The Experts below are selected from a list of 231 Experts worldwide ranked by ideXlab platform

Sara Moghtadernejad - One of the best experts on this subject based on the ideXlab platform.

  • effect of material properties on the residence time distribution rtd characterization of Powder Blending unit operations part ii of ii application of models
    Powder Technology, 2019
    Co-Authors: Sebastian M Escotetespinoza, Sara Moghtadernejad, Andres D Romanospino, Elisabeth Schafer, Philippe Cappuyns, Ivo Van Assche, Zilong Wang, Yifan Wang, Mauricio Futran
    Abstract:

    Abstract Residence time distribution (RTD) modeling can aid the understanding and characterization of macro-mixing in continuous Powder processing unit operations by relating observed behavior to quantitative model parameters. This article is the second part of the work done to characterize the effect of material properties on the measurement of RTDs in continuous Powder processing operations. The goal of this paper is to examine the behavior of the RTD given different sets of tracer material properties. Tracer addition methods are discussed within the framework of their mathematical representation. The two most widely used RTD models in Powder systems in the literature, the axial dispersion and the tank-in-series model, are presented and used to describe the experimental data. The RTD model parameters (e.g., Peclet number, number of tanks in series, and residence times) were regressed from the experimental data and compared using one-way ANOVA to determine the effects of materials properties on RTD. A model independent approach using a Multivariate Analysis of Variance (MANOVA) was also applied to compare the results with the model dependent method. Lastly, examples of how the RTD models can aid process design and understanding were described using both continuous and discrete convolution. The RTD models and their regressed coefficients were used to predict the mixing outputs of a semi-random input and the impact of disturbances on the process.

  • effect of tracer material properties on the residence time distribution rtd of continuous Powder Blending operations part i of ii experimental evaluation
    Powder Technology, 2019
    Co-Authors: Sebastian M Escotetespinoza, Sara Moghtadernejad, Andres D Romanospino, Elisabeth Schafer, Philippe Cappuyns, Ivo Van Assche, Mauricio Futran, Yifan Wang, Marianthi G. Ierapetritou
    Abstract:

    Abstract Residence time distribution (RTD) models are essential to understand process dynamics and support process monitoring and control in continuous manufacturing systems. RTD models can also be used to monitor material traceability and to isolate intermediate materials or finished products when specifications are not met. However, while pharmaceutical companies are currently making extensive use of RTD approaches, standard methods for conducting, interpreting, and using RTD results in continuous pharmaceutical manufacturing have not yet been established by regulatory authorities. This paper seeks to facilitate generating such standards. We discuss in detail the assumptions and conditions that are relevant to the proper selection of tracers for RTD experiments, and demonstrate that tracer selection can have substantial impact on RTD results. We selected seven materials with a wide range of properties as tracers and a single material as our base “blend”. The experimental results led to two major conclusions: (1) materials with different mechanical properties have dissimilar mean residence times (MRT) inside the systems and (2) blend ingredients with different mechanical properties travel at different speed inside of continuous Blending systems. Results further indicated there were two critical mean residence times (MRTs): that of the tracer and that of the bulk. Matching of material properties between tracers is key in order to obtain similar MRTs using a given tracer. Differences between selected tracer and bulk material properties were found to lead to differences between the bulk space time and the tracer MRT. A set of recommendations on how to select tracer materials that would help characterize accurately the RTD of a continuous flow system are presented.

James K Drennen - One of the best experts on this subject based on the ideXlab platform.

  • a process analytical technology approach to near infrared process control of pharmaceutical Powder Blending part i d optimal design for characterization of Powder mixing and preliminary spectral data evaluation
    Journal of Pharmaceutical Sciences, 2006
    Co-Authors: Arwa S Elhagrasy, Frank Damico, James K Drennen
    Abstract:

