS solution. Both infected and control samples were scanned with an SWIR hyperspectral system over the spectral range of 1100-1700 nm. A partial least squares discriminant analysis (PLS-DA) model was developed to categorize control and infected kernels and the highest overall classification accuracy yielded from the developed model was 96.9%. Spectral deviation was observed between the control and inoculated samples as the AFB1 concentrations increased. In addition, the contamination map generated with the PLS-DA model provided the visual appearance of infected samples. Our results suggest that SWIR hyperspectral imaging is a rapid, accurate, and non-destructive technique for the detection of toxic metabolites in grains and could be an alternative to manual techniques.

Quality assessment of pharmaceutical tablet samples using Fourier transform near infrared spectroscopy and multivariate analysis

Kandpal, Lalit Mohan,Tewari, Jagdish,Gopinathan, Nishanth,Stolee, Jessica,Strong, Rick,Boulas, Pierre,Cho, Byoung-Kwan Elsevier 2017 Infrared physics & technology Vol.85 No.-

<P><B>Abstract</B></P> <P>Determination of the content uniformity, assessed by the amount of an active pharmaceutical ingredient (API), and hardness of pharmaceutical materials is important for achieving a high-quality formulation and to ensure the intended therapeutic effects of the end-product. In this work, Fourier transform near infrared (FT-NIR) spectroscopy was used to determine the content uniformity and hardness of a pharmaceutical mini-tablet and standard tablet samples. Tablet samples were scanned using an FT-NIR instrument and tablet spectra were collected at wavelengths of 1000–2500nm. Furthermore, multivariate analysis was applied to extract the relationship between the FT-NIR spectra and the measured parameters. The results of FT-NIR spectroscopy for API and hardness prediction were as precise as the reference high-performance liquid chromatography and mechanical hardness tests. For the prediction of mini-tablet API content, the highest coefficient of determination for the prediction ( <SUP> R 2 </SUP> p ) was found to be 0.99 with a standard error of prediction (SEP) of 0.72mg. Moreover, the standard tablet hardness measurement had a <SUP> R 2 </SUP> p value of 0.91 with an SEP of 0.25kg. These results suggest that FT-NIR spectroscopy is an alternative and accurate nondestructive measurement tool for the detection of the chemical and physical properties of pharmaceutical samples.</P> <P><B>Highlights</B></P> <P> <UL> <LI> FT-NIR technique was used for investigation of content uniformity and hardness of pharmaceutical tablet samples. </LI> <LI> Multivariate analysis predicted API and hardness of tablets with higher accuracy. </LI> <LI> FT-NIR demonstrated a great potential tool for detection of chemical and physical properties of the pharmaceutical samples. </LI> </UL> </P>

A Review of the Applications of Spectroscopy for the Detection of Microbial Contaminations and Defects in Agro Foods

Kandpal, Lalit Mohan,Cho, Byoung-Kwan Korean Society for Agricultural Machinery 2014 바이오시스템공학 Vol.39 No.3

Recently, spectroscopy has emerged as a potential tool for quality evaluation of numerous food and agricultural products because it provides information regarding both spectral distribution and image features of the sample (i.e., hyperspectral imaging). Spectroscopic techniques reveal hidden information regarding the sample and do so in a non-destructive manner. This review describes the various approaches of spectroscopic modalities, especially hyperspectroscopy and vibrational spectroscopies (i.e., Raman spectroscopy and Fourier transform near infrared spectroscopy) combined with chemometrics for the non-destructive assessment of contaminations and defects in agro-food products.

