Publications

Authors: Wei Meng, Jakub Dvořák, Ravish Kumar, Rudy, Hofmeister,  František Štěpánek, Rohit Ramachandran, Fernando J.Muzzio

Paper Link: Link

Abstract: Over the past decade, continuous wet granulation has been emerging as a promising technology in drug product development. In this paper, the continuous high-shear mixer granulator, Lӧdige CoriMix® CM5, was investigated using a low-dose formulation with acetaminophen as the model drug. Design of experiments was deployed in conjunction with multivariate data analysis to explore the granulator design space and comprehensively understand the interrelation between process parameters and critical attributes of granules and tablets. Moreover, several complementary imaging techniques were implemented to unveil the underlying mechanisms of physical and chemical microstructure in affecting the tablet performance. The results indicated that L/S ratio and impeller speed outweighed materials feeding rate in modifying the granule and tablet properties. Increasing the degree of liquid saturation and mechanical shear input in the granulation system principally produced granules of larger size, smaller porosity, improved flowability and enhanced sphericity, which after compression generated tablets with slower disintegration process and drug release kinetics due to highly consolidated physical microstructure. Besides, in comparison to batch mixing, continuous mixing integrated with a conical mill enabled better powder de-agglomeration effect, thus accelerating the drug dissolution with increased surface area.

Authors: Yukteshwar Baranwal, Andrés D.Román-Ospino, Golshid Keyvan, Jung Myung Ha, Eon Pyo Hong, Fernando J.Muzzio, Rohit Ramachandran

Paper Link: Link

Abstract: This study describes how near infrared (NIR) spectroscopy can be used to predict the dissolution of bilayer tablets as a non-destructive approach. Tablets in this study consist of two active pharmaceutical ingredients (APIs) physically separated in layers and manufactured under three levels of hardness. NIR spectra were individually acquired for both layers in diffuse reflectance mode. Reference dissolution profile values were obtained using dissolution apparatus & HPLC. A multivariate partial least squares (PLS) calibration model was developed for each API relating its dissolution profile to spectral data. This calibration model was used to predict dissolution profiles of an independent test set and results of the prediction were compared using model free approaches i.e. dissimilarity (f1) & similarity (f2) factors to assure similarity in dissolution performance.

Authors: Subhodh Karkala, Nathan Davis, Carl Wassgren, Yanxiang Shi, Xue Liu, Christian Riemann, Gary Yacobian, and Rohit Ramachandran

Paper Link: Link

Abstract: This study tested the effectiveness of using dynamic yield strength (DYS) and shear-cell experiments to calibrate the following discrete-element-method (DEM) parameters: surface energy, and the coefficients of sliding and rolling friction. These experiments were carried out on cohesive granules, and DEM models were developed for these experiment setups using the JKR cohesion contact model. Parameter-sensitivity analysis on the DYS model showed that the DYS results in the simulations were highly sensitive to surface energy and were also impacted by the values of the two friction coefficients. These results indicated that the DYS model could be used to calibrate the surface energy parameter once the friction coefficients were fixed. Shear-cell sensitivity analysis study found that the influence of surface energy on the critical-state shear value cannot be neglected. It was inferred that the shear-cell model has to be used together with the DYS model to identify the right set of friction parameters. Next, surface energy was calibrated using DYS simulations for a chosen set of friction parameters. Calibrations were successfully conducted for simulations involving experimentally sized particles, scaled-up particles, a different shear modulus, and a different set of friction parameters. In all these cases, the simulation DYS results were found to be linearly correlated with surface energy and were within 5% of the experimental DYS result. Shear-cell simulations were then used to compare calibrated surface-energy values for the scaled-up particles with the experimentally sized particles. Both the simulations resulted in similar critical-state shear values. Finally, it was demonstrated that a combination of DYS and shear-cell simulations could be used to compare two sets of friction parameters and their corresponding calibrated surface energy values to identify the set of parameters that better represent the flow behavior demonstrated by the experimental system.

