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Kreiser MJ, Wabel C, Wagner KG. Impact of Vertical Blender Unit Parameters on Subsequent Process Parameters and Tablet Properties in a Continuous Direct Compression Line. Pharmaceutics 2022; 14:pharmaceutics14020278. [PMID: 35214014 PMCID: PMC8879867 DOI: 10.3390/pharmaceutics14020278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 01/14/2022] [Accepted: 01/20/2022] [Indexed: 12/10/2022] Open
Abstract
The continuous manufacturing of solid oral-dosage forms represents an emerging technology among the pharmaceutical industry, where several process steps are combined in one production line. As all mixture components, including the lubricant (magnesium stearate), are passing simultaneously through one blender, an impact on the subsequent process steps and critical product properties, such as content uniformity and tablet tensile strength, is to be expected. A design of experiment (DoE) was performed to investigate the impact of the blender variables hold-up mass (HUM), impeller speed (IMP) and throughput (THR) on the mixing step and the subsequent continuous manufacturing process steps. Significant impacts on the mixing parameters (exit valve opening width (EV), exit valve opening width standard deviation (EV SD), torque of lower impeller (TL), torque of lower impeller SD (TL SD), HUM SD and blend potency SD), material attributes of the blend (conditioned bulk density (CBD), flow rate index (FRI) and particle size (d10 values)), tableting parameters (fill depth (FD), bottom main compression height (BCH) and ejection force (EF)) and tablet properties (tablet thickness (TT), tablet weight (TW) and tensile strength (TS)) could be found. Furthermore, relations between these process parameters were evaluated to define which process states were caused by which input variables. For example, the mixing parameters were mainly impacted by impeller speed, and material attributes, FD and TS were mainly influenced by variations in total blade passes (TBP). The current work presents a rational methodology to minimize process variability based on the main blender variables hold-up mass, impeller speed and throughput. Moreover, the results facilitated a knowledge-based optimization of the process parameters for optimum product properties.
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Affiliation(s)
- Marius J. Kreiser
- Product and Process Development, Pfizer Manufacturing Deutschland GmbH, 79108 Freiburg, Germany; (M.J.K.); (C.W.)
- Department of Pharmaceutical Technology and Biopharmaceutics, University of Bonn, 53121 Bonn, Germany
| | - Christoph Wabel
- Product and Process Development, Pfizer Manufacturing Deutschland GmbH, 79108 Freiburg, Germany; (M.J.K.); (C.W.)
| | - Karl G. Wagner
- Department of Pharmaceutical Technology and Biopharmaceutics, University of Bonn, 53121 Bonn, Germany
- Correspondence:
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Bhalode P, Tian H, Gupta S, Razavi SM, Roman-Ospino A, Talebian S, Singh R, Scicolone JV, Muzzio FJ, Ierapetritou M. Using residence time distribution in pharmaceutical solid dose manufacturing - A critical review. Int J Pharm 2021; 610:121248. [PMID: 34748808 DOI: 10.1016/j.ijpharm.2021.121248] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 10/04/2021] [Accepted: 10/27/2021] [Indexed: 11/18/2022]
Abstract
While continuous manufacturing (CM) of pharmaceutical solid-based drug products has been shown to be advantageous for improving the product quality and process efficiency in alignment with FDA's support of the quality-by-design paradigm (Lee, 2015; Ierapetritou et al., 2016; Plumb, 2005; Schaber, 2011), it is critical to enable full utilization of CM technology for robust production and commercialization (Schaber, 2011; Byrn, 2015). To do so, an important prerequisite is to obtain a detailed understanding of overall process characteristics to develop cost-effective and accurate predictive models for unit operations and process flowsheets. These models are utilized to predict product quality and maintain desired manufacturing efficiency (Ierapetritou et al., 2016). Residence time distribution (RTD) has been a widely used tool to characterize the extent of mixing in pharmaceutical unit operations (Vanhoorne, 2020; Rogers and Ierapetritou, 2015; Teżyk et al., 2015) and manufacturing lines and develop computationally cheap predictive models. These models developed using RTD have been demonstrated to be crucial for various flowsheet applications (Kruisz, 2017; Martinetz, 2018; Tian, 2021). Though extensively used in the literature (Gao et al., 2012), the implementation, execution, evaluation, and assessment of RTD studies has not been standardized by regulatory agencies and can thus lead to ambiguity regarding their accurate implementation. To address this issue and subsequently prevent unforeseen errors in RTD implementation, the presented article aims to aid in developing standardized guidelines through a detailed review and critical discussion of RTD studies in the pharmaceutical manufacturing literature. The review article is divided into two main sections - 1) determination of RTD including different steps for RTD evaluation including experimental approach, data acquisition and pre-treatment, RTD modeling, and RTD metrics and, 2) applications of RTD for solid dose manufacturing. Critical considerations, pertaining to the limitations of RTDs for solid dose manufacturing, are also examined along with a perspective discussion of future avenues of improvement.
