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Ohashi R, Koide T, Fukami T. Effects of wet granulation process variables on the quantitative assay model of transmission Raman spectroscopy for pharmaceutical tablets. Eur J Pharm Biopharm 2023; 191:276-289. [PMID: 37714414 DOI: 10.1016/j.ejpb.2023.09.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 09/11/2023] [Accepted: 09/12/2023] [Indexed: 09/17/2023]
Abstract
Transmission Raman spectroscopy (TRS) is a process analytical technology tool for nondestructive analysis of drug content in tablets. Although wet granulation is the most used tablet manufacturing method, most TRS studies have focused on tablets manufactured via direct compression. The effects of upstream process parameter variations, such as granulation, on the prediction performance of TRS quantitative models are unknown. We evaluated the effects of process parameter variations during granulation on the prediction performance of the TRS quantitative model. Tablets with a drug concentration of 1%w/w were used. We developed PLS calibration models for the drug concentration range of 70-130% label claims. Subsequently, we predicted the drug content of the tablets with different granulation parameters. The results of our study demonstrate that the variation in the predicted recovery due to the variation in granulation parameters was practically acceptable. The calibration model showed a good prediction performance for tablets manufactured at different granulation scales and thicknesses. Therefore, we conclude that TRS quantitative models are robust to variations in upstream processes, such as granulation and downstream variations in tableting parameters. These results suggest that TRS is a versatile non-destructive quantitative analysis method that can be applied in tablet manufacturing.
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Affiliation(s)
- Ryo Ohashi
- Department of Molecular Pharmaceutics, Meiji Pharmaceutical University, 2-522-1 Noshio, Kiyose, Tokyo 204-8588 Japan; Formulation R&D Laboratory, R&D Division, SHIONOGI & CO., LTD., Hyogo 660-0813, Japan.
| | - Tatsuo Koide
- Division of Drugs, National Institute of Health Sciences, Tonomachi, Kawasaki-ku, Kawasaki 210-9501, Japan
| | - Toshiro Fukami
- Department of Molecular Pharmaceutics, Meiji Pharmaceutical University, 2-522-1 Noshio, Kiyose, Tokyo 204-8588 Japan
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Sadergaski LR, Irvine SB, Andrews HB. Partial Least Squares, Experimental Design, and Near-Infrared Spectrophotometry for the Remote Quantification of Nitric Acid Concentration and Temperature. Molecules 2023; 28:molecules28073224. [PMID: 37049987 PMCID: PMC10096128 DOI: 10.3390/molecules28073224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 03/22/2023] [Accepted: 04/02/2023] [Indexed: 04/14/2023] Open
Abstract
Near-infrared spectrophotometry and partial least squares regression (PLSR) were evaluated to create a pleasantly simple yet effective approach for measuring HNO3 concentration with varying temperature levels. A training set, which covered HNO3 concentrations (0.1-8 M) and temperature (10-40 °C), was selected using a D-optimal design to minimize the number of samples required in the calibration set for PLSR analysis. The top D-optimal-selected PLSR models had root mean squared error of prediction values of 1.4% for HNO3 and 4.0% for temperature. The PLSR models built from spectra collected on static samples were validated against flow tests including HNO3 concentration and temperature gradients to test abnormal conditions (e.g., bubbles) and the model performance between sample points in the factor space. Based on cross-validation and prediction modeling statistics, the designed near-infrared absorption approach can provide remote, quantitative analysis of HNO3 concentration and temperature for production-oriented applications in facilities where laser safety challenges would inhibit the implementation of other optical techniques (e.g., Raman spectroscopy) and in which space, time, and/or resources are constrained. The experimental design approach effectively minimized the number of samples in the training set and maintained or improved PLSR model performance, which makes the described chemometric approach more amenable to nuclear field applications.
