1
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Fink E, Gartshein E, Khinast JG. Extending the Use of Optical Coherence Tomography to Scattering Coatings Containing Pigments. J Pharm Sci 2024; 113:1580-1585. [PMID: 38246362 DOI: 10.1016/j.xphs.2024.01.008] [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: 09/25/2023] [Revised: 01/15/2024] [Accepted: 01/15/2024] [Indexed: 01/23/2024]
Abstract
Coating thickness is a critical quality attribute of many coated tablets. Functional coatings ensure correct drug release kinetics or protection from light, while non-functional coatings are generally applied for cosmetic reasons. Traditionally, coating thickness is assessed indirectly via offline methods, such as weight gain or diameter growth. In the past decade, several methods, including optical coherence tomography (OCT) and Raman spectroscopy, have emerged to perform in-line measurements of various subclasses of coating formulations. However, there are some obstacles. For example, when using OCT, a major challenge is scattering pigments, such as titanium dioxide and iron oxide, which make the interface between the coating and the tablet core difficult to detect. This work explores novel OCT image evaluation techniques using unsupervised machine learning to compute image metrics. Certain image metrics of highly scattering coatings are correlated with the tablet thickness, and hence indirectly with the coating thickness. The method was demonstrated using a titanium dioxide rich coating formulation. The results are expected to be applicable to other scattering coatings and will significantly broaden the applicability of OCT to at-line and in-line coating thickness measurements of a much larger class of coating formulations.
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Affiliation(s)
- Elisabeth Fink
- Research Center Pharmaceutical Engineering GmbH, Inffeldgasse 13, 8010 Graz, Austria.
| | - Elen Gartshein
- Pfizer Inc, 100 Rt 206N, Gladstone Peapack, NJ 07977, USA
| | - Johannes G Khinast
- Research Center Pharmaceutical Engineering GmbH, Inffeldgasse 13, 8010 Graz, Austria; Institute for Process and Particle Engineering, Graz University of Technology, Inffeldgasse 13, 8010 Graz, Austria
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2
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Zou W, Liu W, Hu C. Characterization of enteric-coated erythromycin tablets by Raman mapping and its pharmaceutical evaluation. Front Chem 2023; 11:1270737. [PMID: 37920414 PMCID: PMC10619665 DOI: 10.3389/fchem.2023.1270737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 10/09/2023] [Indexed: 11/04/2023] Open
Abstract
Enteric tablet coating thickness is a critical quality attribute of the coating process that can affect dissolution behavior in vitro as well as release in vivo. Raman mapping offers unique advantages in analyzing the distribution of active pharmaceutical ingredients and excipients in formulations. In this study, Raman mapping was used to characterize the coating of enteric-coated erythromycin tablets coated by two different processes and compare the differences in their coating formulation, thickness, and uniformity. Furthermore, we aimed to select the appropriate pH of the dissolution medium at which the coating slowly cracks to release the drug and determine the dissolution profile. The differences in the coating thickness and uniformity of the two products resulted in differences in dissolution behavior. Although there are differences in the coating processes for the two types of enteric-coated erythromycin tablets, the thickness of the outer coating on the side is a critical quality attribute in both processes. The outer coating of product A is relatively thick, and the thickness of the outer coating on the side affects the dissolution amount. The outer coating of product B is relatively thin, resulting in a short cracking time and large variation and a significant difference in the initial dissolution amounts between tablets. Raman mapping can be used to analyze the differences in coating formulations and for process evaluation.
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Affiliation(s)
- Wenbo Zou
- Key Laboratory of Molecular Pharmacology and Drug Evaluation (Yantai University), School of Pharmacy, Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai, China
- National Institutes for Food and Drug Control, Beijing, China
| | - Wanhui Liu
- Key Laboratory of Molecular Pharmacology and Drug Evaluation (Yantai University), School of Pharmacy, Ministry of Education, Collaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs in Universities of Shandong, Yantai University, Yantai, China
| | - Changqin Hu
- National Institutes for Food and Drug Control, Beijing, China
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3
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Wolfgang M, Kern A, Deng S, Stranzinger S, Liu M, Drexler W, Leitgeb R, Haindl R. Ultra-high-resolution optical coherence tomography for the investigation of thin multilayered pharmaceutical coatings. Int J Pharm 2023; 643:123096. [PMID: 37268027 DOI: 10.1016/j.ijpharm.2023.123096] [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: 02/20/2023] [Revised: 05/25/2023] [Accepted: 05/26/2023] [Indexed: 06/04/2023]
Abstract
Optical Coherence Tomography (OCT) has recently gained attention as a promising technology for in-line monitoring of pharmaceutical film-coating processes for (single-layered) tablet coatings and end-point detection with commercial systems. An increasing interest in the investigation of multiparticulate dosage forms with mostly multi-layered coatings below 20 µm final film thickness demands advancement in OCT technology for pharmaceutical imaging. We present an ultra-high-resolution (UHR-) OCT and investigate its performance based on three different multiparticulate dosage forms with different layer structures (one single-layered, two multi-layered) with layer thicknesses in a range from 5 to 50 µm. The achieved system resolution of 2.4 µm (axial) and 3.4 µm (lateral, both in air) enables the assessment of defects, film thickness variability and morphological features within the coating, previously unattainable using OCT. Despite the high transverse resolution, the provided depth of field was found sufficient to reach the core region of all dosage forms under test. We further demonstrate an automated segmentation and evaluation of UHR-OCT images for coating thicknesses, where human experts struggle using today's standard OCT systems.