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Affiliation(s)
- Pooja Bhalode
- Department of Chemical and Biochemical Engineering, Rutgers - The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Huayu Tian
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE 19716, USA
| | - Shashwat Gupta
- Department of Chemical and Biochemical Engineering, Rutgers - The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Sonia M Razavi
- Department of Chemical and Biochemical Engineering, Rutgers - The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Andres Roman-Ospino
- Department of Chemical and Biochemical Engineering, Rutgers - The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Shahrzad Talebian
- Department of Chemical and Biochemical Engineering, Rutgers - The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Ravendra Singh
- Department of Chemical and Biochemical Engineering, Rutgers - The State University of New Jersey, Piscataway, NJ 08854, USA
| | - James V Scicolone
- Department of Chemical and Biochemical Engineering, Rutgers - The State University of New Jersey, Piscataway, NJ 08854, USA
| | - Fernando J Muzzio
- 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, Newark, DE 19716, USA.
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Lee KT, Kimber JA, Cogoni G, Brandon JK, Wilsdon D, Verrier HM, Grieb S, Blackwood DO, Jain AC, Doshi P. Continuous Mixing Technology: Characterization of a Vertical Mixer Using Residence Time Distribution. J Pharm Sci 2021; 110:2694-2702. [PMID: 33607187 DOI: 10.1016/j.xphs.2021.01.035] [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: 11/01/2020] [Revised: 01/03/2021] [Accepted: 01/22/2021] [Indexed: 11/30/2022]
Abstract
Continuous powder mixing technology (CMT) application during continuous direct compression has emerged as a leading technology used in the development and manufacture of solid oral dosage forms. The critical quality attributes of the final product are heavily dependent on the performance of the mixing step as the quality of mixing directly influences the drug product quality attributes. This study investigates the impact of blend material properties (bulk density, API particle size distribution) and process parameters (process throughput, hold up mass and impeller speed) on the mixing performance. Mixing of the blend was characterized using the Residence Time Distribution (RTD) of the process by trending the outlet stream of the mixer using a near-infrared (NIR) probe after the injection of a small mass of tracer at the inlet stream. The outcomes of this study show that the RTDs of the mixer with throughput ranging between 15 and 30 kg/h; impeller speed ranging between 400 and 600 rpm and hold up mass (HUM) ranging between 500 and 850 g can be described by a series of two ideal Continuous Stirred Tank Reactors (CSTRs) with different volumes, and correspondingly, different mean residence times. It is also observed that the mixing is mainly occurring in the lower chamber of the CMT and the normalized RTDs of the mixer are similar across the range of process conditions and material attributes studied. The results also showed that the formulation blend with different API particle sizes and bulk properties, like bulk density and flowability, provide insignificant impact on the mixing performance. The CMT allows independent selection of target set points for HUM, impeller rotational speed and line throughput and it shows great robustness and flexibility for continuous blending in solid oral dose manufacturing.
