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Movilla-Meza NA, Sierra-Vega NO, Alvarado-Hernández BB, Méndez R, Romañach RJ. The Use of a Closed Feed Frame for the Development of Near-Infrared Spectroscopic Calibration Model to Determine Drug Concentration. Pharm Res 2023; 40:2903-2916. [PMID: 37700106 DOI: 10.1007/s11095-023-03601-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 08/31/2023] [Indexed: 09/14/2023]
Abstract
PURPOSE This study evaluates the use of the closed feed frame as a material sparing approach to develop near-infrared (NIR) spectroscopic calibration models for monitoring blend uniformity. The effect of shear induced by recirculation on NIR spectra was also studied. METHODS Calibration models were developed using NIR spectra obtained in the closed feed frame for two cases. For case 2, blends that flowed through the open feed frame were predicted with the model. The shear effect of the feed frame on the blends was assessed through the characterization of powder properties before and after recirculation. RESULTS The physical characterization of the blends confirmed that the powder properties were not altered after recirculation within the closed feed frame. Both calibration models provided highly accurate predictions of the test sets with low bias (0.03% w/w and -0.06% w/w) and relative standard error of prediction (1.9% and 3.7%), respectively. The predictive performance of the calibration models was not affected by the shear effect. CONCLUSION Recirculation within the closed feed frame did not change the physical properties of the blends studied. The prediction of blends flowing through the open feed frame was possible with a calibration model developed in the closed feed frame. The closed feed frame could reduce the materials needed to develop calibration models by more than 90%.
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Affiliation(s)
| | - Nobel O Sierra-Vega
- Department of Chemical Engineering, University of Puerto Rico at Mayagüez, Mayagüez, PR, USA
| | | | - Rafael Méndez
- Department of Chemical Engineering, University of Puerto Rico at Mayagüez, Mayagüez, PR, USA
| | - Rodolfo J Romañach
- Department of Chemistry, University of Puerto Rico at Mayagüez, Mayagüez, PR, USA.
- Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemistry, University of Puerto Rico at Mayagüez, PO Box 9000, Mayagüez, PR, 00681, USA.
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2
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Kappatou CD, Odgers J, García-Muñoz S, Misener R. An Optimization Approach Coupling Preprocessing with Model Regression for Enhanced Chemometrics. Ind Eng Chem Res 2023; 62:6196-6213. [PMID: 37097815 PMCID: PMC10119938 DOI: 10.1021/acs.iecr.2c04583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 03/02/2023] [Accepted: 03/27/2023] [Indexed: 04/09/2023]
Abstract
Chemometric methods are broadly used in the chemical and biochemical sectors. Typically, derivation of a regression model follows data preprocessing in a sequential manner. Yet, preprocessing can significantly influence the regression model and eventually its predictive ability. In this work, we investigate the coupling of preprocessing and model parameter estimation by incorporating them simultaneously in an optimization step. Common model selection techniques rely almost exclusively on the performance of some accuracy metric, yet having a quantitative metric for model robustness can prolong model up-time. Our approach is applied to optimize for model accuracy and robustness. This requires the introduction of a novel mathematical definition for robustness. We test our method in a simulated set up and with industrial case studies from multivariate calibration. The results highlight the importance of both accuracy and robustness properties and illustrate the potential of the proposed optimization approach toward automating the generation of efficient chemometric models.
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Affiliation(s)
- Chrysoula D. Kappatou
- Computational Optimisation Group, Department of Computing, Imperial College London, London SW7 2AZ, United Kingdom
| | - James Odgers
- Computational Optimisation Group, Department of Computing, Imperial College London, London SW7 2AZ, United Kingdom
| | - Salvador García-Muñoz
- Synthetic Molecule Design and Development, Lilly Research Laboratories, Eli Lilly & Company, Indianapolis, Indiana 46285, United States
| | - Ruth Misener
- Computational Optimisation Group, Department of Computing, Imperial College London, London SW7 2AZ, United Kingdom
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3
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Velez NL, Drennen JK, Anderson CA. Challenges, opportunities and recent advances in near infrared spectroscopy applications for monitoring blend uniformity in the continuous manufacturing of solid oral dosage forms. Int J Pharm 2022; 615:121462. [PMID: 35026317 DOI: 10.1016/j.ijpharm.2022.121462] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 12/20/2021] [Accepted: 01/07/2022] [Indexed: 10/19/2022]
Abstract
Near infrared (NIR) spectroscopy has been widely recognized as a powerful PAT tool for monitoring blend uniformity in continuous manufacturing (CM) processes. However, the dynamic nature of the powder stream and the fast rate at which it moves, compared to batch processes, introduces challenges to NIR quantitative methods for monitoring blend uniformity. For instance, defining the effective sample size interrogated by NIR, selecting the best sampling location for blend monitoring, and ensuring NIR model robustness against influential sources of variability are challenges commonly reported for NIR applications in CM. This article reviews the NIR applications for powder blend monitoring in the continuous manufacturing of solid oral dosage forms, with a particular focus on the challenges, opportunities for method optimization and recent advances with respect three main aspects: effective sample size measured by NIR, probe location and method robustness.