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Affiliation(s)
| | - Alice Kern
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Shiyu Deng
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | | | - Mengyang Liu
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Wolfgang Drexler
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Rainer Leitgeb
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria; Christian Doppler Laboratory OPTRAMED, Medical University of Vienna, Vienna, Austria.
| | - Richard Haindl
- Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria; School of Chemistry, Chemical Engineering and Biotechnology, Nanyang Technological University, 62 Nanyang Drive, Singapore, Singapore; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
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4
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Sivanesapillai R, Ehrig A, Nogueira LW, Vukosavljevic B, Grilc B, Ilić IG, Bharadwaj R, Sibanc R. A validation of discrete-element model simulations for predicting tablet coating variability. Int J Pharm 2023:123109. [PMID: 37295569 DOI: 10.1016/j.ijpharm.2023.123109] [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: 01/10/2023] [Revised: 06/03/2023] [Accepted: 06/05/2023] [Indexed: 06/12/2023]
Abstract
Achieving an even coating distribution on tablets during the coating process can be challenging, not to mention the challenges of accurately measuring and quantifying inter-tablet coating variability. Computer simulations using the Discrete Element Method (DEM) provide a viable pathway towards model-predictive design of coating processes. The purpose of this study was to assess their predictivity accounting for both experimental and simulation input uncertainties. To this end, a comprehensive set of coating experiments covering various process scales, process conditions and tablet shapes were conducted. A water-soluble formulation was developed to enable rapid spectroscopic UV/VIS analysis of coating amounts on a large number of tablets. DEM predictions are found to lie within the experimentally inferred confidence intervals in all cases. A mean absolute comparison error of 0.54 % was found between model predictions of coating variability and respective sample point estimates. Among all simulation inputs the parameterization of spray area sizes is considered the most significant source for prediction errors. However, this error was found significantly smaller in magnitude compared to experimental uncertainties at larger process scales underlining the value of DEM in the design of industrial coating processes.
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Affiliation(s)
| | - Anja Ehrig
- Bayer AG, Engineering and Technology, Leverkusen, 51368, Germany
| | | | | | - Blaž Grilc
- University of Ljubljana, Faculty of Pharmacy, Department of Pharmaceutical Technology, Ljubljana, 1000, Slovenia
| | - Ilija German Ilić
- University of Ljubljana, Faculty of Pharmacy, Department of Pharmaceutical Technology, Ljubljana, 1000, Slovenia
| | | | - Rok Sibanc
- Bayer AG, Chemical and Pharmaceutical Development, Wuppertal, 42117, Germany.
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5
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Yang TL, Szewc J, Zhong L, Leonova A, Giebułtowicz J, Habashy R, Isreb A, Alhnan MA. The Use of Near-infrared as Process Analytical Technology (PAT) during 3D Printing Tablets at the Point-of-Care. Int J Pharm 2023:123073. [PMID: 37230372 DOI: 10.1016/j.ijpharm.2023.123073] [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: 01/30/2023] [Revised: 05/20/2023] [Accepted: 05/22/2023] [Indexed: 05/27/2023]
Abstract
Fused deposition modelling (FDM) is one of the most researched 3D printing technologies that holds great potential for low-cost manufacturing of personalised medicine. To achieve real-time release, timely quality control is a major challenge for applying 3D printing technologies as a point-of-care (PoC) manufacturing approach. This work proposes the use of a low-cost and compact near-infrared (NIR) spectroscopy modality as a process analytical technology (PAT) to monitor a critical quality attribute (drug content) during and after FDM 3D printing process. 3D printed caffeine tablets were used to manifest the feasibility of the NIR model as a quantitative analytical procedure and dose verification method. Caffeine tablets (0-40% w/w) were fabricated using polyvinyl alcohol and FDM 3D printing. The predictive performance of the NIR model was demonstrated in linearity (correlation coefficient, R2) and accuracy (root mean square error of prediction, RMSEP). The actual drug content values were determined using the reference high-performance liquid chromatography (HPLC) method. The model of full-completion caffeine tablets demonstrated linearity (R2 = 0.985) and accuracy (RMSEP =1.4%), indicated to be an alternative dose quantitation method for 3D printed products. The ability of the models to assess caffeine contents during the 3D printing process could not be accurately achieved using the model built with complete tablets. Instead, by building a predictive model for each completion stage of 20%, 40%, 60% and 80%, the model of different completion caffeine tablets displayed linearity (R2 of 0.991, 0.99, 0.987, and 0.983) and accuracy (RMSEP of 2.22%, 1.65%, 1.41%, 0.83%), respectively. Overall, this study demonstrated the feasibility of a low NIR model as a non-destructive, low-cost, compact, and rapid analysis dose verification method enabling the real-time release to facilitate 3D printing medicine production in the clinic.