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Affiliation(s)
- Kai T Lee
- Worldwide Research and Development, Pfizer Inc, Sandwich Kent, UK.
| | - James A Kimber
- Worldwide Research and Development, Pfizer Inc, Sandwich Kent, UK
| | - Giuseppe Cogoni
- Worldwide Research and Development, Pfizer Inc, Groton, CT, USA
| | - Jenna K Brandon
- Worldwide Research and Development, Pfizer Inc, Groton, CT, USA
| | - David Wilsdon
- Worldwide Research and Development, Pfizer Inc, Groton, CT, USA
| | - Hugh M Verrier
- Worldwide Research and Development, Pfizer Inc, Sandwich Kent, UK
| | - Sally Grieb
- Worldwide Research and Development, Pfizer Inc, Sandwich Kent, UK
| | | | | | - Pankaj Doshi
- Worldwide Research and Development, Pfizer Inc, Groton, CT, USA.
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Furukawa R, Singh R, Ierapetritou M. Effect of material properties on the residence time distribution (RTD) of a tablet press feed frame. Int J Pharm 2020; 591:119961. [DOI: 10.1016/j.ijpharm.2020.119961] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Revised: 09/18/2020] [Accepted: 10/05/2020] [Indexed: 11/24/2022]
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Gyürkés M, Madarász L, Köte Á, Domokos A, Mészáros D, Beke ÁK, Nagy B, Marosi G, Pataki H, Nagy ZK, Farkas A. Process Design of Continuous Powder Blending Using Residence Time Distribution and Feeding Models. Pharmaceutics 2020; 12:pharmaceutics12111119. [PMID: 33233635 PMCID: PMC7699818 DOI: 10.3390/pharmaceutics12111119] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 11/18/2020] [Accepted: 11/19/2020] [Indexed: 11/16/2022] Open
Abstract
The present paper reports a thorough continuous powder blending process design of acetylsalicylic acid (ASA) and microcrystalline cellulose (MCC) based on the Process Analytical Technology (PAT) guideline. A NIR-based method was applied using multivariate data analysis to achieve in-line process monitoring. The process dynamics were described with residence time distribution (RTD) models to achieve deep process understanding. The RTD was determined using the active pharmaceutical ingredient (API) as a tracer with multiple designs of experiment (DoE) studies to determine the effect of critical process parameters (CPPs) on the process dynamics. To achieve quality control through material diversion from feeding data, soft sensor-based process control tools were designed using the RTD model. The operation block model of the system was designed to select feasible experimental setups using the RTD model, and feeder characterizations as digital twins, therefore visualizing the output of theoretical setups. The concept significantly reduces the material and instrumental costs of process design and implementation.
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Explicit Residence Time Distribution of a Generalised Cascade of Continuous Stirred Tank Reactors for a Description of Short Recirculation Time (Bypassing). Processes (Basel) 2019. [DOI: 10.3390/pr7090615] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
The tanks-in-series model (TIS) is a popular model to describe the residence time distribution (RTD) of non-ideal continuously stirred tank reactors (CSTRs) with limited back-mixing. In this work, the TIS model was generalised to a cascade of n CSTRs with non-integer non-negative n. The resulting model describes non-ideal back-mixing with n > 1. However, the most interesting feature of the n-CSTR model is the ability to describe short recirculation times (bypassing) with n < 1 without the need of complex reactor networks. The n-CSTR model is the only model that connects the three fundamental RTDs occurring in reactor modelling by variation of a single shape parameter n: The unit impulse at n→0, the exponential RTD of an ideal CSTR at n = 1, and the delayed impulse of an ideal plug flow reactor at n→∞. The n-CSTR model can be used as a stand-alone model or as part of a reactor network. The bypassing material fraction for the regime n < 1 was analysed. Finally, a Fourier analysis of the n-CSTR was performed to predict the ability of a unit operation to filter out upstream fluctuations and to model the response to upstream set point changes.