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Affiliation(s)
- Natasha L Velez
- Duquesne University Graduate School for Pharmaceutical Sciences, Pittsburgh, PA 15282, United States; Duquesne Center for Pharmaceutical Technology, Duquesne University, Pittsburgh, PA 15282, United States.
| | - James K Drennen
- Duquesne University Graduate School for Pharmaceutical Sciences, Pittsburgh, PA 15282, United States; Duquesne Center for Pharmaceutical Technology, Duquesne University, Pittsburgh, PA 15282, United States.
| | - Carl A Anderson
- Duquesne University Graduate School for Pharmaceutical Sciences, Pittsburgh, PA 15282, United States; Duquesne Center for Pharmaceutical Technology, Duquesne University, Pittsburgh, PA 15282, United States.
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4
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Sierra-Vega NO, González-Rosario RA, Rangel-Gil RS, Romañach RJ, Méndez R. Quantitative analysis of blend uniformity within a Three-Chamber feed frame using simultaneously Raman and Near-Infrared spectroscopy. Int J Pharm 2021; 613:121417. [PMID: 34965466 DOI: 10.1016/j.ijpharm.2021.121417] [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: 10/29/2021] [Revised: 12/14/2021] [Accepted: 12/18/2021] [Indexed: 11/29/2022]
Abstract
This study reports the use of Raman and Near-infrared (NIR) spectroscopy to simultaneously monitor the drug concentration in flowing powder blends within a three-chamber feed frame. The Raman probe was located at the top of the dosing chamber, while the NIR probe was located at the top of the filling chamber. The Raman and NIR spectra were continuously acquired while the powder blends flowed through the feed frame. Calibration models were developed with spectra from a total of five calibration blends ranging in caffeine concentration among 3.50 and 6.50% w/w. These models were optimized to predict three test set blends of 4.00, 5.00, and 6.00% w/w caffeine. The results showed a high predictive ability of the models based on root mean square error of predictions of 0.174 and 0.235% w/w for NIR and Raman spectroscopic models, respectively. Concentration profiles with higher variability were observed for the Raman spectroscopy predictions. An estimate of the mass analyzed by each spectrum showed that a NIR spectrum analyzes approximately 4.5 times the mass analyzed by a Raman spectrum; despite these differences in the mass analyzed, blend uniformity results are equivalent between techniques. Variographic analysis demonstrated that both techniques have significantly low sampling errors for the real-time monitoring process of drug concentration within the feed frame.
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Affiliation(s)
- Nobel O Sierra-Vega
- Department of Chemical Engineering, University of Puerto Rico at Mayaguez, Puerto Rico 00681, United States.