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Affiliation(s)
- Tzuyi L Yang
- Centre for Pharmaceutical Medicine, Institute of Pharmaceutical Science, King's College London, London, SE1 9NH, UK
| | - Jakub Szewc
- Faculty of Pharmacy with the Laboratory Medicine Division, Medical University of Warsaw, Warsaw, Poland
| | - Lingu Zhong
- Centre for Pharmaceutical Medicine, Institute of Pharmaceutical Science, King's College London, London, SE1 9NH, UK
| | - Anna Leonova
- Centre for Pharmaceutical Medicine, Institute of Pharmaceutical Science, King's College London, London, SE1 9NH, UK
| | - Joanna Giebułtowicz
- Faculty of Pharmacy with the Laboratory Medicine Division, Medical University of Warsaw, Warsaw, Poland
| | | | - Abdullah Isreb
- School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool L3 3AF, UK
| | - Mohamed A Alhnan
- Centre for Pharmaceutical Medicine, Institute of Pharmaceutical Science, King's College London, London, SE1 9NH, UK.
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6
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Xi W, Yilmaz H, Gao Z, Rodriguez JD, Willett DR. A top-down spectroscopic approach for correlating coating thickness distributions with the dissolution profiles of enterically coated pellets. J Pharm Biomed Anal 2023; 224:115176. [PMID: 36423497 DOI: 10.1016/j.jpba.2022.115176] [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: 09/02/2022] [Revised: 11/15/2022] [Accepted: 11/18/2022] [Indexed: 11/22/2022]
Abstract
Pharmaceutical dosage forms such as tablets and capsules are often coated with a functional polymer to modify the drug release. To obtain the drug release profiles, ensure quality control and predict in-vivo performance, dissolution studies are performed. However, dissolution tests are time-consuming, sample destructive and do not readily allow for at-line or in-line characterization. Rapid assessment of functional coatings is essential for products where a single capsule is comprised of hundreds of functionally-coated pellets and the collective drug release kinetics of the entire capsule depends on contributions from each pellet. Here, single Raman measurements were used to evaluate the coating thickness distributions of a dosage form comprised of small, functionally-coated pellets in capsules. First, the composition and physicochemical properties of pellets were characterized by multivariate analysis assisted Raman mapping of pellet cross-sections. Second, a method of collecting single Raman spectrum with spectral contributions from the coating and API layers was developed and optimized to estimate the thickness of coatings. The coating thicknesses obtained from single Raman measurements of pellets in each capsule revealed thickness distributions that correlated with the dissolution profiles (capsules with one distribution had single stage release and capsules with two distributions had a two-stage release). Finally, an unsupervised multivariate analysis method was demonstrated as a rapid and efficient way to correlate dissolution profiles of enterically coated pellets. In summary, this study presents a non-destructive and rapid characterization method for assessing coating thickness and has the potential to be applied in process analytical technologies to ensure coating uniformity and predict product dissolution rate performance.