Near-infrared hyperspectral imaging system coupled with multivariate methods to predict viability and vigor in muskmelon seeds

Kandpal, L.M.,Lohumi, S.,Kim, M.S.,Kang, J.S.,Cho, B.K. Elsevier Sequoia 2016 Sensors and actuators. B Chemical Vol.229 No.-

A near-infrared (NIR) hyperspectral imaging (HSI) system was used to predict viability and vigor (in term of germination periods) in muskmelon seeds. Hyperspectral images of muskmelon seeds were acquired using a NIR push-broom HSI system covering the spectral range of 948-2494nm. After NIR spectra collection, all seeds underwent a germination test to confirm their viability and vigor. The spectra from seeds with 3 and 5 germination days and nongerminated seeds were further used for development of a classification model of partial least-squares discriminant analysis (PLSDA). Most effective wavelengths were selected using three model-based variable selection methods, i.e., variable important in projection (VIP), selectivity ratio (SR), and significance multivariate correlation (sMC), which selected 23, 18, and 19 optimal variables, respectively, from full set of 208 variables. The selected variables from different waveband selection methods were found genuine and significant for interpreting the prediction results of seed viability and vigor. Subsequently, the PLS-DA model was constructed using individual VIP-, SR-, or sMC-selected variables. The results demonstrated that the PLSDA model developed with the selected optimal variables from the different methods provided comparable results for the calibration set; however, the PLSDA-SR method afforded the highest classification accuracy (94.6%) for a validation set used to determine the viability and vigor of muskmelon seeds. The wavelengths selected by the different methods represents chemical components of the seed and the attribute of germination ability was chosen most often.

Raman spectral imaging technique for API detection in pharmaceutical microtablets

Kandpal, Lalit Mohan,Cho, Byoung-Kwan,Tewari, Jagdish,Gopinathan, Nishanth Elsevier 2018 Sensors and actuators. B, Chemical Vol.260 No.-

<P><B>Abstract</B></P> <P>In pharmaceutical manufacturing, quality monitoring of end products is essential to gain regulatory approval. In particular, monitoring the quantity of an active pharmaceutical ingredient (API) in the administered dosage is key to ensuring the content uniformity of the product. Thus, we herein aim to demonstrate the ability of the newly developed line-scan Raman hyperspectral imaging (RHSI) technique for the quantitative analysis of APIs in microtablet samples. Microtablets containing the API of interest and appropriate excipients of varying concentrations (i.e., 60–130% (w/w) API) were prepared by direct compression. The microtablet RHSI spectra were obtained over a wavelength range of 400–1800 cm<SUP>−1</SUP>. High-performance liquid chromatography was also employed as a reference method for the API assay. Multivariate analysis methods, including partial least squares and least-squares support vector machines, were employed to predict the API concentrations using the spectral and reference values of the microtablets. The developed models exhibited excellent prediction abilities for the API concentration, with a coefficient of correlation (R<SUP>2</SUP>) >0.95, which was associated with an error of <5% (w/w) API. Furthermore, visualization of the API concentrations and distributions in the microtablets was achieved through chemical imaging. These results confirmed that line-scan RHSI is a powerful tool for the characterization of pharmaceutical products. In addition, this approach is suitable for application in the pharmaceutical production line for the online inspection of bulk products and would be expected to easily replace conventional measurement techniques.</P> <P><B>Highlights</B></P> <P> <UL> <LI> The quantitative analysis of active pharmaceutical ingredients (APIs) was examined. </LI> <LI> Line-scan Raman hyperspectral imaging (RHSI) was employed for API analysis. </LI> <LI> Microtablets containing the API of interest were analyzed by RHSI. </LI> <LI> RHSI is suitable for use in the pharmaceutical production line for nondestructive quality control. </LI> </UL> </P>

Polymer Incorporated Electrochromic Device (ECD)

Suchita Kandpal,Tanushree Ghosh,Rajesh Kumar 한국고분자학회 2021 한국고분자학회 학술대회 연구논문 초록집 Vol.46 No.2

Polythiophene being a conducting polymer has been studied especially in electrochromism owing to its ease of processibility. In this work polythiophene has been doped with ethyl viologen to fabricate an ECD. The original device which was magenta in color turned transparent when a bias of 1 V was applied and then on increasing the bias to 1.4 V it turned bluish. Subsequently on removal of the bias the original color was restored indicating a reversible nature. Absorption spectroscopy was recorded to note the color contrast value and to perform time derivative study. The current v/s time response was recorded using the Keithley and subsequently typical device parameters were calculated. A switching time of 1/1.1s (77%, 67%, respectively) at a readout voltage of 1.4 V and a coloration efficiency value of ~275 indicates that the fabricated device shows excellent electrochromic properties.