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Affiliation(s)
- Luke R Sadergaski
- Radioisotope Science and Technology Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Sawyer B Irvine
- Isotope Processing and Manufacturing Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Hunter B Andrews
- Radioisotope Science and Technology Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
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Wu S, Ketcham SA, Corredor CC, Both D, Drennen JK, Anderson CA. Capacitance spectroscopy enables real-time monitoring of early cell death in mammalian cell culture. Biotechnol J 2023; 18:e2200231. [PMID: 36479620 DOI: 10.1002/biot.202200231] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 08/21/2022] [Accepted: 09/06/2022] [Indexed: 12/13/2022]
Abstract
BACKGROUND/AIMS Previous work developed a quantitative model using capacitance spectroscopy in an at-line setup to predict the dying cell percentage measured from a flow cytometer. This work aimed to transfer the at-line model to monitor lab-scale bioreactors in real-time, waiving the need for frequent sampling and enabling precise controls. METHODS AND RESULTS Due to the difference between the at-line and in-line capacitance probes, direct application of the at-line model resulted in poor accuracy and high prediction bias. A new model with a variable range and offering similar spectral shape across all probes was first constructed, improving prediction accuracy. Moreover, the global calibration method included the variance of different probes and scales in the model, reducing prediction bias. External parameter orthogonalization, a preprocessing method, also mitigated the interference from feeding, which further improved model performance. The root-mean-square error of prediction of the final model was 6.56% (8.42% of the prediction range) with an R2 of 92.4%. CONCLUSION The culture evolution trajectory predicted by the in-line model captured the cell death and alarmed cell death onset earlier than the trypan blue exclusion test. Additionally, the incorporation of at-line spectra following orthogonal design into the calibration set was shown to generate calibration models that are more robust than the calibration models constructed using the in-line spectra only. This is advantageous, as at-line spectral collection is easier, faster, and more material-sparing than in-line spectra collection.
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Affiliation(s)
- Suyang Wu
- Duquesne Center for Pharmaceutical Technology, Duquesne University, Pittsburgh, Pennsylvania, USA.,Duquesne University Graduate School for Pharmaceutical Sciences, Pittsburgh, Pennsylvania, USA
| | - Stephanie A Ketcham
- Manufacturing Science and Technology, Bristol-Myers Squibb, Devens, Massachusetts, USA
| | - Claudia C Corredor
- Pharmaceutical Development, Bristol-Myers Squibb, New Brunswick, New Jersey, USA
| | - Douglas Both
- Pharmaceutical Development, Bristol-Myers Squibb, New Brunswick, New Jersey, USA
| | - James K Drennen
- Duquesne Center for Pharmaceutical Technology, Duquesne University, Pittsburgh, Pennsylvania, USA.,Duquesne University Graduate School for Pharmaceutical Sciences, Pittsburgh, Pennsylvania, USA
| | - Carl A Anderson
- Duquesne Center for Pharmaceutical Technology, Duquesne University, Pittsburgh, Pennsylvania, USA.,Duquesne University Graduate School for Pharmaceutical Sciences, Pittsburgh, Pennsylvania, USA
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Sadergaski LR, Myhre KG, Delmau LH. Multivariate chemometric methods and Vis-NIR spectrophotometry for monitoring plutonium-238 anion exchange column effluent in a radiochemical hot cell. TALANTA OPEN 2022. [DOI: 10.1016/j.talo.2022.100120] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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Zhao X, Wang N, Zhu M, Qiu X, Sun S, Liu Y, Zhao T, Yao J, Shan G. Application of Transmission Raman Spectroscopy in Combination with Partial Least-Squares (PLS) for the Fast Quantification of Paracetamol. Molecules 2022; 27:molecules27051707. [PMID: 35268808 PMCID: PMC8911717 DOI: 10.3390/molecules27051707] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 03/02/2022] [Accepted: 03/03/2022] [Indexed: 11/16/2022] Open
Abstract
In recent years, transmission Raman spectroscopy (TRS) has emerged as a potent new tool for rapid, nondestructive quantitation in pharmaceutical manufacturing. In order to expand the applicability of TRS and enhance its use in product quality monitoring during drug production, we aimed, in the present study, to apply partial least-squares (PLS) approaches to build a model consisting of 150 handmade tablets and covering 15 levels through the use of a multifactor orthogonal design of experiment (DOE), which was used to predict concentrations of validation tablets made by hand. The difference between results according to HPLC and TRS were negligible. The model was used to predict the active pharmaceutical ingredient (API) content in four random commercial paracetamol tablets, and corrected with the spectra of the commercial tablets to obtain four corresponding models. The results show that the content relative error in the model’s predictions after correction with commercially available tablets was significantly lower than that before correction. The corrected model was used to make predictions for 20 tablets from the brand Panadol. Compared with the HPLC results, the prediction relative error was basically less than 4.00%, and the relative standard deviation (RSD) of the content was 0.86%.
