(723f) Effect of Material Properties on the Mass Hold up Dynamics and Residence Time Distribution in Continuous Powder Blenders

Escotet-Espinoza, M. S., Rutgers, The State University of New Jersey
Ierapetritou, M., Rutgers, The State University of New Jersey
Oka, S., Rutgers, The State University of New Jersey
D. Román-Ospino, A., Rutgers, The State University of New Jersey
Muzzio, F., Rutgers, The State University of New Jersey
Moghtadernejad, S., Rutgers University
Pharmaceutical research development has focused in characterizing blender performance using a formulation based approach. This approach consists on studying blender performance for a specific blend (e.g., mixture of excipients, lubricant, and API) and a desired process flow rate [1-4]. Although efficient for the early stages of continuous manufacturing, this approach does not provide process developers with sufficient information to ensure process performance on instances where process throughput and/or formulation fractions – due to dosing changes – vary from the ones measured during characterization. The formulation based approach, although effective for the specific product used for development, does not provide a vast amount of information that can be used to design new processes for new formulations. For these reasons, we performed an experiment to develop a correlation between incoming material properties and the mixing behavior in a continuous tubular blender. As a result, we developed a model to predict blender performance metrics such as mass hold up and mixing behavior using process parameters and material properties as model inputs.

The new paradigm focuses on characterizing the blender using pharmaceutically relevant materials that span a large range of material properties. The objective is not to develop a specific blend of material, but to understand how do blender process outputs (e.g., mass hold up, residence time, and flow rate out) are affected when material properties change. To establish the largest range of material properties, we evaluated our in-house material property database containing twenty-five (25) different materials using a statistical method for orthogonal transformation, known as Principal Component Analysis. Out the twenty-five (25) possible materials available to us, eight (8) were found to have a unique set of material properties. All 8 materials were run individually through a GEA continuous convective blender. Each material was fed individually to reduce the effects of changing material properties due to mixing. The effect of impeller speed and total mass flow rate were investigated along with the effect of material properties. The study was performed using a 3x2x8 experimental design for the blade speed, mass flow rate, and materials, respectively; yielding a total of 48 experiments. In each experiment, the mass flow rate out of blender was dynamically monitored over time by placing a weight scale at the blender outlet. Using the information from the feeders coupled with the blender and the outgoing flow rate, the mass hold up was computed dynamically. Mass hold up transitions between impeller speeds and mass flow rates were also investigated at all conditions for all eight materials. From the results provided, we developed a model to calculate mass hold up dynamically as a function of material properties.

Besides the mass hold up inside of the blender, we also investigated the effect of material properties on the mixing behavior of the unit. Residence time distribution (RTD) has been shown to be a powerful tool for understanding and characterizing the mixing behavior inside of continuous powder blenders [5-7]. RTD is defined as the distribution of time a material stays inside a unit operation in a continuous flow system [8]. In the context of continuous blenders, RTD enables the understanding of material flow profiles inside the blender (i.e., mixing and dispersion), which can be used to determine the blender’s ability to filter incoming noise from unit operations upstream. RTDs are also an integral piece in the development of control strategies for a specific unit operation and operations in series. The RTD profile of the blender was investigated for the eight materials by using a pulse experiments. In each pulse experiment, a known amount of tracer was introduced at the process’s steady state while monitoring the tracer’s concentration at the blender output over time. The effects of impeller speed, blade configuration, and mass flowrate on the RTD of continuous blenders have been examined for a variety of convective blending systems [7, 9]. Nevertheless, the role of material properties on RTD parameters, remains poorly understood.

The mixing behavior in the GEA blender was characterized by using a modified version of the Tank-in-Series RTD model. The modification of the Tanks-in-Series model included a delay time associated with the transport of powder inside of the convective blender. For each of the eight (8) material, a pulse of tracer material was introduced at each of the 3x2 experimental conditions – blade speed and flow rate – and the concentration of the tracer was measured dynamically at the blender’s outlet. For each of the tracer concentration profiles, time-constant parameters for the delay Tanks-in-Series RTD model were regressed. The RTD model constants fit were the number of tanks, mean residence time, and delay time. A correlation was developed between the model parameters, material properties, process parameters, and operating conditions. Each of those regressed constants were then correlated with the material properties, leading to a two (2) level model that allows to predict the residence time distribution of material in the system based on its properties. This material property correlation and empirical modeling strategies can enable savings in time and material in future process and product development, as well as improve our understanding of how material properties affect residence time in continuous tubular blenders. Tracer properties and its effect on RTD measurements are also briefly discussed.


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