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Wang Z, Li Y, Zhai J, Yang S, Sun B, Liang P. Deep learning-based Raman spectroscopy qualitative analysis algorithm: A convolutional neural network and transformer approach. Talanta 2024; 275:126138. [PMID: 38677164 DOI: 10.1016/j.talanta.2024.126138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Revised: 04/16/2024] [Accepted: 04/19/2024] [Indexed: 04/29/2024]
Abstract
Raman spectroscopy is a general and non-destructive detection technique that can obtain detailed information of the chemical structure of materials. In the past, when using chemometric algorithms to analyze the Raman spectra of mixtures, the challenges of complex spectral overlap and noise often limited the accurate identification of components. The emergence of deep learning has introduced a novel approach to qualitative analysis of mixed Raman spectra. In this paper, we propose a deep learning-based Raman spectroscopy qualitative analysis algorithm (RST) by borrowing the ideas of convolutional neural network and Transformer. By transforming the Raman spectrum into 64 word vectors, the contribution weights of each word vector to the components are obtained. For the 75 spectral data used for validation, the positive identification rate can reach 100.00 %, the recall rate can reach 99.3 %, the average identification score can reach 9.51, and it is applicable to the fields of Raman and surface-enhanced Raman spectroscopy. Furthermore, compared with traditional CNN models, RST has excellent accuracy and robustness in identifying components in complex mixtures. The model's interpretability has been enhanced, aiding in a deeper understanding of spectroscopic learning patterns for future analysis of more complex mixtures.
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Affiliation(s)
- Zilong Wang
- College of Optical and Electronic Technology, China Jiliang University, Hangzhou, 310018, China; Xiamen Palantier Technology Co., Ltd., Xiamen, 361000, China
| | - Yunfeng Li
- College of Information Engineering, China Jiliang University, Hangzhou, 310018, China
| | - Jinglei Zhai
- School of Electrical and Information Engineering, Tianjin University, No. 92, Weijin Road, Nankai District, Tianjin, 300072, China
| | - Siwei Yang
- College of Optical and Electronic Technology, China Jiliang University, Hangzhou, 310018, China
| | - Biao Sun
- School of Electrical and Information Engineering, Tianjin University, No. 92, Weijin Road, Nankai District, Tianjin, 300072, China
| | - Pei Liang
- College of Optical and Electronic Technology, China Jiliang University, Hangzhou, 310018, China; Xiamen Palantier Technology Co., Ltd., Xiamen, 361000, China.
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2
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Liu M, Liu J, Wang Q, Song P, Li H, Sun Z, Shi C, Dong W. Quantitative analysis of low-content impurity crystal forms in canagliflozin tablets by NIR solid-state analysis technique. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 311:124000. [PMID: 38350412 DOI: 10.1016/j.saa.2024.124000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 01/05/2024] [Accepted: 02/04/2024] [Indexed: 02/15/2024]
Abstract
Canagliflozin (CFZ) tablets was a commercially new class of anti-diabetic drug, CFZ had various anhydrate crystal forms and two hydrate crystal forms (Canagliflozin hemihydrate (Hemi-CFZ) and Canagliflozin monohydrate (Mono-CFZ) crystal form). The active pharmaceutical ingredients (APIs) of commercially available CFZ tablets were Hemi-CFZ, was easily convert to CFZ or Mono-CFZ under the influence of temperature, pressure, humidity and other factors in tablets processing, storage, and transportation, thus affected bioavailability and efficacy of tablets. Therefore, quantitative analysis of low-content CFZ and Mono-CFZ in tablets was essential to control tablets' quality. The main objective of this study was to explore the feasibility and in-depth explain its quantitative analysis mechanism of NIR for quantitative analysis of low-content CFZ/Mono-CFZ in CFZ tablets. PLSR models for low-content CFZ/Mono-CFZ were established by NIR solid-state analysis technique in different resolutions with different wavenumber regions combined with various pretreatments methods (such as Multiplicative Scatter Correction (MSC), Standard Normal Variate (SNV), Savitzky-Golay First Derivative (SG1st), Savitzky-Golay Second Derivative (SG2nd) and Wavelet Transform (WT)), and the PLSR models were verified. The feasibility of NIR spectroscopy for quantitative analysis of low-content CFZ and Mono-CFZ in CFZ tablets was discussed and analyzed from multiple perspectives, which included the distribution of effective information on the spectrum, the influence of resolution on PLSR models performance, the variance contribution/cumulative variance contribution of PLSR model principal components (PCs), the relation of PCI loadings, scores of the spectra and CFZ/Mono-CFZ content, and the mechanism of quantitative analysis was in-depth explained simultaneously. Eventually the most suitable PLSR models in 0.0000-10.0000 % w/w % obtained. That can provide theoretical support for quantitative analysis of low-content impurity crystal during the production, storage and transportation of CFZ tablets, thus provide reference methods for quality control of CFZ tablets and a reliable reference method for quantitative analysis of impurity crystal forms and quality control of similar drugs.