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Affiliation(s)
- Xuejia Zhao
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1, Tian Tan Xi Li, Beijing 100050, China; (X.Z.); (M.Z.); (X.Q.); (S.S.); (Y.L.); (T.Z.)
| | - Ning Wang
- College of Life Science and Technology, Beijing University of Chemical Technology, North Third Ring Road 15, Beijing 100029, China;
| | - Minghui Zhu
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1, Tian Tan Xi Li, Beijing 100050, China; (X.Z.); (M.Z.); (X.Q.); (S.S.); (Y.L.); (T.Z.)
| | - Xiaodan Qiu
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1, Tian Tan Xi Li, Beijing 100050, China; (X.Z.); (M.Z.); (X.Q.); (S.S.); (Y.L.); (T.Z.)
| | - Shengnan Sun
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1, Tian Tan Xi Li, Beijing 100050, China; (X.Z.); (M.Z.); (X.Q.); (S.S.); (Y.L.); (T.Z.)
| | - Yitong Liu
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1, Tian Tan Xi Li, Beijing 100050, China; (X.Z.); (M.Z.); (X.Q.); (S.S.); (Y.L.); (T.Z.)
| | - Ting Zhao
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1, Tian Tan Xi Li, Beijing 100050, China; (X.Z.); (M.Z.); (X.Q.); (S.S.); (Y.L.); (T.Z.)
| | - Jing Yao
- China National Institutes for Food and Drug Control, No. 2, Tian Tan Xi Li, Beijing 100050, China
- Correspondence: (J.Y.); (G.S.)
| | - Guangzhi Shan
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1, Tian Tan Xi Li, Beijing 100050, China; (X.Z.); (M.Z.); (X.Q.); (S.S.); (Y.L.); (T.Z.)
- Correspondence: (J.Y.); (G.S.)
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Sadergaski LR, Toney GK, Delmau LH, Myhre KG. Chemometrics and Experimental Design for the Quantification of Nitrate Salts in Nitric Acid: Near-Infrared Spectroscopy Absorption Analysis. APPLIED SPECTROSCOPY 2021; 75:1155-1167. [PMID: 33393348 DOI: 10.1177/0003702820987281] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Implementing remote, real-time spectroscopic monitoring of radiochemical processing streams in hot cell environments requires efficiency and simplicity. The success of optical spectroscopy for the quantification of species in chemical systems highly depends on representative training sets and suitable validation sets. Selecting a training set (i.e., calibration standards) to build multivariate regression models is both time- and resource-consuming using standard one-factor-at-a-time approaches. This study describes the use of experimental design to generate spectral training sets and a validation set for the quantification of sodium nitrate (0-1 M) and nitric acid (0.1-10 M) using the near-infrared water band centered at 1440 nm. Partial least squares regression models were built from training sets generated by both D- and I-optimal experimental designs and a one-factor-at-a-time approach. The prediction performance of each model was evaluated by comparing the bias and standard error of prediction for statistical significance. D- and I-optimal designs reduced the number of samples required to build regression models compared with one-factor-at-a-time while also improving performance. Models must be confirmed against a validation sample set when minimizing the number of samples in the training set. The D-optimal design performed the best when considering both performance and efficiency by improving predictive capability and reducing number of samples in the training set by 64% compared with the one-factor-at-a-time approach. The experimental design approach objectively selects calibration and validation spectral data sets based on statistical criterion to optimize performance and minimize resources.