| | - Rafael A González-Rosario
- Department of Chemical Engineering, University of Puerto Rico at Mayaguez, Puerto Rico 00681, United States
| | - Raúl S Rangel-Gil
- Department of Chemical Engineering, University of Puerto Rico at Mayaguez, Puerto Rico 00681, United States
| | - Rodolfo J Romañach
- Department of Chemistry, University of Puerto Rico at Mayaguez, Puerto Rico 00681, United States
| | - Rafael Méndez
- Department of Chemical Engineering, University of Puerto Rico at Mayaguez, Puerto Rico 00681, United States
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5
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Román-Ospino AD, Baranwal Y, Li J, Vargas J, Igne B, Bate S, Brouckaert D, Chauchard F, Hausner D, Ramachandran R, Singh R, Muzzio FJ. Sampling optimization for blend monitoring of a low dose formulation in a tablet press feed frame using spatially resolved near-infrared spectroscopy. Int J Pharm 2021; 602:120594. [PMID: 33857586 DOI: 10.1016/j.ijpharm.2021.120594] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 03/23/2021] [Accepted: 04/07/2021] [Indexed: 10/21/2022]
Abstract
In-line measurements of low dose blends in the feed frame of a tablet press were performed for API concentration levels as low as 0.10% w/w. The proposed methodology utilizes the advanced sampling capabilities of a Spatially Resolved Near-Infrared (SR-NIR) probe to develop Partial Least-Squares calibration models. The fast acquisition speed of multipoint spectra allowed the evaluation of different numbers of co-adds and feed frame paddle speeds to establish the optimum conditions of data collection to predict low potency blends. The interaction of the feed frame paddles with the SR-NIR probe was captured with high resolution and allowed the implementation of a spectral data selection criterion to remove the effect of the paddles from the calibration and testing process. The method demonstrated accuracy and robustness when predicting drug concentrations across different feed frame paddle speeds.
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Affiliation(s)
- Andrés D Román-Ospino
- Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, United States
| | - Yukteshwar Baranwal
- Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, United States
| | - Jingzhe Li
- Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, United States
| | - Jenny Vargas
- GlaxoSmithKline (GSK), Collegeville, PA 19426, United States
| | - Benoît Igne
- GlaxoSmithKline (GSK), Collegeville, PA 19426, United States
| | - Simon Bate
- GlaxoSmithKline (GSK), Collegeville, PA 19426, United States
| | | | | | - Douglas Hausner
- Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, United States
| | - Rohit Ramachandran
- Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, United States
| | - Ravendra Singh
- Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, United States
| | - Fernando J Muzzio
- Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, United States.
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6
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Alam MA, Liu YA, Dolph S, Pawliczek M, Peeters E, Palm A. Benchtop NIR method development for continuous manufacturing scale to enable efficient PAT application for solid oral dosage form. Int J Pharm 2021; 601:120581. [PMID: 33839228 DOI: 10.1016/j.ijpharm.2021.120581] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 03/24/2021] [Accepted: 04/04/2021] [Indexed: 11/15/2022]
Abstract
A Near Infrared (NIR) method was developed using a small benchtop feed frame system to quantify Saccharin potency in a powder blend during continuous manufacturing process. A 15-point Design of Experiments (DoE) was created based on the NIR spectral response and compositions of the formulation to develop a calibration set. The calibration set was designed to create compositional and raw material lots variation using minimum resources. The calibration experiments utilized around 0.5 kg Saccharin (Active Pharmaceutical Ingredient (API) surrogate) and 1.8 kg of excipients. Partial Least Square (PLS) modeling was used to develop a quantitative NIR method from the calibration data. The NIR method was implemented during 5 test batches in two different manufacturing sites across different potency levels at a continuous manufacturing platform for direction compression. Acceptable prediction performance was achieved from the NIR method at both sites. The NIR method was robust against changes in process scale and NIR instruments. The variance information built into the calibration set was found to be critical to successful model performance. This study shows a benchtop feed frame can be used for material sparing calibration method development without operating at a full-scale process line and applied across multiple sites, instruments at different potency levels.
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Affiliation(s)
- Md Anik Alam
- Worldwide Research and Development, Pfizer Inc., Groton, CT 06340, USA.
| | - Yang Angela Liu
- Worldwide Research and Development, Pfizer Inc., Groton, CT 06340, USA
| | - Stephanie Dolph
- Worldwide Research and Development, Pfizer Inc., Groton, CT 06340, USA
| | - Marcin Pawliczek
- Pfizer Global Supply, Pfizer Manufacturing Deutschland GmbH, Freiburg, Germany
| | - Elisabeth Peeters
- Worldwide Research and Development, Pfizer Inc., Groton, CT 06340, USA
| | - Andrew Palm
- Worldwide Research and Development, Pfizer Inc., Groton, CT 06340, USA
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7
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An agile and robust in-line NIR potency deviation detection method for monitoring and control of a continuous direct compression process. Int J Pharm 2021; 601:120521. [PMID: 33775726 DOI: 10.1016/j.ijpharm.2021.120521] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 03/10/2021] [Accepted: 03/21/2021] [Indexed: 11/23/2022]
Abstract
Near Infrared (NIR) method for blend potency estimation has been commonly used as an essential tool for process monitoring and control in continuous manufacturing of solid oral dosage forms. Robustness has been the main challenge for successful application of an NIR method, which often results in a long development time with frequent method update. Robustness deficiency often presents as an offset (bias) on the mean potency estimation. In this paper, the purpose of the NIR method has been redefined from estimating potency to potency deviation. This quantitative approach uses the mean centered potency to estimate potency deviations from the process mean, therefore, detects the non-conforming materials for continuous process monitoring and control. An NIR method was developed at the lab benchtop scale and directly deployed to a direct compression continuous manufacturing platform at Pfizer for mean centered potency estimation. The benchtop calibration provided a speedy and efficient NIR method development and the method showed enhanced robustness for estimating potency deviation in presence of wide process and raw material variations. Integrating with the mean centered approach, the NIR model from the lab could be implemented to different sites using different instruments without requiring model update for the established range of process conditions and raw material properties.