    Abstract Experimental design, multivariate data acquisition, and analysis in addition to real time monitoring and control through process analyzers, represent an integrated approach for implementation of Process Analytical Technology (PAT) in the pharmaceutical industry. This study, which is the first in a series of three parts, uses an experimental design approach to identify critical factors affecting Powder Blending. Powder mixtures composed of salicylic acid and lactose were mixed in an 8 qt. V-blender. D-optimal design was employed to characterize the Blending process, by studying the effect of humidity, component concentration, and blender speed on mixing end point. Additionally, changes in particle size and density of Powder mixtures were examined. A near-infrared (NIR) fiber-optic probe was used to monitor mixing, through multiple optical ports on the blender. Humidity, component concentration, and blender speed were shown to have a significant impact on the Blending process. Furthermore, humidity and concentration had a significant effect on particle size and density of Powder mixtures. NIRS was sensitive to changes in physicochemical properties of the mixtures, resulting from process variables. Proper selection of NIR spectral preprocessing is of ultimate importance for successful implementation of this technology in the monitoring and control of Powder Blending and is discussed. © 2005 Wiley-Liss, Inc. and the American Pharmacists Association

  • a process analytical technology approach to near infrared process control of pharmaceutical Powder Blending part ii qualitative near infrared models for prediction of blend homogeneity
    Journal of Pharmaceutical Sciences, 2006
    Co-Authors: Arwa S Elhagrasy, Miriam Delgadolopez, James K Drennen
    Abstract:

    Abstract The successful implementation of near-infrared spectroscopy (NIRS) in process control of Powder Blending requires constructing an inclusive spectral database that reflects the anticipated voluntary or involuntary changes in processing conditions, thereby minimizing bias in prediction of Blending behavior. In this study, experimental design was utilized as an efficient way of generating blend experiments conducted under varying processing conditions such as humidity, blender speed and component concentration. NIR spectral data, collected from different Blending experiments, was used to build qualitative models for prediction of blend homogeneity. Two pattern recognition algorithms: Soft Independent Modeling of Class Analogies (SIMCA) and Principal Component Modified Bootstrap Error-adjusted Single-sample Technique (PC-MBEST) were evaluated for qualitative analysis of NIR Blending data. Optimization of NIR models, for the two algorithms, was achieved by proper selection of spectral processing, and training set samples. The models developed were successful in predicting blend homogeneity of independent blend samples under different processing conditions. © 2005 Wiley-Liss, Inc. and the American Pharmacists Association

  • a process analytical technology approach to near infrared process control of pharmaceutical Powder Blending part iii quantitative near infrared calibration for prediction of blend homogeneity and characterization of Powder mixing kinetics
    Journal of Pharmaceutical Sciences, 2006
    Co-Authors: Arwa S Elhagrasy, James K Drennen
    Abstract:

    Abstract The Process Analytical Technology (PAT) initiative, undertaken by the Food and Drug Administration (FDA), paves the way for improvement of drug manufacturing through real-time measurements that allow better process understanding. This study is the third and final Part in a series of studies that represent an integrated approach for real-time blend uniformity assessment using near-infrared (NIR) technology. In this study, the development of a quantitative NIR model for prediction of Blending end point is presented. Process signature was built into NIR calibration models by using blend samples that were collected from actual blend experiments under different processing conditions. Evaluation of various calibration algorithms including principal component regression (PCR), partial least squares (PLS), and multi-term linear regression (MLR) was performed. It was found that linear regression, using a single wavelength, yielded optimum calibration and prediction results. The Blending profiles predicted by the NIR quantitative model correlated well to those determined by the UV reference analytical method. Characterization of intra-shell versus inter-shell Powder mixing kinetics and its implication in sensor positioning was also performed and will be discussed. © 2005 Wiley-Liss, Inc. and the American Pharmacists Association

  • a process analytical technology approach to near infrared process control of pharmaceutical Powder Blending part iii quantitative near infrared calibration for prediction of blend homogeneity and characterization of Powder mixing kinetics
    Journal of Pharmaceutical Sciences, 2006
    Co-Authors: Arwa S Elhagrasy, James K Drennen
    Abstract:

    The Process Analytical Technology (PAT) initiative, undertaken by the Food and Drug Administration (FDA), paves the way for improvement of drug manufacturing through real-time measurements that allow better process understanding. This study is the third and final Part in a series of studies that represent an integrated approach for real-time blend uniformity assessment using near-infrared (NIR) technology. In this study, the development of a quantitative NIR model for prediction of Blending end point is presented. Process signature was built into NIR calibration models by using blend samples that were collected from actual blend experiments under different processing conditions. Evaluation of various calibration algorithms including principal component regression (PCR), partial least squares (PLS), and multi-term linear regression (MLR) was performed. It was found that linear regression, using a single wavelength, yielded optimum calibration and prediction results. The Blending profiles predicted by the NIR quantitative model correlated well to those determined by the UV reference analytical method. Characterization of intra-shell versus inter-shell Powder mixing kinetics and its implication in sensor positioning was also performed and will be discussed.