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Affiliation(s)
- Luke R Sadergaski
- Radioisotope Science and Technology Division, 6146Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Gretchen K Toney
- Radioisotope Science and Technology Division, 6146Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Laetitia H Delmau
- Radioisotope Science and Technology Division, 6146Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | - Kristian G Myhre
- Radioisotope Science and Technology Division, 6146Oak Ridge National Laboratory, Oak Ridge, TN, USA
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Zeng J, Ping W, Sanaeifar A, Xu X, Luo W, Sha J, Huang Z, Huang Y, Liu X, Zhan B, Zhang H, Li X. Quantitative visualization of photosynthetic pigments in tea leaves based on Raman spectroscopy and calibration model transfer. PLANT METHODS 2021; 17:4. [PMID: 33407678 PMCID: PMC7788994 DOI: 10.1186/s13007-020-00704-3] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 12/22/2020] [Indexed: 05/19/2023]
Abstract
BACKGROUND Photosynthetic pigments participating in the absorption, transformation and transfer of light energy play a very important role in plant growth. While, the spatial distribution of foliar pigments is an important indicator of environmental stress, such as pests, diseases and heavy metal stress. RESULTS In this paper, in situ quantitative visualization of chlorophyll and carotenoid was realized by combining the Raman spectroscopy with calibration model transfer, and a laboratory Raman spectral model was successfully extended to a portable field spectral measurement. Firstly, a nondestructive and fast model for determination of chlorophyll and carotenoid in tea leaf was established based on confocal micro-Raman spectrometer in the laboratory. Then the spectral model was extended to a real-time foliar map scanning spectra of a field portable Raman spectrometer through calibration model transfer, and the spectral variation between the confocal micro-Raman spectrometer in the laboratory and the portable Raman spectrometer were effectively corrected by the direct standardization (DS) algorithm. The portable map scanning Raman spectra of the tea leaves after the model transfer were got into the established quantitative determination model to predict the concentration of photosynthetic pigments at each pixel of the tea leaves. The predicted photosynthetic pigments concentration of each pixel was imaged to illustrate the distribution map of foliar pigments. Statistical analysis showed that the predicted pigment contents were highly correlated with the real contents. CONCLUSIONS It can be concluded that the Raman spectroscopy was applicable for in situ, non-destructive and rapid quantitative detecting and imaging of photosynthetic pigment concentration in tea leaves, and the spectral detection model established based on the laboratory Raman spectrometer can be applied to a portable field spectrometer for quantitatively imaging of the foliar pigments.
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Affiliation(s)
- Jianjun Zeng
- College of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, 330013, China
| | - Wen Ping
- College of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, 330013, China
| | - Alireza Sanaeifar
- College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
| | - Xiao Xu
- College of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, 330013, China
| | - Wei Luo
- College of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, 330013, China
| | - Junjing Sha
- College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
| | - Zhenxiong Huang
- College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China
| | - Yifeng Huang
- College of Civil Engineering and Architecture, East China Jiaotong University, Nanchang, 330013, China
| | - Xuemei Liu
- College of Civil Engineering and Architecture, East China Jiaotong University, Nanchang, 330013, China
| | - Baishao Zhan
- College of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, 330013, China
| | - Hailiang Zhang
- College of Electrical and Automation Engineering, East China Jiaotong University, Nanchang, 330013, China.
| | - Xiaoli Li
- College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China.
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Calibration transfer between modelled and commercial pharmaceutical tablet for API quantification using backscattering NIR, Raman and transmission Raman spectroscopy (TRS). J Pharm Biomed Anal 2020; 194:113766. [PMID: 33280998 DOI: 10.1016/j.jpba.2020.113766] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Accepted: 11/11/2020] [Indexed: 01/19/2023]
Abstract
Backscattering NIR, Raman (BSR) and transmission Raman spectroscopy (TRS) coupled with chemometrics have shown to be rapid and non-invasive tools for the quantification of active pharmaceutical ingredient (API) content in tablets. However, the developed models are generally specifically related to the measurement conditions and sample characteristics. In this study, a number of calibration transfer methods, including DS, PDS, DWPDS, GLSW and SST, were evaluated for the spectra correction between modelled tablets produced in the laboratory and commercial samples. Results showed that the NIR and BSR spectra of commercial tablet corrected by DWPDS and PDS, respectively, enabled accurate API predictions with the high ratio of prediction error to deviation (RPDP) values of 2.33 and 3.03. The most successfully approach was achieved with DS corrected TRS data and SiPLS modelling (161 variables) and yielded RMSEP of 0.72 %, R2P of 0.946 and RPDP of 4.35. The proposed calibration transfer strategy offers the opportunities to analyse samples produced in different conditions; in the future, its implication will find extensively process control and quality assurance applications and benefit all possible users in the entire pharmaceutical industry.
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