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8
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Shi G, Lin L, Liu Y, Chen G, Luo Y, Wu Y, Li H. Pharmaceutical application of multivariate modelling techniques: a review on the manufacturing of tablets. RSC Adv 2021; 11:8323-8345. [PMID: 35423324 PMCID: PMC8695199 DOI: 10.1039/d0ra08030f] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Accepted: 01/26/2021] [Indexed: 11/21/2022] Open
Abstract
The tablet manufacturing process is a complex system, especially in continuous manufacturing (CM). It includes multiple unit operations, such as mixing, granulation, and tableting. In tablet manufacturing, critical quality attributes are influenced by multiple factorial relationships between material properties, process variables, and interactions. Moreover, the variation in raw material attributes and manufacturing processes is an inherent characteristic and seriously affects the quality of pharmaceutical products. To deepen our understanding of the tablet manufacturing process, multivariable modeling techniques can replace univariate analysis to investigate tablet manufacturing. In this review, the roles of the most prominent multivariate modeling techniques in the tablet manufacturing process are discussed. The review mainly focuses on applying multivariate modeling techniques to process understanding, optimization, process monitoring, and process control within multiple unit operations. To minimize the errors in the process of modeling, good modeling practice (GMoP) was introduced into the pharmaceutical process. Furthermore, current progress in the continuous manufacturing of tablets and the role of multivariate modeling techniques in continuous manufacturing are introduced. In this review, information is provided to both researchers and manufacturers to improve tablet quality.
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Affiliation(s)
- Guolin Shi
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Longfei Lin
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Yuling Liu
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Gongsen Chen
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Yuting Luo
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Yanqiu Wu
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
| | - Hui Li
- Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700 China
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9
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Hetrick EM, Shi Z, Harms ZD, Myers DP. Sample Mass Estimate for the Use of Near-Infrared and Raman Spectroscopy to Monitor Content Uniformity in a Tablet Press Feed Frame of a Drug Product Continuous Manufacturing Process. APPLIED SPECTROSCOPY 2021; 75:216-224. [PMID: 32721168 DOI: 10.1177/0003702820950318] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Recently, feed frame-based process analytical technology measurements used to assure product quality during continuous manufacturing processes have received significant attention. These measurements are able to accurately determine uniformity of the powder blend before compression, and in these applications, it is necessary to understand the interrogated sample volume per measurement. This understanding ensures that the blend measurement can be indicative of the uniformity of the final dosage form. A scientifically sound approach is proposed here to estimate sample mass for a continuous manufacturing process that utilizes either near infrared or Raman spectroscopy. A wide range of commercially available probes with varying spot diameters are considered. By comparing near infrared and Raman spectroscopy, an optimal range of probe spot diameters was identified in order to reach an estimated sample mass between 50 and 500 mg for pharmaceutical blends per measurement, which is equivalent to common tablet weight ranges for solid oral dosage forms currently on the market.