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Affiliation(s)
- Wenjing Xi
- Food and Drug Administration (FDA)/Center for Drug Evaluation and Research (CDER)/Office of Pharmaceutical Quality (OPQ)/Office of Testing and Research (OTR)/Division of Complex Drug Analysis (DCDA), 645 S. Newstead Ave., St. Louis, MO 63110, USA
| | - Huzeyfe Yilmaz
- Food and Drug Administration (FDA)/Center for Drug Evaluation and Research (CDER)/Office of Pharmaceutical Quality (OPQ)/Office of Testing and Research (OTR)/Division of Complex Drug Analysis (DCDA), 645 S. Newstead Ave., St. Louis, MO 63110, USA
| | - Zongming Gao
- Food and Drug Administration (FDA)/Center for Drug Evaluation and Research (CDER)/Office of Pharmaceutical Quality (OPQ)/Office of Testing and Research (OTR)/Division of Complex Drug Analysis (DCDA), 645 S. Newstead Ave., St. Louis, MO 63110, USA
| | - Jason D Rodriguez
- Food and Drug Administration (FDA)/Center for Drug Evaluation and Research (CDER)/Office of Pharmaceutical Quality (OPQ)/Office of Testing and Research (OTR)/Division of Complex Drug Analysis (DCDA), 645 S. Newstead Ave., St. Louis, MO 63110, USA
| | - Daniel R Willett
- Food and Drug Administration (FDA)/Center for Drug Evaluation and Research (CDER)/Office of Pharmaceutical Quality (OPQ)/Office of Testing and Research (OTR)/Division of Complex Drug Analysis (DCDA), 645 S. Newstead Ave., St. Louis, MO 63110, USA.
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7
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Liu Z, Ma H, Zhou L, Liu Y, Huang Z, Liao X, Zhao Y. DEM-DDM Investigation of the Tablet Coating Process Using Different Particle Shape Models. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.2c04030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Zihan Liu
- Institute of Process Equipment, Zhejiang University, Hangzhou310027, China
| | - Huaqing Ma
- Institute of Process Equipment, Zhejiang University, Hangzhou310027, China
| | - Lianyong Zhou
- Institute of Process Equipment, Zhejiang University, Hangzhou310027, China
| | - Yanlei Liu
- Hangzhou Special Equipment Inspection and Research Institute, Hangzhou310051, China
| | - Ze Huang
- Hangzhou Special Equipment Inspection and Research Institute, Hangzhou310051, China
| | - Xiaoling Liao
- Hangzhou Special Equipment Inspection and Research Institute, Hangzhou310051, China
| | - Yongzhi Zhao
- Institute of Process Equipment, Zhejiang University, Hangzhou310027, China
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8
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Studying the dissolution of immediate release film coating using terahertz pulsed imaging. Int J Pharm 2022; 630:122456. [PMID: 36503850 DOI: 10.1016/j.ijpharm.2022.122456] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 11/24/2022] [Accepted: 11/25/2022] [Indexed: 11/27/2022]
Abstract
Coated tablets introduce complexity to the dissolution process, even with readily soluble immediate release coating layers. Therefore, a more detailed understanding of the physical steps involved in the dissolution process can improve the efficiency of formulation and process design. The current study uses terahertz pulsed imaging to visualise the hydration process of microcrystalline cellulose (MCC) tablet cores that were film coated with an immediate release coating formulation upon exposure to the dissolution medium. Film coated tablets that were prepared from three levels of core porosity (10%, 20% and 30%) and with coating thickness in the range of 30μm to 250μm were investigated. It was possible to resolve and quantify the distinct stages of wetting of the coating layer, swelling of the MCC particles at the core surface, and dissolution of the coating layer followed by the ingress of dissolution media into the tablet core. The liquid transport process through the coating layer was highly consistent and scalable. The penetration rate through the coating layer and the tablet core both strongly depended on coating thickness and core porosity.
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9
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The Use of Novel, Rapid Analytical Tools in the Assessment of the Stability of Tablets—A Pilot Analysis of Expired and Unexpired Tablets Containing Nifuroxazide. Processes (Basel) 2022. [DOI: 10.3390/pr10101934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
In the analysis of finished pharmaceutical products, numerous innovative analytical techniques are often used, i.e., Raman spectroscopy, scanning electron microscopy, computer microtomography, directional hemispherical reflectance, and hyperspectral analyses. These techniques allow for the identification of changes in solid phases. Many advantages over other techniques can be attributed to these techniques, e.g., they are rapid, non-destructive, and comprehensive. They allow for the identification of changes occurring in solid phases. However, the above-mentioned methods are still not standard procedures in pharmaceutical research. The present study aimed to assess the possible usefulness of total directional hemispherical reflectance (THR), hyperspectral imaging, and computer microtomography to evaluate the stability of tablets containing nifuroxazide during storage. In the study, expired and unexpired coating tablets containing nifuroxazide (n = 10 each) were analyzed. In addition, four unexpired tablets were stored at 40°C over 3 months (stressed tablets). Reflectance was determined with seven wavelength bands from 335 nm to 2500 nm using an SOC-410 Directional Hemispherical Reflectometer (Surface Optics Corporation, San Diego, CA, USA). A Specim IQ hyperspectral camera (Spectral Imaging Ltd., Oulu, Finland) was used with a wavelength range of 400–1030 nm. Tablets were also scanned using X-ray microtomography (Phoenix vǀtomeǀx, GE Sensing & Inspection Technologies GmbH, Wunstorf, Germany). The results indicated that total reflectance was lower in expired tablets than in unexpired tablets in all spectral bands, except for 700–1100 nm and 1700–2500 nm. In turn, the stressed tablets showed higher THR values than expired tablets in all spectral bands, except for 1000–1700 nm. In addition, hyperspectral analysis of the homogeneity of the tablets, as well as X-ray microtomographic analysis of tablet density and coating thickness, indicated that these parameters differed significantly between the analyzed tablets.