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Affiliation(s)
- Mingdi Liu
- College of Chemistry and Chemical Engineering, Qinghai Minzu University, Xining 810007, PR China; State Key Laboratory of Chemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China; Key Laboratory of Resource Chemistry and Eco-environmental Protection in Tibetan Plateau, State Ethnic Affairs Commission, Xining 810007, PR China.
| | - Jichao Liu
- College of Chemistry and Chemical Engineering, Qinghai Minzu University, Xining 810007, PR China; Key Laboratory of Resource Chemistry and Eco-environmental Protection in Tibetan Plateau, State Ethnic Affairs Commission, Xining 810007, PR China
| | - Qiuhong Wang
- College of Chemistry and Chemical Engineering, Qinghai Minzu University, Xining 810007, PR China; Key Laboratory of Resource Chemistry and Eco-environmental Protection in Tibetan Plateau, State Ethnic Affairs Commission, Xining 810007, PR China
| | - Ping Song
- College of Chemistry and Chemical Engineering, Qinghai Minzu University, Xining 810007, PR China; Key Laboratory of Resource Chemistry and Eco-environmental Protection in Tibetan Plateau, State Ethnic Affairs Commission, Xining 810007, PR China
| | - Haichao Li
- College of Chemistry and Chemical Engineering, Qinghai Minzu University, Xining 810007, PR China; Key Laboratory of Resource Chemistry and Eco-environmental Protection in Tibetan Plateau, State Ethnic Affairs Commission, Xining 810007, PR China
| | - Zan Sun
- College of Chemistry and Chemical Engineering, Qinghai Minzu University, Xining 810007, PR China; Key Laboratory of Resource Chemistry and Eco-environmental Protection in Tibetan Plateau, State Ethnic Affairs Commission, Xining 810007, PR China
| | - Chenglong Shi
- College of Chemistry and Chemical Engineering, Qinghai Minzu University, Xining 810007, PR China; Key Laboratory of Resource Chemistry and Eco-environmental Protection in Tibetan Plateau, State Ethnic Affairs Commission, Xining 810007, PR China
| | - Weibing Dong
- College of Chemistry and Chemical Engineering, Qinghai Minzu University, Xining 810007, PR China; Key Laboratory of Resource Chemistry and Eco-environmental Protection in Tibetan Plateau, State Ethnic Affairs Commission, Xining 810007, PR China
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3
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Liu M, Liu J, Wang Q, Song P, Li H, Wu S, Gong J. Quantitative analysis of low content polymorphic impurities in canagliflozin tablets by PXRD, NIR, ATR-FITR and Raman solid-state analysis techniques combined with stoichiometry. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 293:122458. [PMID: 36801728 DOI: 10.1016/j.saa.2023.122458] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 01/31/2023] [Accepted: 02/04/2023] [Indexed: 06/18/2023]
Abstract
