Mechanistic Model Development & Validation of Particulate Processes

Here, we seek to develop mechanistic and predictive models particulate processes such as granulation, mixing and milling. We are working develop sub-models (kernels) that describe the dynamics as a function of key material properties and process parameters. The models are validated against experimental data at the lab-scale and are tested for their predictive capability. Such validated models are able to reduce the time and cost associated with tedious experimental trials. 

Batch Processes

Continuous Processes

Multi-dimensional PBM Simulation from Graphical User Interface

List of Publications from this Research Area:

• A. Chaudhury, A. Tamrakar, M. Schongut, D.  Smrcka, F. Stepanek, R. Ramachandran. Multi-dimensional population balance model development and validation of reactive granulation processes.Industrial & Engineering Chemistry Research , 54 (3), 842-857, 2015.

• D. Barrasso, A. El Hagrasy, J.D. Litster, R. Ramachandran. Multi-dimensional population balance model development and validation for a twin screw granulation process, Powder Technology, 270 B, 612-621, 2015.

• M. O. Besenhard, A. Chaudhury, T. Vetter, R. Ramachandran, J. Khinast. Evaluation of parameter estimation methods for crystallization processes modeled via population balance equations. Chemical Engineering Research & Design, 94, 275-289, 2015.

• A. Chaudhury, M. E. Armenante and R. Ramachandran. Compartment based  population balance modeling of a high shear wet granulation process using  data analytics.  Chemical Engineering Research & Design, 95, 211-228, 2015.

• M. Sen, A. Chaudhury. R. Singh, R.  Ramachandran. Two-dimensional population balance development and validation  of a pharmaceutical crystallization process. American Journal of Modern Chemical Engineering, 1, 3-29 , 2014.

• A. Chaudhury, D. Barrasso, P. Pandey, H. Wu, R. Ramachandran. Population balance model development, validation and prediction of CQAs of a high-shear wet granulation process: Towards QbD in drug product pharmaceutical manufacturing, Journal of Pharmaceutical Innovation, 9 (1), 53-64, 2014.

• A. Chaudhury, H. Wu, M. Khan, R. Ramachandran. A mechanistic population balance model for granulation processes: Effect of process and formulation parameters,  Chemical Engineering Science, 107, 76-92, 2013.

• D. Barrasso, S. Oka, A. Muliadi, J.D. Litster, C. Wassgren and R. Ramachandran. Population balance model validation and prediction of CQAs for continuous milling processes: toward QbD in pharmaceutical drug product manufacturing. Journal of Pharmaceutical Innovation, 8(3), 147-162, 2013. 

• D. Barrasso, S. Walia, R. Ramachandran. Multi-component population balance modeling of continuous granulation processes: a parametric study and comparison with experimental trends. Powder Technology, 241, 85-97, 2013.

• A. Chaudhury and R. Ramachandran. Integrated population balance model development and validation of a granulation process. Particulate Science & Technology, 31(4), 407-418, 2013.

• A. Chaudhury, A. Niziolek and R. Ramachandran. Multi-dimensional mechanistic modeling of fluid-bed granulation processes: an integrated approach. Advanced Powder Technology, 113-131, 24, 2013. 

• M. Sen and R. Ramachandran. A Multi-dimensional Population Balance Model Approach to Continuous Powder Mixing Processes. Advanced Powder Technology, 51-59, 24, 2013. 

• M. Sen, R. Singh, A. Vanarase, J. John and R. Ramachandran. Multi-dimensional population balance modeling and experimental validation of continuous powder mixing processes. Chemical Engineering Science, 80, 349-360, 2012. 

• P. Pandey, J. Tao, A. Chaudhury, R. Ramachandran, J.Z. Gao, D. Bindra. A combined experimental and modeling approach to study the effects of high-shear wet granulation process parameters on granule characteristics.Pharmaceutical Development & Technology, 18, 210-224, 2012. 

• R. Ramachandran, M. Ansari, A. Chaudhury, A. Kapadia, A. V. Prakash and F. Stepanek. A quantitative assessment of the influence of primary particle size distribution on granule inhomogeneity. Chemical Engineering Science, 104-110, 71, 2012. 

• R. Ramachandran and A. Chaudhury. Model-based Design and Control of Continuous Drum Granulation Processes. Chemical Engineering Research & Design, 90, 1063-1073, 2012. 

• F. Boukoulava, A. Dubey, A. Vanarase, R. Ramachandran, F.J. Muzzio and M.I. Ierapetritou. Computational approaches for studying the granular dynamics of continuous blending processes: Population Balance and Data based methods. Macromolecular Materials and Engineering, 296, 9-19, 2012.