An evaluation of the relative urbanisation in peri-urban villages affected by industrialisation: the case study of Bhiwandi in the Mumbai Metropolitan Region, India

Richa Kandpal,Izuru Saizen 대한공간정보학회 2019 Spatial Information Research Vol.27 No.2

The Mumbai Metropolitan Region in India has a history of uneven development with a concentration of population and employment in the urban core of Mumbai city. Recently, there has been an increased rate of development in other nodes outside Mumbai city. Evaluating the intra-regional inequalities will facilitate more focused planning based on contextual issues. The peri-urban villages of Bhiwandi Surrounding Notified Area are among the least planned areas within the metropolitan region, witnessing intensive industrial development and a host of other resultant problems. This study focuses on the calculation of a measure of relative urbanisation for these villages in order to identify areas that are at an advanced stage of transition from rural to urban. The measure is based upon demographic, social, economic, spatial and infrastructural parameters. Variables were selected with reference to existing research in the field of indices for urbanity and the definitions of ‘urban’ and ‘rural’ in context of India, and comprehensive scores were generated for each village. The results guide the theoretical analysis of the pattern of development in the region and the influence of urbanisation on the socio-economic changes and living conditions in the villages. Further, this study discusses the formulation of customised planning policies for different categories of peri-urban villages in the Indian context. Since the development in these villages is driven primarily by secondary and tertiary sector employment, it can be concluded that the traditional consideration of ‘rural’ as being predominantly agricultural should be reassessed for peri-urban villages.

Hyperspectral imaging technique for detection of API contents in pharmaceutical powder blends

( Lalit Mohan Kandpal ),( Anisur Rahman ),( Santosh Lohumi ),( Byoung-kwan Cho ) 한국농업기계학회 2016 한국농업기계학회 학술발표논문집 Vol.21 No.2

Currently, many offline technology (e.g., HPLC) is used in quality testing of pharmaceutical medications. However, such technique used for active pharmaceutical ingredient (API) monitoring are time consuming, and often destructive. Hence, more rapid and accurate techniques are needed for real-time testing and validation of the final product. In this study, the hyperspectral image monitoring technique was used to characterize the API of powder blend samples. The powder blends were prepared using a V-blender device to mix the API formulation excipients. The reflectance spectra of powder samples were obtained using a HSI system at a wavelength range from 400-2500 nm (visible near infrared and shortwave infrared HSI). A partial least square regression (PLSR) model was developed for the prediction of the API concentration. The overall model performed a strong coefficient of determination (R²p) of 0.99 along with a lowest error (RMSEP) of 0.85mg, for API prediction. Furthermore, concentration-mapped images not only provided the spatial distribution of the predicted API concentration into the powder surface but were also useful to ensure the specific API concentration was added in the final dosage from. The binary images of PLSR model detects all the pixels that are corresponding to the API component. Based on this observation, we concluded the PLSR model developed with HSI could be used to easily predict and visualize the API distribution in powder samples.

Review : A Review of the Applications of Spectroscopy for the Detection of Microbial Contaminations and Defects in Agro Foods

( Lalit Mohan Kandpal ),( Byoung Kwan Cho ) 한국농업기계학회 2014 바이오시스템공학 Vol.39 No.3

Recently, spectroscopy has emerged as a potential tool for quality evaluation of numerous food and agricultural products because it provides information regarding both spectral distribution and image features of the sample (i.e., hyperspectral imaging). Spectroscopic techniques reveal hidden information regarding the sample and do so in a non-destructive manner. This review describes the various approaches of spectroscopic modalities, especially hyperspectroscopy and vibrational spectroscopies (i.e., Raman spectroscopy and Fourier transform near infrared spectroscopy) combined with chemometrics for the non-destructive assessment of contaminations and defects in agro-food products.