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10
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Zhong Z, Liu X, Luo X, Zhu Y, Wang S, Huang Y. Evaluation of coating uniformity for the digestion-aid tablets by portable near-infrared spectroscopy. Int J Pharm 2022; 622:121833. [PMID: 35618177 DOI: 10.1016/j.ijpharm.2022.121833] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 04/29/2022] [Accepted: 05/13/2022] [Indexed: 10/18/2022]
Abstract
Process analysis can effectively stabilize pharmaceutical quality and optimize the control of production process. For the sustained-release digestion-aid tablets, the coating film thickness is an important indicator to measure the quality of products. Traditional method mainly spot-checks tablets and measures with visual microscopy, which is time-consuming and laborious. This study attempted to use a portable near-infrared spectroscopy for rapid detection of a Chinese medicine tablets from production line. First, PLS regression models were established for coating film at twelve different locations of the tablet section, and the results showed that the correlation coefficients of training and validation sets were all over 0.80. Subsequently, the twelve locations were divided into six groups to further establish regressions. After chemometrics optimization, the optimal of six group models were generally better than single location models, with Rc2 and Rv2 all above 0.85, and RMSEV values all below 2.0. The mean relative error of prediction of the optimal model was 9.49%. The pharmaceutical process detection based on the portable NIR spectroscopy met the demand of managing digestion-aid tablet coating data conveniently. The proposed approach can successfully realize on-site and online pharmaceutical monitoring and has a promising practical value.
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Affiliation(s)
- Zhijian Zhong
- Technology and Innovation Center of Jiangxi Traditional Chinese Medicine Manufacturing and Process Quality Control, Nanchang, Jiangxi 330004, PR China; Research Center of CR Jiangzhong Pharmaceutical Group Co. Ltd, Nanchang, Jiangxi 330096, PR China
| | - Xuhai Liu
- Technology and Innovation Center of Jiangxi Traditional Chinese Medicine Manufacturing and Process Quality Control, Nanchang, Jiangxi 330004, PR China; Research Center of CR Jiangzhong Pharmaceutical Group Co. Ltd, Nanchang, Jiangxi 330096, PR China
| | - Xiaorong Luo
- Technology and Innovation Center of Jiangxi Traditional Chinese Medicine Manufacturing and Process Quality Control, Nanchang, Jiangxi 330004, PR China
| | - Yewei Zhu
- Beijing Great Tech Technology Co. Ltd, Beijing 100142, PR China
| | - Shuai Wang
- Beijing Great Tech Technology Co. Ltd, Beijing 100142, PR China
| | - Yue Huang
- Technology and Innovation Center of Jiangxi Traditional Chinese Medicine Manufacturing and Process Quality Control, Nanchang, Jiangxi 330004, PR China; College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, PR China.
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11
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Wolfgang M, Stranzinger S, Khinast JG. Ascertain a minimum coating thickness for acid protection of enteric coatings by means of optical coherence tomography. Int J Pharm 2022; 618:121680. [PMID: 35314279 DOI: 10.1016/j.ijpharm.2022.121680] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 03/14/2022] [Accepted: 03/15/2022] [Indexed: 11/18/2022]
Abstract
Enteric coatings are designed to protect active pharmaceutical ingredients (APIs) against untimely release in the stomach. Acid protection of such coatings depends on the coating layer thickness and integrity, which must be determined in an accurate and reliable way to ensure the final product's desired performance. Our work addresses the use of optical coherence tomography (OCT) for characterizing the coating thickness and variability of an enteric-coated drug product and linking them to resistance against gastric fluid. In this study, three batches of enteric-coated tablets drawn during the manufacturing process were investigated. An industrial OCT system was used to establish the coating thickness variability of single tablets (intra-tablet), all tablets in a batch (inter-tablet) and between the batches (inter-batch). Based on the large amount of OCT data, we calculated a critical coating thickness for the investigated film coating, which was found to be 27.4 µm. The corresponding distribution has a mean coating thickness of 44.3 µm ± 7.8 µm. The final coated product has a final mean coating thickness of 63.4 µm ± 8.7 µm, guaranteeing that all tablets meet the quality criterion (i.e., acid protection). Based on the measured thickness distributions, already known distribution functions were considered and an additional, new function was proposed for characterizing the coating thickness distributions in the early stages of industrial coating processes. The proposed approach can be transferred to in-line monitoring of the tablet coating processes, which could drastically improve the production efficiency by ultimately allowing real-time release testing (RTRT).