Canagliflozin (CFZ) was a commercially new class of anti-diabetic drug, which had various anhydrate crystal forms and two hydrate crystal forms (Canagliflozin hemihydrate (Hemi-CFZ) and Canagliflozin monohydrate (Mono-CFZ) crystal form). Commercially available CFZ tablets' active pharmaceutical ingredient (API) was Hemi-CFZ, which was easy conversion to CFZ or Mono-CFZ under the influence of temperature, pressure, humidity and other factors in tablets processing, storage, and transportation, thus affected bioavailability and efficacy of tablets. Therefore, quantitative analysis low content of CFZ and Mono-CFZ in tablets was essential to control tablets' quality. The main objective of this study was to examine the feasibility of Powder X-ray Diffraction (PXRD), Near Infrared Spectroscopy (NIR), Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR) and Raman for quantitative analysis the low content of CFZ or Mono-CFZ in ternary mixtures. PLSR calibration models for low content of CFZ and Mono-CFZ were established by the solid analysis techniques of PXRD, NIR, ATR-FTIR and Raman combined with various pretreatments (such as Multiplicative Scatter Correction (MSC), Standard Normal Variate (SNV), Savitzky-Golay First Derivative (SG1st), Savitzky-Golay Second Derivative (SG2nd) and Wavelet Transform (WT)), and the correction models were verified. However, compared with PXRD, ATR-FTIR and Raman, NIR due to its water sensitivity was the most suitable for the quantitative analysis low content of CFZ or Mono-CFZ in tablets. Partial Least Squares Regression (PLSR) model for quantitative analysis low content of CFZ in tablets was as follow: Y = 0.0480 + 0.9928 X, R2 = 0.9986, LOD = 0.1596 %, LOQ = 0.4838 %, SG1st + WT pretreated. And that of Mono-CFZ were Y = 0.0050 + 0.9996 X, R2 = 0.9996, LOD = 0.0164 %, LOQ = 0.0498 %, MSC + WT pretreated and Y = 0.0051 + 0.9996 X, R2 = 0.9996, LOD = 0.0167 %, LOQ = 0.0505 %, SNV + WT pretreated, respectively. That can be used for quantitative analysis of impurity crystal content in drug production to ensure drug quality.
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Affiliation(s)
- Mingdi Liu
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China; College of Chemistry and Chemical Engineering, Qinghai Minzu University, Xining 810007, PR China; Key Laboratory of Resource Chemistry and Eco-environmental Protection in Tibetan Plateau, State Ethnic Affairs Commission, Xining 810007, PR China
| | - Jichao Liu
- College of Chemistry and Chemical Engineering, Qinghai Minzu University, Xining 810007, PR China; Key Laboratory of Resource Chemistry and Eco-environmental Protection in Tibetan Plateau, State Ethnic Affairs Commission, Xining 810007, PR China
| | - Qiuhong Wang
- College of Chemistry and Chemical Engineering, Qinghai Minzu University, Xining 810007, PR China; Key Laboratory of Resource Chemistry and Eco-environmental Protection in Tibetan Plateau, State Ethnic Affairs Commission, Xining 810007, PR China
| | - Ping Song
- College of Chemistry and Chemical Engineering, Qinghai Minzu University, Xining 810007, PR China; Key Laboratory of Resource Chemistry and Eco-environmental Protection in Tibetan Plateau, State Ethnic Affairs Commission, Xining 810007, PR China
| | - Haichao Li
- College of Chemistry and Chemical Engineering, Qinghai Minzu University, Xining 810007, PR China; Key Laboratory of Resource Chemistry and Eco-environmental Protection in Tibetan Plateau, State Ethnic Affairs Commission, Xining 810007, PR China
| | - Songgu Wu
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China; College of Chemistry and Chemical Engineering, Qinghai Minzu University, Xining 810007, PR China.