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Detailed modeling and process design of an advanced continuous powder mixer. Int J Pharm 2018; 552:288-300. [DOI: 10.1016/j.ijpharm.2018.09.032] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Revised: 09/13/2018] [Accepted: 09/14/2018] [Indexed: 11/30/2022]
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Sheoran M, Chandra A, Bhunia H, Bajpai PK, Pant HJ. Residence time distribution studies using radiotracers in chemical industry—A review. CHEM ENG COMMUN 2018. [DOI: 10.1080/00986445.2017.1410478] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Affiliation(s)
- Meenakshi Sheoran
- Department of Chemical Engineering, Thapar Institute of Engineering & Technology, Patiala, Punjab, India
| | - Avinash Chandra
- Department of Chemical Engineering, Thapar Institute of Engineering & Technology, Patiala, Punjab, India
| | - Haripada Bhunia
- Department of Chemical Engineering, Thapar Institute of Engineering & Technology, Patiala, Punjab, India
| | - Pramod K. Bajpai
- Department of Chemical Engineering, Thapar Institute of Engineering & Technology, Patiala, Punjab, India
| | - Harish J. Pant
- Isotope and Radiation Application Division, Bhabha Atomic Research Centre, Mumbai, India
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Meier R, Thommes M, Rasenack N, Moll KP, Krumme M, Kleinebudde P. Granule size distributions after twin-screw granulation – Do not forget the feeding systems. Eur J Pharm Biopharm 2016; 106:59-69. [DOI: 10.1016/j.ejpb.2016.05.011] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2015] [Revised: 05/13/2016] [Accepted: 05/15/2016] [Indexed: 11/26/2022]
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Engisch W, Muzzio F. Using Residence Time Distributions (RTDs) to Address the Traceability of Raw Materials in Continuous Pharmaceutical Manufacturing. J Pharm Innov 2015; 11:64-81. [PMID: 26937258 PMCID: PMC4759219 DOI: 10.1007/s12247-015-9238-1] [Citation(s) in RCA: 105] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Continuous processing in pharmaceutical manufacturing is a relatively new approach that has generated significant attention. While it has been used for decades in other industries, showing significant advantages, the pharmaceutical industry has been slow in its adoption of continuous processing, primarily due to regulatory uncertainty. This paper aims to help address these concerns by introducing methods for batch definition, raw material traceability, and sensor frequency determination. All of the methods are based on established engineering and mathematical principles, especially the residence time distribution (RTD). This paper introduces a risk-based approach to address content uniformity challenges of continuous manufacturing. All of the detailed methods are discussed using a direct compaction manufacturing line as the main example, but the techniques can easily be applied to other continuous manufacturing methods such as wet and dry granulation, hot melt extrusion, capsule filling, etc.
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Affiliation(s)
- William Engisch
- Department of Chemical and Biochemical Engineering, Rutgers University, 98 Brett Rd., Piscataway, NJ 08854 USA
| | - Fernando Muzzio
- Department of Chemical and Biochemical Engineering, Rutgers University, 98 Brett Rd., Piscataway, NJ 08854 USA
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11
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12
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Xi Y, Chen Q, You C. Flow characteristics of biomass particles in a horizontal stirred bed reactor: Part II. Modeling studies on particle residence time distribution and axial mixing. POWDER TECHNOL 2015. [DOI: 10.1016/j.powtec.2014.07.039] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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13
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Engisch WE, Muzzio FJ. Loss-in-Weight Feeding Trials Case Study: Pharmaceutical Formulation. J Pharm Innov 2014. [DOI: 10.1007/s12247-014-9206-1] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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14
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Mathematical Development and Comparison of a Hybrid PBM-DEM Description of a Continuous Powder Mixing Process. ACTA ACUST UNITED AC 2013. [DOI: 10.1155/2013/843784] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
This paper describes the development of a multidimensional population balance model (PBM) which can account for the dynamics of a continuous powder mixing/blending process. The PBM can incorporate the important design and process conditions and determine their effects on the various critical quality attributes (CQAs) accordingly. The important parameters considered in this study are blender dimensions and presence of noise in the inlet streams. The blender dynamics have been captured in terms of composition of the ingredients, (relative standard deviation) RSD, and (residence time distribution) RTD. PBM interacts with discrete element modeling (DEM) via one-way coupling which forms a basic framework for hybrid modeling. The results thus obtained have been compared against a full DEM simulation which is a more fundamental particle-level model that elucidates the dynamics of the mixing process. Results show good qualitative agreement which lends credence to the use of coupled PBM as an effective tool in control and optimization of mixing process due to its relatively fewer computational requirements compared to DEM.