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Affiliation(s)
- Matthias Wolfgang
- Research Center Pharmaceutical Engineering (RCPE) GmbH, Inffeldgasse 13, 8010 Graz, Austria
| | - Sandra Stranzinger
- Research Center Pharmaceutical Engineering (RCPE) GmbH, Inffeldgasse 13, 8010 Graz, Austria
| | - Johannes G Khinast
- Research Center Pharmaceutical Engineering (RCPE) GmbH, Inffeldgasse 13, 8010 Graz, Austria; Institute for Process and Particle Engineering, Graz University of Technology, Inffeldgasse 13, 8010 Graz, Austria.
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12
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Rodrigues CP, Duchesne C, Poulin É, Lapointe-Garant PP. In-line cosmetic end-point detection of batch coating processes for colored tablets using multivariate image analysis. Int J Pharm 2021; 606:120953. [PMID: 34329698 DOI: 10.1016/j.ijpharm.2021.120953] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 07/23/2021] [Accepted: 07/25/2021] [Indexed: 11/16/2022]
Abstract
In this study, an in-line Process Analytical Technology (PAT) for cosmetic (non-functional) coating unit operations is developed using images of the tablet bed acquired in real-time by an inexpensive industrial camera and lighting system. The cosmetic end-point of multiple batches, run under different operating conditions, is automatically computed from these images using a Multivariate Image Analysis (MIA) methodology in conjunction with a stability determination strategy. The end-points detected by the algorithm differed, on average, by 3% in terms of total batch time from those identified visually by a trained operator. Since traditional practice typically relies on a coating overage to ensure full batch aspect homogeneity in the face of disturbances, the current in-line method can be used to reduce coating material and processing time (over 40% for the operating policy adopted in this work). Additionally, monitoring of the color features calculated by the algorithm allowed the identification of abnormal process conditions affecting visible coating uniformity. This work also addresses practical challenges related to image acquisition in the harsh environment of a pan coater, bringing this tool closer to a state of maturity for implementation in production units and opening the path for their optimization, monitoring, and automatic control.
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Affiliation(s)
- Cecilia Pereira Rodrigues
- Laboratoire d'observation et d'optimisation des procédés (LOOP), Université Laval, Pavillon Adrien-Pouliot Québec (Québec), G1V 0A6, Canada
| | - Carl Duchesne
- Laboratoire d'observation et d'optimisation des procédés (LOOP), Université Laval, Pavillon Adrien-Pouliot Québec (Québec), G1V 0A6, Canada.
| | - Éric Poulin
- Laboratoire d'observation et d'optimisation des procédés (LOOP), Université Laval, Pavillon Adrien-Pouliot Québec (Québec), G1V 0A6, Canada
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13
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Sacher S, Peter A, Khinast JG. Feasibility of In-line monitoring of critical coating quality attributes via OCT: Thickness, variability, film homogeneity and roughness. INTERNATIONAL JOURNAL OF PHARMACEUTICS-X 2021; 3:100067. [PMID: 33385160 PMCID: PMC7772539 DOI: 10.1016/j.ijpx.2020.100067] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 12/10/2020] [Accepted: 12/11/2020] [Indexed: 11/16/2022]
Abstract
The feasibility of Optical Coherence Tomography (OCT) for in-line monitoring of pharmaceutical film coating processes has recently been demonstrated. OCT enables real-time acquisition of high-resolution cross-sectional images of coating layers and computation of coating thickness. In addition, coating quality attributes can be computed based on in-line data. This study assesses the in-line applicability of OCT to various coating functionalities and formulations. Several types of commercial film-coated tablets containing the most common ingredients were investigated. To that end, the tablets were placed into a miniaturized perforated drum. An in-line OCT system was used to monitor the tablet bed. This set-up resembles the final stage of an industrial pan coating process. All investigated coatings were measured, and the coating thickness, homogeneity and roughness were computed. The rotation rate was varied in a range comparable to large-scale coating operations, and no influence on the outcome was observed. The results indicate that OCT can be used to determine end-point and establish in-process control for a wide range of coating formulations. The real-time computation of coating homogeneity and roughness can support process optimization and formulation development.