| | - Junbo Gong
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, PR China; College of Chemistry and Chemical Engineering, Qinghai Minzu University, Xining 810007, PR China
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4
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Su X, Wang Y, Mao J, Chen Y, Yin AT, Zhao B, Zhang H, Liu M. A Review of Pharmaceutical Robot based on Hyperspectral Technology. J INTELL ROBOT SYST 2022; 105:75. [PMID: 35909703 PMCID: PMC9306415 DOI: 10.1007/s10846-022-01602-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 02/22/2022] [Indexed: 11/04/2022]
Abstract
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.
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Fauteux-Lefebvre C, Lavoie FB, Hudon S, Gosselin R. Hierarchical Multivariate Curve Resolution Coupled to Raman Imaging for Fast Characterization of Pharmaceutical Tablets. J Pharm Innov 2022. [DOI: 10.1007/s12247-022-09652-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Liu M, Shi P, Wang G, Wang G, Song P, Liu Y, Wu S, Gong J. Quantitative analysis of binary mixtures of entecavir using solid-state analytical techniques with chemometric methods. ARAB J CHEM 2021. [DOI: 10.1016/j.arabjc.2021.103360] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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Gao M, Liu S, Chen J, Gordon KC, Tian F, McGoverin CM. Potential of Raman spectroscopy in facilitating pharmaceutical formulations development - An AI perspective. Int J Pharm 2021; 597:120334. [PMID: 33540015 DOI: 10.1016/j.ijpharm.2021.120334] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 01/26/2021] [Accepted: 01/27/2021] [Indexed: 01/17/2023]
Abstract
Drug development is time-consuming and inherently possesses a high failure rate. Pharmaceutical formulation development is the bridge that links a new chemical entity (NCE) to pre-clinical and clinical trials, and has a high impact on the efficacy and safety of the final drug product. Further, the time required for this process is escalating as formulation techniques are becoming more complicated due to the rising demands for drug products with better efficacy and patient compliance, as well as the inherent difficulties of addressing the unfavorable properties of NCEs such as low water solubility. The advent of artificial intelligence (AI) provides possibilities to accelerate the drug development process. In this review, we first examine applications of AI methods in different types of pharmaceutical formulations and formulation techniques. Moreover, as availability of data is the engine for the advancement of AI, we then suggest a potential way (i.e. applying Raman spectroscopy) for faster high-quality data gathering from formulations. Raman techniques have the capability of analyzing the composition and distribution of components and the physicochemical properties thereof within formulations, which are prominent factors governing drug dissolution profiles and subsequently bioavailability. Thus, useful information can be obtained bridging formulation development to the final product quality.
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Affiliation(s)
- Ming Gao
- Nycrist Pharmtech Limited, 2/2D, A3, Science and Technology Park, 3009 Guanguang Rd, Guangming, Shenzhen, Guangdong 518107, China
| | - Sibo Liu
- Nycrist Pharmtech Limited, 2/2D, A3, Science and Technology Park, 3009 Guanguang Rd, Guangming, Shenzhen, Guangdong 518107, China
| | - Jianan Chen
- Department of Medical Biophysics, University of Toronto, Princess Margaret Cancer Research Tower, MaRS Centre, 101 College Street, Toronto, Ontario M5G 1L7, Canada
| | - Keith C Gordon
- Dodd-Walls Centre, Department of Chemistry, University of Otago, PO Box 56, Dunedin 9054, New Zealand
| | - Fang Tian
- Nycrist Pharmtech Limited, 2/2D, A3, Science and Technology Park, 3009 Guanguang Rd, Guangming, Shenzhen, Guangdong 518107, China
| | - Cushla M McGoverin
- Nycrist Pharmtech Limited, 2/2D, A3, Science and Technology Park, 3009 Guanguang Rd, Guangming, Shenzhen, Guangdong 518107, China.