  • A process analytical technology approach to near-infrared process control of pharmaceutical Powder Blending. Part I: D-optimal design for characterization of Powder mixing and preliminary spectral data evaluation
    Journal of Pharmaceutical Sciences, 2006
    Co-Authors: Arwa S El Hagrasy, Frank D'amico, James K Drennen
    Abstract:

    Experimental design, multivariate data acquisition, and analysis in addition to real time monitoring and control through process analyzers, represent an integrated approach for implementation of Process Analytical Technology (PAT) in the pharmaceutical industry. This study, which is the first in a series of three parts, uses an experimental design approach to identify critical factors affecting Powder Blending. Powder mixtures composed of salicylic acid and lactose were mixed in an 8 qt. V-blender. D-optimal design was employed to characterize the Blending process, by studying the effect of humidity, component concentration, and blender speed on mixing end point. Additionally, changes in particle size and density of Powder mixtures were examined. A near-infrared (NIR) fiber-optic probe was used to monitor mixing, through multiple optical ports on the blender. Humidity, component concentration, and blender speed were shown to have a significant impact on the Blending process. Furthermore, humidity and concentration had a significant effect on particle size and density of Powder mixtures. NIRS was sensitive to changes in physicochemical properties of the mixtures, resulting from process variables. Proper selection of NIR spectral preprocessing is of ultimate importance for successful implementation of this technology in the monitoring and control of Powder Blending and is discussed.

Mauricio Futran - One of the best experts on this subject based on the ideXlab platform.

  • effect of material properties on the residence time distribution rtd characterization of Powder Blending unit operations part ii of ii application of models
    Powder Technology, 2019
    Co-Authors: Sebastian M Escotetespinoza, Sara Moghtadernejad, Andres D Romanospino, Elisabeth Schafer, Philippe Cappuyns, Ivo Van Assche, Zilong Wang, Yifan Wang, Mauricio Futran
    Abstract:

    Abstract Residence time distribution (RTD) modeling can aid the understanding and characterization of macro-mixing in continuous Powder processing unit operations by relating observed behavior to quantitative model parameters. This article is the second part of the work done to characterize the effect of material properties on the measurement of RTDs in continuous Powder processing operations. The goal of this paper is to examine the behavior of the RTD given different sets of tracer material properties. Tracer addition methods are discussed within the framework of their mathematical representation. The two most widely used RTD models in Powder systems in the literature, the axial dispersion and the tank-in-series model, are presented and used to describe the experimental data. The RTD model parameters (e.g., Peclet number, number of tanks in series, and residence times) were regressed from the experimental data and compared using one-way ANOVA to determine the effects of materials properties on RTD. A model independent approach using a Multivariate Analysis of Variance (MANOVA) was also applied to compare the results with the model dependent method. Lastly, examples of how the RTD models can aid process design and understanding were described using both continuous and discrete convolution. The RTD models and their regressed coefficients were used to predict the mixing outputs of a semi-random input and the impact of disturbances on the process.

  • effect of tracer material properties on the residence time distribution rtd of continuous Powder Blending operations part i of ii experimental evaluation
    Powder Technology, 2019
    Co-Authors: Sebastian M Escotetespinoza, Sara Moghtadernejad, Andres D Romanospino, Elisabeth Schafer, Philippe Cappuyns, Ivo Van Assche, Mauricio Futran, Yifan Wang, Marianthi G. Ierapetritou
    Abstract:

    Abstract Residence time distribution (RTD) models are essential to understand process dynamics and support process monitoring and control in continuous manufacturing systems. RTD models can also be used to monitor material traceability and to isolate intermediate materials or finished products when specifications are not met. However, while pharmaceutical companies are currently making extensive use of RTD approaches, standard methods for conducting, interpreting, and using RTD results in continuous pharmaceutical manufacturing have not yet been established by regulatory authorities. This paper seeks to facilitate generating such standards. We discuss in detail the assumptions and conditions that are relevant to the proper selection of tracers for RTD experiments, and demonstrate that tracer selection can have substantial impact on RTD results. We selected seven materials with a wide range of properties as tracers and a single material as our base “blend”. The experimental results led to two major conclusions: (1) materials with different mechanical properties have dissimilar mean residence times (MRT) inside the systems and (2) blend ingredients with different mechanical properties travel at different speed inside of continuous Blending systems. Results further indicated there were two critical mean residence times (MRTs): that of the tracer and that of the bulk. Matching of material properties between tracers is key in order to obtain similar MRTs using a given tracer. Differences between selected tracer and bulk material properties were found to lead to differences between the bulk space time and the tracer MRT. A set of recommendations on how to select tracer materials that would help characterize accurately the RTD of a continuous flow system are presented.

Sebastian M Escotetespinoza - One of the best experts on this subject based on the ideXlab platform.

  • effect of material properties on the residence time distribution rtd characterization of Powder Blending unit operations part ii of ii application of models
    Powder Technology, 2019
    Co-Authors: Sebastian M Escotetespinoza, Sara Moghtadernejad, Andres D Romanospino, Elisabeth Schafer, Philippe Cappuyns, Ivo Van Assche, Zilong Wang, Yifan Wang, Mauricio Futran
    Abstract:

    Abstract Residence time distribution (RTD) modeling can aid the understanding and characterization of macro-mixing in continuous Powder processing unit operations by relating observed behavior to quantitative model parameters. This article is the second part of the work done to characterize the effect of material properties on the measurement of RTDs in continuous Powder processing operations. The goal of this paper is to examine the behavior of the RTD given different sets of tracer material properties. Tracer addition methods are discussed within the framework of their mathematical representation. The two most widely used RTD models in Powder systems in the literature, the axial dispersion and the tank-in-series model, are presented and used to describe the experimental data. The RTD model parameters (e.g., Peclet number, number of tanks in series, and residence times) were regressed from the experimental data and compared using one-way ANOVA to determine the effects of materials properties on RTD. A model independent approach using a Multivariate Analysis of Variance (MANOVA) was also applied to compare the results with the model dependent method. Lastly, examples of how the RTD models can aid process design and understanding were described using both continuous and discrete convolution. The RTD models and their regressed coefficients were used to predict the mixing outputs of a semi-random input and the impact of disturbances on the process.

  • effect of tracer material properties on the residence time distribution rtd of continuous Powder Blending operations part i of ii experimental evaluation
    Powder Technology, 2019
    Co-Authors: Sebastian M Escotetespinoza, Sara Moghtadernejad, Andres D Romanospino, Elisabeth Schafer, Philippe Cappuyns, Ivo Van Assche, Mauricio Futran, Yifan Wang, Marianthi G. Ierapetritou
    Abstract:

    Abstract Residence time distribution (RTD) models are essential to understand process dynamics and support process monitoring and control in continuous manufacturing systems. RTD models can also be used to monitor material traceability and to isolate intermediate materials or finished products when specifications are not met. However, while pharmaceutical companies are currently making extensive use of RTD approaches, standard methods for conducting, interpreting, and using RTD results in continuous pharmaceutical manufacturing have not yet been established by regulatory authorities. This paper seeks to facilitate generating such standards. We discuss in detail the assumptions and conditions that are relevant to the proper selection of tracers for RTD experiments, and demonstrate that tracer selection can have substantial impact on RTD results. We selected seven materials with a wide range of properties as tracers and a single material as our base “blend”. The experimental results led to two major conclusions: (1) materials with different mechanical properties have dissimilar mean residence times (MRT) inside the systems and (2) blend ingredients with different mechanical properties travel at different speed inside of continuous Blending systems. Results further indicated there were two critical mean residence times (MRTs): that of the tracer and that of the bulk. Matching of material properties between tracers is key in order to obtain similar MRTs using a given tracer. Differences between selected tracer and bulk material properties were found to lead to differences between the bulk space time and the tracer MRT. A set of recommendations on how to select tracer materials that would help characterize accurately the RTD of a continuous flow system are presented.