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Affiliation(s)
- Evan M Hetrick
- Lilly Research Laboratories, Eli Lilly & Co., Indianapolis, IN, USA
| | - Zhenqi Shi
- Lilly Research Laboratories, Eli Lilly & Co., Indianapolis, IN, USA
| | - Zachary D Harms
- Lilly Research Laboratories, Eli Lilly & Co., Indianapolis, IN, USA
| | - David P Myers
- Lilly Research Laboratories, Eli Lilly & Co., Indianapolis, IN, USA
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10
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Aldama J, Shi Z, Ortega-Zúñiga C, Romañach RJ, Lysenko S. Fractal and Polarization Properties of Light Scattering Using Microcrystalline Pharmaceutical Aggregates. APPLIED SPECTROSCOPY 2021; 75:94-106. [PMID: 33030990 DOI: 10.1177/0003702820949272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Fractal and polarization analysis of diffusively scattered light is applied to determine the complex relationship between fractal dimension of structural morphology and concentration of chemically active ingredients in two pharmaceutical mixture systems including a series of binary mixtures of acetaminophen in lactose and three multicomponent blends with a proprietary active ingredient. A robust approach is proposed to identify and filter out multiple- and single-scattering components of scattering indicatrix. The fractal dimension extracted from scattering field reveals complex structural details of the sample, showing strong dependence on low-dose drug concentration in the blend. Low-angle diffraction shows optical "halo" patterns near the angle of specular reflection caused by light refraction in microcrystalline aggregates. Angular measurements of diffuse reflection demonstrate noticeable dependence of Brewster's angle on drug concentration. It is shown that the acetaminophen microcrystals produce scattered light depolarization due to their optical birefringence. The light scattering measurement protocol developed for diffusively scattered light by microcrystalline pharmaceutical compositions provides a novel approach for the pattern recognition, analysis and classification of materials with a low concentration of active chemical ingredients.
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Affiliation(s)
- Jennifer Aldama
- Department of Physics, University of Puerto Rico, Mayaguez, Puerto Rico
- ICFO-Institut de Ciencies Fotoniques, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain
| | - Zhenqi Shi
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, IN, USA
| | | | - Rodolfo J Romañach
- Department of Chemistry, University of Puerto Rico, Mayaguez, Puerto Rico
| | - Sergiy Lysenko
- Department of Physics, University of Puerto Rico, Mayaguez, Puerto Rico
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11
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Tanimura S, Singh R, Román-Ospino AD, Ierapetritou M. Residence time distribution modelling and in line monitoring of drug concentration in a tablet press feed frame containing dead zones. Int J Pharm 2020; 592:120048. [PMID: 33161037 DOI: 10.1016/j.ijpharm.2020.120048] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 10/15/2020] [Accepted: 11/01/2020] [Indexed: 01/08/2023]
Abstract
The presence of a 'significant dead zone' in any continuous manufacturing equipment may affect the product quality and need to be investigated systematically. Dead zone will affect the residence time distribution (RTD) of continuous manufacturing and thus the mixing and product quality. Tablet press (feed frame) is one of unit operations that directly influence the critical quality attributes (CQA's). However, currently no systematic methods and tools are available to characterize and model the feed frame dead zone. In this manuscript, the RTD of the tablet press feed frame containing dead zone is investigated. Step-change experiments revealed that the feed frame could be expressed as a traditional continuous stirred tank model. The volume fractions of the dead zones are determined experimentally as well as using RTD model. In addition, an in-line NIR method for drug concentration monitoring inside the feed frame is also developed. The developed NIR calibration model enables to monitor the drug concentration precisely and detect the variation immediately with the probe positioned right above the left paddle. It is also found that the feed frame paddle speed slightly affects the predictive accuracy of NIR, while the die disc speed has no significant effect.
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Affiliation(s)
- Shinji Tanimura
- CMC R&D Center, Kyowa Kirin Co., Ltd., 1188 Shimotogari, Nagaizumi-cho, Sunto-gun, Shizuoka 411-8731 Japan
| | - Ravendra Singh
- Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.
| | - Andrés D Román-Ospino
- Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemical and Biochemical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Marianthi Ierapetritou
- Department of Chemical and Biomolecular Engineering, University of Delaware, DE 19716, USA.