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8
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Chang Y, Hu C, Yang R, He D, Wang X, Ning B, Sun H, Xiong Y, Tu J, Sun C. A Raman imaging-based technique to assess HPMC substituent contents and their effects on the drug release of commercial extended-release tablets. Carbohydr Polym 2020; 244:116460. [PMID: 32536397 DOI: 10.1016/j.carbpol.2020.116460] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 05/13/2020] [Accepted: 05/13/2020] [Indexed: 10/24/2022]
Abstract
In this study, we tried to assess the substitute contents of HPMC used in commercial extended-release tablets directly by an innovative Raman imaging-based analysis technique and find their effects on the in vitro performance of these pharmaceuticals. Twenty-seven batches of metformin hydrochloride extended-release tablets from various sources were collected in the Chinese mainland market. While Raman imaging was used to qualitatively analyze the composition of the tablets, the MeO and HPO contents of HPMC were quantitatively assessed by a newly proposed calculation method based on the Raman intensity of corresponding characteristic band. Additionally, the dissolution test was performed to evaluate the relationship between HPMC substitution pattern and in vitro behavior. In sum, our findings indicate that the drug release rate can be downregulated by increasing the MeO content of HPMC, while the high HPO content would largely eliminate the variation of drug release profiles among batches.
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Affiliation(s)
- Yan Chang
- State Key Laboratory of Natural Medicines, Center for Research Development and Evaluation of Pharmaceutical Excipients and Generic Drugs, and Department of Pharmaceutics, School of Pharmacy, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing 210009, China; NMPA Key Laboratory for Quality Research and Evaluation of Chemical Drugs, Institute for Chemical Drug Control, National Institutes for Food and Drug Control, 31 Huatuo Road, Beijing 102629, China
| | - Changqin Hu
- NMPA Key Laboratory for Quality Research and Evaluation of Chemical Drugs, Institute for Chemical Drug Control, National Institutes for Food and Drug Control, 31 Huatuo Road, Beijing 102629, China.
| | - Rui Yang
- NMPA Key Laboratory for Quality Research and Evaluation of Pharmaceutical Excipients, Institute for Control of Pharmaceutical Excipient and Packaging Material, National Institutes for Food and Drug Control, 2 Tiantan Xili, Beijing 100050, China
| | - Dongsheng He
- State Key Laboratory of Natural Medicines, Center for Research Development and Evaluation of Pharmaceutical Excipients and Generic Drugs, and Department of Pharmaceutics, School of Pharmacy, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing 210009, China
| | - Xueyi Wang
- State Key Laboratory of Natural Medicines, Center for Research Development and Evaluation of Pharmaceutical Excipients and Generic Drugs, and Department of Pharmaceutics, School of Pharmacy, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing 210009, China
| | - Baoming Ning
- NMPA Key Laboratory for Quality Research and Evaluation of Chemical Drugs, Institute for Chemical Drug Control, National Institutes for Food and Drug Control, 31 Huatuo Road, Beijing 102629, China
| | - Huimin Sun
- NMPA Key Laboratory for Quality Research and Evaluation of Pharmaceutical Excipients, Institute for Control of Pharmaceutical Excipient and Packaging Material, National Institutes for Food and Drug Control, 2 Tiantan Xili, Beijing 100050, China
| | - Yerong Xiong
- State Key Laboratory of Natural Medicines, Center for Research Development and Evaluation of Pharmaceutical Excipients and Generic Drugs, and Department of Pharmaceutics, School of Pharmacy, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing 210009, China
| | - Jiasheng Tu
- State Key Laboratory of Natural Medicines, Center for Research Development and Evaluation of Pharmaceutical Excipients and Generic Drugs, and Department of Pharmaceutics, School of Pharmacy, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing 210009, China.
| | - Chunmeng Sun
- State Key Laboratory of Natural Medicines, Center for Research Development and Evaluation of Pharmaceutical Excipients and Generic Drugs, and Department of Pharmaceutics, School of Pharmacy, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing 210009, China.