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Rogers AJ, Inamdar C, Ierapetritou MG. An Integrated Approach to Simulation of Pharmaceutical Processes for Solid Drug Manufacture. Ind Eng Chem Res 2013. [DOI: 10.1021/ie401344a] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Amanda J. Rogers
- Department of Chemical and Biochemical Engineering, Rutgers University, Piscataway, New Jersey 08854, United States
| | - Chaitali Inamdar
- Department of Chemical and Biochemical Engineering, Rutgers University, Piscataway, New Jersey 08854, United States
| | - Marianthi G. Ierapetritou
- Department of Chemical and Biochemical Engineering, Rutgers University, Piscataway, New Jersey 08854, United States
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16
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Modeling of Particulate Processes for the Continuous Manufacture of Solid-Based Pharmaceutical Dosage Forms. Processes (Basel) 2013. [DOI: 10.3390/pr1020067] [Citation(s) in RCA: 61] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
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17
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Gao Y, Boukouvala F, Engisch W, Meng W, Muzzio FJ, Ierapetritou MG. Improving Continuous Powder Blending Performance Using Projection to Latent Structures Regression. J Pharm Innov 2013. [DOI: 10.1007/s12247-013-9152-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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18
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19
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A multi-dimensional population balance model approach to continuous powder mixing processes. ADV POWDER TECHNOL 2013. [DOI: 10.1016/j.apt.2012.02.001] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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20
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Multi-dimensional population balance modeling and experimental validation of continuous powder mixing processes. Chem Eng Sci 2012. [DOI: 10.1016/j.ces.2012.06.024] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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22
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Gao Y, Muzzio FJ, Ierapetritou MG. A review of the Residence Time Distribution (RTD) applications in solid unit operations. POWDER TECHNOL 2012. [DOI: 10.1016/j.powtec.2012.05.060] [Citation(s) in RCA: 114] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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23
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Boukouvala F, Niotis V, Ramachandran R, Muzzio FJ, Ierapetritou MG. An integrated approach for dynamic flowsheet modeling and sensitivity analysis of a continuous tablet manufacturing process. Comput Chem Eng 2012. [DOI: 10.1016/j.compchemeng.2012.02.015] [Citation(s) in RCA: 105] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Gao Y, Ierapetritou M, Muzzio F. Investigation on the effect of blade patterns on continuous solid mixing performance. CAN J CHEM ENG 2011. [DOI: 10.1002/cjce.20530] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Yijie Gao
- Department of Chemical and Biochemical Engineering, Rutgers—The State University of New Jersey, 98 Brett Road, Piscataway, NJ 08854, U.S.A
| | - Marianthi Ierapetritou
- Department of Chemical and Biochemical Engineering, Rutgers—The State University of New Jersey, 98 Brett Road, Piscataway, NJ 08854, U.S.A
| | - Fernando Muzzio
- Department of Chemical and Biochemical Engineering, Rutgers—The State University of New Jersey, 98 Brett Road, Piscataway, NJ 08854, U.S.A
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Gao Y, Vanarase A, Muzzio F, Ierapetritou M. Characterizing continuous powder mixing using residence time distribution. Chem Eng Sci 2011. [DOI: 10.1016/j.ces.2010.10.045] [Citation(s) in RCA: 149] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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