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12
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Sierra-Vega NO, Romañach RJ, Méndez R. Real-time quantification of low-dose cohesive formulations within a sampling interface for flowing powders. Int J Pharm 2020; 588:119726. [DOI: 10.1016/j.ijpharm.2020.119726] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Revised: 07/29/2020] [Accepted: 07/31/2020] [Indexed: 11/27/2022]
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13
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Liu S, Tong L, Jiang M, Feng X, Yin S, Liu C, Wang L, Ding Y. Flow stratification characteristics of binary particles in a moving granular bed. POWDER TECHNOL 2020. [DOI: 10.1016/j.powtec.2020.07.035] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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14
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In-line monitoring of low drug concentration of flowing powders in a new sampler device. Int J Pharm 2020; 583:119358. [DOI: 10.1016/j.ijpharm.2020.119358] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 04/15/2020] [Accepted: 04/19/2020] [Indexed: 01/18/2023]
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15
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Hildebrandt C, Gopireddy SR, Scherließ R, Urbanetz NA. A DEM approach to assess the influence of the paddle wheel shape on force feeding during pharmaceutical tableting. ADV POWDER TECHNOL 2020. [DOI: 10.1016/j.apt.2019.11.030] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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16
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Alvarado-Hernández BB, Sierra-Vega NO, Martínez-Cartagena P, Hormaza M, Méndez R, Romañach RJ. A sampling system for flowing powders based on the theory of sampling. Int J Pharm 2019; 574:118874. [PMID: 31837408 DOI: 10.1016/j.ijpharm.2019.118874] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 11/10/2019] [Accepted: 11/12/2019] [Indexed: 12/16/2022]
Abstract
An innovative chute and stream sampler system for flowing powders has been developed and tested. The system is designed for representative sampling based on the principles of the Theory of Sampling (TOS). The sampling system was used in combination with near infrared (NIR) spectroscopy to determine the drug concentration of flowing powders. The system is comprised of three parts: a chute, a stream sampler and a sample collection port. The NIR spectra were obtained at the chute, before entering the sampler, and as the powder flowed through the stream sampler. Samples were also collected from the sample collection port to be analyzed using an ultraviolet-visible (UV-Vis) reference method to determine drug content. A total of eight pharmaceutical powder blends, ranging in concentration from 10.5(%w/w) to 19.5(%w/w) of caffeine, were used to test the sampling system. Materials were characterized before blends were made to provide information on flow properties. The throughput of the system was between 30 and 35 kg/h based on the flow properties of the blend. Drug concentration was effectively determined at the chute and stream sampler. The NIR calibration models showed low root mean squared errors of prediction, 0.65(%w/w) and 0.51(%w/w), for the chute and stream sampler respectively. The NIR calibration models also showed low bias values -0.36(%w/w) at the chute and 0.057(%w/w) at the stream sampler. Significant agreement was obtained between the results from the nondestructive NIR versus the destructive UV-Vis method. Variographic analysis was performed to estimate the analytical and sampling errors when determining the drug concentration at the chute and stream sampler respectively. The variographic analysis showed low analytical errors, 0.103(%w/w)2 and 0.181(%w/w)2 at the chute and stream sampler respectively. The analysis also showed that the minimum practical error (MPE) was around 0.2(%w/w)2 at both chute and stream sampler.
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Affiliation(s)
| | - Nobel O Sierra-Vega
- Department of Chemical Engineering, University of Puerto Rico at Mayaguez, Puerto Rico
| | - Pedro Martínez-Cartagena
- Department of Chemistry, University of Puerto Rico at Mayaguez, Call Box 9000, Mayaguez 00680, Puerto Rico
| | - Manuel Hormaza
- IBS Caribe INC., P.O. Box 8849, San Juan PR 00910, Puerto Rico
| | - Rafael Méndez
- Department of Chemical Engineering, University of Puerto Rico at Mayaguez, Puerto Rico
| | - Rodolfo J Romañach
- Department of Chemistry, University of Puerto Rico at Mayaguez, Call Box 9000, Mayaguez 00680, Puerto Rico.