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Mészáros LA, Galata DL, Madarász L, Köte Á, Csorba K, Dávid ÁZ, Domokos A, Szabó E, Nagy B, Marosi G, Farkas A, Nagy ZK. Digital UV/VIS imaging: A rapid PAT tool for crushing strength, drug content and particle size distribution determination in tablets. Int J Pharm 2020; 578:119174. [DOI: 10.1016/j.ijpharm.2020.119174] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Revised: 02/21/2020] [Accepted: 02/22/2020] [Indexed: 12/21/2022]
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10
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Kang Y, Shao Z, Wang Q, Hu X, Yu D. Quantitation of polymorphic impurity in entecavir polymorphic mixtures using powder X-ray diffractometry and Raman spectroscopy. J Pharm Biomed Anal 2018; 158:28-37. [DOI: 10.1016/j.jpba.2018.05.026] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2018] [Revised: 05/15/2018] [Accepted: 05/16/2018] [Indexed: 10/16/2022]
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Calvo NL, Maggio RM, Kaufman TS. Characterization of pharmaceutically relevant materials at the solid state employing chemometrics methods. J Pharm Biomed Anal 2018; 147:538-564. [DOI: 10.1016/j.jpba.2017.06.017] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Revised: 06/08/2017] [Accepted: 06/12/2017] [Indexed: 11/28/2022]
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12
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Nagy B, Farkas A, Gyürkés M, Komaromy-Hiller S, Démuth B, Szabó B, Nusser D, Borbás E, Marosi G, Nagy ZK. In-line Raman spectroscopic monitoring and feedback control of a continuous twin-screw pharmaceutical powder blending and tableting process. Int J Pharm 2017; 530:21-29. [PMID: 28723408 DOI: 10.1016/j.ijpharm.2017.07.041] [Citation(s) in RCA: 62] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2017] [Revised: 07/01/2017] [Accepted: 07/12/2017] [Indexed: 10/19/2022]
Abstract
The integration of Process Analytical Technology (PAT) initiative into the continuous production of pharmaceuticals is indispensable for reliable production. The present paper reports the implementation of in-line Raman spectroscopy in a continuous blending and tableting process of a three-component model pharmaceutical system, containing caffeine as model active pharmaceutical ingredient (API), glucose as model excipient and magnesium stearate as lubricant. The real-time analysis of API content, blend homogeneity, and tablet content uniformity was performed using a Partial Least Squares (PLS) quantitative method. The in-line Raman spectroscopic monitoring showed that the continuous blender was capable of producing blends with high homogeneity, and technological malfunctions can be detected by the proposed PAT method. The Raman spectroscopy-based feedback control of the API feeder was also established, creating a 'Process Analytically Controlled Technology' (PACT), which guarantees the required API content in the produced blend. This is, to the best of the authors' knowledge, the first ever application of Raman-spectroscopy in continuous blending and the first Raman-based feedback control in the formulation technology of solid pharmaceuticals.
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Affiliation(s)
- Brigitta Nagy
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Műegyetem rakpart 3, Hungary
| | - Attila Farkas
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Műegyetem rakpart 3, Hungary
| | - Martin Gyürkés
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Műegyetem rakpart 3, Hungary
| | | | - Balázs Démuth
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Műegyetem rakpart 3, Hungary
| | - Bence Szabó
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Műegyetem rakpart 3, Hungary
| | - Dávid Nusser
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Műegyetem rakpart 3, Hungary
| | - Enikő Borbás
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Műegyetem rakpart 3, Hungary
| | - György Marosi
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Műegyetem rakpart 3, Hungary
| | - Zsombor Kristóf Nagy
- Department of Organic Chemistry and Technology, Budapest University of Technology and Economics, H-1111 Budapest, Műegyetem rakpart 3, Hungary.
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