Marianthi G. Ierapetritou - One of the best experts on this subject based on the ideXlab platform.

  • effect of tracer material properties on the residence time distribution rtd of continuous Powder Blending operations part i of ii experimental evaluation
    Powder Technology, 2019
    Co-Authors: Sebastian M Escotetespinoza, Sara Moghtadernejad, Andres D Romanospino, Elisabeth Schafer, Philippe Cappuyns, Ivo Van Assche, Mauricio Futran, Yifan Wang, Marianthi G. Ierapetritou
    Abstract:

    Abstract Residence time distribution (RTD) models are essential to understand process dynamics and support process monitoring and control in continuous manufacturing systems. RTD models can also be used to monitor material traceability and to isolate intermediate materials or finished products when specifications are not met. However, while pharmaceutical companies are currently making extensive use of RTD approaches, standard methods for conducting, interpreting, and using RTD results in continuous pharmaceutical manufacturing have not yet been established by regulatory authorities. This paper seeks to facilitate generating such standards. We discuss in detail the assumptions and conditions that are relevant to the proper selection of tracers for RTD experiments, and demonstrate that tracer selection can have substantial impact on RTD results. We selected seven materials with a wide range of properties as tracers and a single material as our base “blend”. The experimental results led to two major conclusions: (1) materials with different mechanical properties have dissimilar mean residence times (MRT) inside the systems and (2) blend ingredients with different mechanical properties travel at different speed inside of continuous Blending systems. Results further indicated there were two critical mean residence times (MRTs): that of the tracer and that of the bulk. Matching of material properties between tracers is key in order to obtain similar MRTs using a given tracer. Differences between selected tracer and bulk material properties were found to lead to differences between the bulk space time and the tracer MRT. A set of recommendations on how to select tracer materials that would help characterize accurately the RTD of a continuous flow system are presented.

  • Improving Continuous Powder Blending Performance Using Projection to Latent Structures Regression
    Journal of Pharmaceutical Innovation, 2013
    Co-Authors: Fani Boukouvala, Fernando J Muzzio, William E. Engisch, Wei Meng, Marianthi G. Ierapetritou
    Abstract:

    Purpose There has been increasing interest in the last few years especially within the pharmaceutical industry towards continuous Powder Blending. In this paper, the effects of different design and operating parameters are investigated, which include blade speed, shaft angle, weir height, fill level, blade angle, and blade width. Method The projection to latent structures regression is introduced to elucidate the significance of these factors on the two key indices of continuous Blending performance, the local Blending rate and the mean axial velocity. Results Shaft angle and blade speed are the two most influential factors pointing to a Blending improvement strategy. The proposed strategy is examined using an experimental setup for the production of pharmaceutical Powder mixtures.

  • Improving Continuous Powder Blending Performance Using Projection to Latent Structures Regression
    Journal of Pharmaceutical Innovation, 2013
    Co-Authors: Yijie Gao, Fernando J Muzzio, Fani Boukouvala, William E. Engisch, Wei Meng, Marianthi G. Ierapetritou
    Abstract:

    Purpose There has been increasing interest in the last few years especially within the pharmaceutical industry towards continuous Powder Blending. In this paper, the effects of different design and operating parameters are investigated, which include blade speed, shaft angle, weir height, fill level, blade angle, and blade width.

  • scale up strategy for continuous Powder Blending process
    Powder Technology, 2013
    Co-Authors: Fernando J Muzzio, Marianthi G. Ierapetritou
    Abstract:

    Abstract Continuous Powder mixing has attracted a lot of interest within the pharmaceutical industry. Much work has been done recently that targets the characterization of continuous Powder mixing. In this paper, a quantitative scaling up strategy is introduced that allows the transition from lab to industrial scale. The proposed methodology is based on the variance spectrum analysis, and the residence time distribution, which are key indexes in capturing scale-up of the batch-like mixing, and scale-up of the axial mixing and motion, respectively. Our simulation results are used as preliminary guidance for scaling up different Powder mixing cases.