Authors: Nirupaplava Metta, Michael Ghijs, Elisabeth Schäfer, Ashish Kumar, Philippe Cappuyns, Ivo Van Assche,Ravendra Singh, Rohit Ramachandran, Thomas De Beer,Marianthi Ierapetritou, and Ingmar Nopens

Paper Link: Link

Abstract: In view of growing interest and investment in continuous manufacturing, the development and utilization of mathematical model(s) of the manufacturing line is of prime importance. These models are essential for understanding the complex interplay between process-wide critical process parameters (CPPs) and critical quality attributes (CQAs) beyond the individual process operations. In this work, a flowsheet model that is an approximate representation of the ConsiGma TM -25 line for continuous tablet manufacturing, including wet granulation, is developed. The manufacturing line involves various unit operations, i.e., feeders, blenders, a twin-screw wet granulator, a fluidized bed dryer, a mill, and a tablet press. The unit operations are simulated using various modeling approaches such as data-driven models, semi-empirical models, population balance models, and mechanistic models. Intermediate feeders, blenders, and transfer lines between the units are also simulated. The continuous process is simulated using the flowsheet model thus developed and case studies are provided to demonstrate its application for dynamic simulation. Finally, the flowsheet model is used to systematically identify critical process parameters (CPPs) that affect process responses of interest using global sensitivity analysis methods. Liquid feed rate to the granulator, and air temperature and drying time in the dryer are identified as CPPs affecting the tablet properties.

Authors: Nirupaplava Metta, Rohit Ramachandran & Marianthi Ierapetritou

Paper Link: Link

Abstract: Particle breakage in milling operations is often modeled using population balance models (PBMs). A discrete element method (DEM) model can be coupled with a PBM in order to explicitly identify the effect of material properties on breakage rate. However, the DEM-PBM framework is computationally expensive to evaluate due to high-fidelity DEM simulations. This limits its application in continuous process modeling for dynamic simulation, optimization, or control purposes.MethodsThe current work proposes the use of surrogate modeling (SM) techniques to map mechanistic data obtained from DEM simulations as a function of processing conditions. To demonstrate the benefit of the SM-PBM approach in developing integrated process models for continuous pharmaceutical manufacturing, a comill-tablet press model integration utilizing the proposed framework is presented.ResultsThe SM-PBM approach is in excellent agreement with the DEM-PBM approach to predict particle size distributions (PSDs) and dynamic holdup, with a maximum sum of square errors of 0.0012 for PSD in volume fraction and 0.93 for holdup in grams. In addition, the time taken to run a DEM simulation is in the order of days whereas the proposed hybrid model takes few seconds. The SM-PBM approach also enables comill-tablet press model integration to predict tablet properties such as weight and hardness.ConclusionsThe proposed hybrid framework compares well with a DEM-PBM framework and addresses limitations on computational expense, thus enabling its use in continuous process modeling.

Authors: Wei Meng, Andrés D.Román-Ospino, Savitha S.Panikar, Chris O’Callaghan, Sean J.Gilliam, Rohit Ramachandran, Fernando J.Muzzio

Paper Link: Link

Abstract: Process analytical technologies (PAT) are identified as an essential element in the Quality by Design framework, providing the cornerstone to implement continuous pharmaceutical manufacturing. This study is concerned with employing three in-line PATs: Eyecon™ 3D imaging system, Near-infrared spectroscopy (NIRS) and Raman spectroscopy (RS), in a continuous twin-screw granulation process to enable real-time monitoring and prediction of critical quality attributes of granules. The Thermo Scientific™ Pharma 11 twin-screw granulator was used to manufacture granules from a low-dose formulation with caffeine anhydrous as the model drug. A 30-run full factorial design including three critical process parameters (liquid to solid ratio, barrel temperature and throughput) was conducted to evaluate the performance of each analytical tool. Eyecon™ successfully captured the granule size and shape variation from different experimental conditions and demonstrated sufficient sensitivity to the fluctuation of size parameter D10 in the presence of process perturbations. The partial least square regression (PLSR) models developed using NIRS showed small relative standard error of prediction values (less than 5%) for most granule physical properties. In contrast, the RS-based PLSR models revealed higher prediction errors towards granule drug concentration, potentially due to the inhomogeneous premixing of raw materials during calibration model development.

Authors: Ashutosh Tamrakar, Rohit Ramachandran

Paper Link: Link

Abstract: In pharmaceutical manufacturing, fluidized bed granulation is one of the common processing options available to achieve better flowability of powders through size enlargement of primary particles. In fact over the last 50 years, various fluidized bed operations including freezing, drying, impregnation, coating, etc. have become a common place in the chemical processing industry due to the high level of contacts between fluids and solids attainable in a fluid bed system. These complex interactions between the fluid and particles also mean that simulating fluidized beds are still a challenging endeavor. Generally, Computational Fluid Dynamics (CFD) packages are employed to model the pressure drops in fluids; however, the presence of high concentration of solids and the complexity of granulation behavior require more advanced particle models than are available with CFD software. As a result, coupled frameworks that utilize the strength of particulate simulations such as Discrete Element Method (DEM) and bulk granulation modeling such as Population Balance Model (PBM) in conjunction with CFD information are the next steps to developing practical fluid bed granulation models.