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17
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Characterization of NIR interfaces for the feeding and in-line monitoring of a continuous granulation process. Int J Pharm 2019; 574:118848. [PMID: 31812798 DOI: 10.1016/j.ijpharm.2019.118848] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 10/28/2019] [Accepted: 11/04/2019] [Indexed: 11/23/2022]
Abstract
This work describes the characterization of three NIR interfaces intended to monitor a continuous granulation process. Two interfaces (i.e. a barrel interface and a rotating paddle interface) were evaluated to monitor the API concentration at the entrance of the granulator, and a third interface (i.e. an outlet interface), was evaluated to examine the quality of the resulting outlet granules. The barrel interface provided an assessment of the API concentration during the feeding process by scanning the material conveyed by the screws of the loss-in-weight feeder. The rotating paddle interface analyzed discrete amounts of powder upon exiting the feeder via the accumulation of material on the paddles. Partial Least Squares (PLS) calibration models were developed using the same powder blends for the two inlet interfaces and using the outlet granules for the outlet interface. Five independent batches were used to evaluate the prediction performance of each inlet calibration model. The outlet interface produced the lowest error of prediction due to the homogeneity of the granules. The barrel interface produced lower errors of prediction than the rotating paddle interface. However, powder density affected only the barrel interface, producing deviations in the predicted values. Therefore, powder density is a factor that should be considered in the calibration sample design for spectroscopic measurements when using this type of interface. A variographic analysis demonstrated that the continuous 1-dimensional motion in the barrel and outlet interfaces produced representative measurements of each batch during calibration and test experiments, generating a low minimum practical error (MPE).
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18
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Sierra-Vega NO, Romañach RJ, Méndez R. Feed frame: The last processing step before the tablet compaction in pharmaceutical manufacturing. Int J Pharm 2019; 572:118728. [PMID: 31682965 DOI: 10.1016/j.ijpharm.2019.118728] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Revised: 09/19/2019] [Accepted: 09/21/2019] [Indexed: 10/25/2022]
Abstract
The feed frame is a force-feeding device used in the die filling process. The die filling process is crucial within pharmaceutical manufacturing to guarantee the critical quality attributes of the tablets. In recent years, interest in this unit has increased because it can affect the properties of the powder blend and tablets, and because of the success in real time monitoring of powder blend uniformity potential for Process Analytical Technology as described in this review. The review focuses on the recent advances in understanding the powder flow behavior inside the feed frame and how the residence time distribution of the powder within the feed frame is affected by the operating conditions and design parameters. Furthermore, this review also highlights the effect of the paddle wheel design and feed frame process parameters on the tablet weight, the principal variable for measuring die filling performance.
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Affiliation(s)
- Nobel O Sierra-Vega
- Department of Chemical Engineering, University of Puerto Rico at Mayaguez, PR 00681, United States
| | - Rodolfo J Romañach
- Department of Chemistry, University of Puerto Rico at Mayaguez, PR 00681 United States
| | - Rafael Méndez
- Department of Chemical Engineering, University of Puerto Rico at Mayaguez, PR 00681, United States.
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19
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Development and validation of in-line near-infrared spectroscopy based analytical method for commercial production of a botanical drug product. J Pharm Biomed Anal 2019; 174:674-682. [DOI: 10.1016/j.jpba.2019.06.046] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Revised: 06/25/2019] [Accepted: 06/29/2019] [Indexed: 11/21/2022]
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20
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Razuc M, Grafia A, Gallo L, Ramírez-Rigo MV, Romañach RJ. Near-infrared spectroscopic applications in pharmaceutical particle technology. Drug Dev Ind Pharm 2019; 45:1565-1589. [DOI: 10.1080/03639045.2019.1641510] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- M. Razuc
- Instituto de Química del Sur (INQUISUR), Universidad Nacional del Sur (UNS)-CONICET, Bahía Blanca, Argentina
- Departamento de Biología, Bioquímica y Farmacia, Universidad Nacional del Sur (UNS), Bahía Blanca, Argentina
| | - A. Grafia
- Planta Piloto de Ingeniería Química (PLAPIQUI), Universidad Nacional del Sur (UNS)- CONICET, Bahía Blanca, Argentina
| | - L. Gallo
- Departamento de Biología, Bioquímica y Farmacia, Universidad Nacional del Sur (UNS), Bahía Blanca, Argentina
- Planta Piloto de Ingeniería Química (PLAPIQUI), Universidad Nacional del Sur (UNS)- CONICET, Bahía Blanca, Argentina
| | - M. V. Ramírez-Rigo
- Departamento de Biología, Bioquímica y Farmacia, Universidad Nacional del Sur (UNS), Bahía Blanca, Argentina
- Planta Piloto de Ingeniería Química (PLAPIQUI), Universidad Nacional del Sur (UNS)- CONICET, Bahía Blanca, Argentina