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Affiliation(s)
- Stephan Sacher
- Research Center Pharmaceutical Engineering GmbH, Inffeldgasse 13/2, 8010Graz, Austria
| | - Anna Peter
- Research Center Pharmaceutical Engineering GmbH, Inffeldgasse 13/2, 8010Graz, Austria
| | - Johannes G Khinast
- Research Center Pharmaceutical Engineering GmbH, Inffeldgasse 13/2, 8010Graz, Austria.,Institute for Process and Particle Engineering, Graz University of Technology, Inffeldgasse 13/3, 8010 Graz, Austria
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Bwambok DK, Siraj N, Macchi S, Larm NE, Baker GA, Pérez RL, Ayala CE, Walgama C, Pollard D, Rodriguez JD, Banerjee S, Elzey B, Warner IM, Fakayode SO. QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs. SENSORS (BASEL, SWITZERLAND) 2020; 20:E6982. [PMID: 33297345 PMCID: PMC7730680 DOI: 10.3390/s20236982] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 12/01/2020] [Accepted: 12/03/2020] [Indexed: 12/23/2022]
Abstract
Quality checks, assessments, and the assurance of food products, raw materials, and food ingredients is critically important to ensure the safeguard of foods of high quality for safety and public health. Nevertheless, quality checks, assessments, and the assurance of food products along distribution and supply chains is impacted by various challenges. For instance, the development of portable, sensitive, low-cost, and robust instrumentation that is capable of real-time, accurate, and sensitive analysis, quality checks, assessments, and the assurance of food products in the field and/or in the production line in a food manufacturing industry is a major technological and analytical challenge. Other significant challenges include analytical method development, method validation strategies, and the non-availability of reference materials and/or standards for emerging food contaminants. The simplicity, portability, non-invasive, non-destructive properties, and low-cost of NIR spectrometers, make them appealing and desirable instruments of choice for rapid quality checks, assessments and assurances of food products, raw materials, and ingredients. This review article surveys literature and examines current challenges and breakthroughs in quality checks and the assessment of a variety of food products, raw materials, and ingredients. Specifically, recent technological innovations and notable advances in quartz crystal microbalances (QCM), electroanalytical techniques, and near infrared (NIR) spectroscopic instrument development in the quality assessment of selected food products, and the analysis of food raw materials and ingredients for foodborne pathogen detection between January 2019 and July 2020 are highlighted. In addition, chemometric approaches and multivariate analyses of spectral data for NIR instrumental calibration and sample analyses for quality assessments and assurances of selected food products and electrochemical methods for foodborne pathogen detection are discussed. Moreover, this review provides insight into the future trajectory of innovative technological developments in QCM, electroanalytical techniques, NIR spectroscopy, and multivariate analyses relating to general applications for the quality assessment of food products.
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Affiliation(s)
- David K. Bwambok
- Chemistry and Biochemistry, California State University San Marcos, 333 S. Twin Oaks Valley Rd, San Marcos, CA 92096, USA;
| | - Noureen Siraj
- Department of Chemistry, University of Arkansas at Little Rock, 2801 S. University Ave, Little Rock, AR 72204, USA; (N.S.); (S.M.)
| | - Samantha Macchi
- Department of Chemistry, University of Arkansas at Little Rock, 2801 S. University Ave, Little Rock, AR 72204, USA; (N.S.); (S.M.)
| | - Nathaniel E. Larm
- Department of Chemistry, University of Missouri, 601 S. College Avenue, Columbia, MO 65211, USA; (N.E.L.); (G.A.B.)
| | - Gary A. Baker
- Department of Chemistry, University of Missouri, 601 S. College Avenue, Columbia, MO 65211, USA; (N.E.L.); (G.A.B.)
| | - Rocío L. Pérez
- Department of Chemistry, Louisiana State University, 232 Choppin Hall, Baton Rouge, LA 70803, USA; (R.L.P.); (C.E.A.); (I.M.W.)
| | - Caitlan E. Ayala
- Department of Chemistry, Louisiana State University, 232 Choppin Hall, Baton Rouge, LA 70803, USA; (R.L.P.); (C.E.A.); (I.M.W.)
| | - Charuksha Walgama
- Department of Physical Sciences, University of Arkansas-Fort Smith, 5210 Grand Ave, Fort Smith, AR 72913, USA; (C.W.); (S.B.)