| | - R. J. Romañach
- Department of Chemistry, Center for Structured Organic Particulate Systems, University of Puerto Rico – Mayagüez, Mayagüez, Puerto Rico
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21
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Evaluation of an in-line NIR spectroscopic method for the determination of the residence time in a tablet press. Int J Pharm 2019; 565:358-366. [DOI: 10.1016/j.ijpharm.2019.05.006] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 04/28/2019] [Accepted: 05/04/2019] [Indexed: 10/26/2022]
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22
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Harms ZD, Shi Z, Kulkarni RA, Myers DP. Characterization of Near-Infrared and Raman Spectroscopy for In-Line Monitoring of a Low-Drug Load Formulation in a Continuous Manufacturing Process. Anal Chem 2019; 91:8045-8053. [DOI: 10.1021/acs.analchem.8b05002] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Zachary D. Harms
- Small Molecule Design and Development, Eli Lilly and Company, Indianapolis, Indiana 46285, United States
| | - Zhenqi Shi
- Small Molecule Design and Development, Eli Lilly and Company, Indianapolis, Indiana 46285, United States
| | - Rajesh A. Kulkarni
- Small Molecule Design and Development, Eli Lilly and Company, Indianapolis, Indiana 46285, United States
| | - David P. Myers
- Small Molecule Design and Development, Eli Lilly and Company, Indianapolis, Indiana 46285, United States
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23
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Variographic analysis: A new methodology for quality assurance of pharmaceutical blending processes. Comput Chem Eng 2019. [DOI: 10.1016/j.compchemeng.2019.02.010] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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24
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Sierra-Vega NO, Román-Ospino A, Scicolone J, Muzzio FJ, Romañach RJ, Méndez R. Assessment of blend uniformity in a continuous tablet manufacturing process. Int J Pharm 2019; 560:322-333. [PMID: 30763679 DOI: 10.1016/j.ijpharm.2019.01.073] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 01/25/2019] [Accepted: 01/31/2019] [Indexed: 12/20/2022]
Abstract
Blend uniformity was monitored throughout a continuous manufacturing (CM) process by near infrared (NIR) spectroscopic measurements of flowing blends and compared to the drug concentration in the tablets. The NIR spectra were obtained through the chute after the blender and within the feed frame, while transmission spectra were obtained for the tablets. The CM process was performed with semi-fine acetaminophen blends at 10.0% (w/w). The blender was operated at 250 RPM, for best performance, and 106 and 495 rpm where a lower mixing efficiency was expected. The variation in blender RPM increased the variation in drug concentration at the chute but not at the feed frame. Statistical results show that the drug concentration of tablets can be predicted, with great accuracy, from blends within the feed frame. This study demonstrated a mixing effect within the feed frame, which contribute to a 60% decrease in the relative standard deviation of the drug concentration, when compared to the chute. Variographic analysis showed that the minimum sampling and analytical error was five times less in the feed frame than the chute. This study demonstrates that the feed frame is an ideal location for monitoring the drug concentration of powder blends for CM processes.
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Affiliation(s)
- Nobel O Sierra-Vega
- Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemical Engineering, University of Puerto Rico at Mayaguez, PR 00681, United States
| | - Andrés Román-Ospino
- Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemical and Biochemical Engineering, Rutgers University, New Jersey, Piscataway 08854, United States
| | - James Scicolone
- Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemical and Biochemical Engineering, Rutgers University, New Jersey, Piscataway 08854, United States
| | - Fernando J Muzzio
- Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemical and Biochemical Engineering, Rutgers University, New Jersey, Piscataway 08854, United States
| | - Rodolfo J Romañach
- Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemistry, University of Puerto Rico at Mayaguez, PR 00681, United States
| | - Rafael Méndez
- Center for Structured Organic Particulate Systems (C-SOPS), Department of Chemical Engineering, University of Puerto Rico at Mayaguez, PR 00681, United States.
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25
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Development of near infrared spectroscopic calibration models for in-line determination of low drug concentration, bulk density, and relative specific void volume within a feed frame. J Pharm Biomed Anal 2019; 164:211-222. [DOI: 10.1016/j.jpba.2018.10.046] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 10/24/2018] [Accepted: 10/25/2018] [Indexed: 11/24/2022]
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26
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Characterizing drug product continuous manufacturing residence time distributions of major/minor excipient step changes using near infrared spectroscopy and process parameters. Int J Pharm 2018; 551:60-66. [DOI: 10.1016/j.ijpharm.2018.08.059] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Revised: 08/10/2018] [Accepted: 08/31/2018] [Indexed: 11/16/2022]
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