| | - David Pollard
- Department of Chemistry, Winston-Salem State University, 601 S. Martin Luther King Jr Dr, Winston-Salem, NC 27013, USA;
| | - Jason D. Rodriguez
- Division of Complex Drug Analysis, Center for Drug Evaluation and Research, US Food and Drug Administration, 645 S. Newstead Ave., St. Louis, MO 63110, USA;
| | - Souvik Banerjee
- Department of Physical Sciences, University of Arkansas-Fort Smith, 5210 Grand Ave, Fort Smith, AR 72913, USA; (C.W.); (S.B.)
| | - Brianda Elzey
- Science, Engineering, and Technology Department, Howard Community College, 10901 Little Patuxent Pkwy, Columbia, MD 21044, USA;
| | - Isiah M. Warner
- Department of Chemistry, Louisiana State University, 232 Choppin Hall, Baton Rouge, LA 70803, USA; (R.L.P.); (C.E.A.); (I.M.W.)
| | - Sayo O. Fakayode
- Department of Physical Sciences, University of Arkansas-Fort Smith, 5210 Grand Ave, Fort Smith, AR 72913, USA; (C.W.); (S.B.)
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Wolfgang M, Weißensteiner M, Clarke P, Hsiao WK, Khinast JG. Deep convolutional neural networks: Outperforming established algorithms in the evaluation of industrial optical coherence tomography (OCT) images of pharmaceutical coatings. Int J Pharm X 2020; 2:100058. [PMID: 33294841 PMCID: PMC7689324 DOI: 10.1016/j.ijpx.2020.100058] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
This paper presents a novel evaluation approach for optical coherence tomography (OCT) image analysis of pharmaceutical solid dosage forms based on deep convolutional neural networks (CNNs). As a proof of concept, CNNs were applied to image data from both, in- and at-line OCT implementations, monitoring film-coated tablets as well as single- and multi-layered pellets. CNN results were compared against results from established algorithms based on ellipse-fitting, as well as to human-annotated ground truth data. Performance benchmarks used include, efficiency (computation speed), sensitivity (number of detections from a defined test set) and accuracy (deviation from the reference method). The results were validated by comparing the output of several algorithms to data manually annotated by human experts and microscopy images of cross-sectional cuts of the same dosage forms as a reference method. In order to guarantee comparability for all results, the algorithms were executed on the same hardware. Since modern OCT systems must operate under real-time conditions in order to be implemented in-line into manufacturing lines, the necessary steps are discussed on how to achieve this goal without sacrificing the algorithmic performance and how to tailor a deep CNN to cope with the high amount of image noise and alterations in object appearance. The developed deep learning approach outperforms static algorithms currently available in pharma applications with respect to performance benchmarks, and represents the next level in real time evaluation of challenging industrial OCT image data.
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Affiliation(s)
| | | | - Phillip Clarke
- Research Center Pharmaceutical Engineering GmbH, Graz, Austria
| | - Wen-Kai Hsiao
- Research Center Pharmaceutical Engineering GmbH, Graz, Austria
| | - Johannes G. Khinast
- Research Center Pharmaceutical Engineering GmbH, Graz, Austria
- Institute for Process and Particle Engineering, Graz University of Technology, Graz, Austria
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16
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Feng H, Mohan S. Application of Process Analytical Technology for Pharmaceutical Coating: Challenges, Pitfalls, and Trends. AAPS PharmSciTech 2020; 21:179. [PMID: 32596747 DOI: 10.1208/s12249-020-01727-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 06/08/2020] [Indexed: 12/31/2022] Open
Abstract
Coating process is a critical unit operation for manufacturing solid oral dosage forms. For a long time, the coating weight gain has been discerned as the most important, if not only, characteristic describing the coating quality. As the introduction of quality by design (QbD) and advancement of process analytical technology (PAT), nowadays more techniques are available to analyze other quality attributes which have been overlooked but have substantial impacts on the performance of coated products. The techniques that permit rapid and non-destructive measurements are of particular importance to improve process operation and product quality. This article reviews the analytical techniques that have been and potentially could be used as PAT tools for characterizing the quality of pharmaceutical coating product. By identifying the challenges and pitfalls encountered during PAT application, the review aims at fostering the adoption of PAT for paving the way to enhanced quality and efficiency of the coating processes.
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Affiliation(s)
- Hanzhou Feng
- Process analytical technology, Merck & Co., Inc., Rahway, New Jersey, USA.
| | - Shikhar Mohan
- Graduate School of Pharmaceutical Sciences, Duquesne University, 600 Forbes Avenue, Pittsburgh, Pennsylvania, USA
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17
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At-line validation of optical coherence tomography as in-line/at-line coating thickness measurement method. Int J Pharm 2019; 572:118766. [DOI: 10.1016/j.ijpharm.2019.118766] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 10/01/2019] [Accepted: 10/03/2019] [Indexed: 11/19/2022]
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