454184 Modeling and Simulation Efforts in Scale up of Sustained Release Microspheres

Monday, November 14, 2016
Grand Ballroom B (Hilton San Francisco Union Square)
Rishi Mehan, SVB Janardhan Garikipati, Birendra K. David, Yash Partani and RaviChandra Palaparthi, Modelling and Simulations Group, IPDO, Dr Reddys Laboratories, Hyderabad, India


Generic pharmaceutical industry has to operate in tight timelines of product development and scale up from lab to plant. To meet such needs, Dr Reddys Laboratories use approaches like modeling and simulation for better process understanding and to reduce scale up risks. This presentation provides example cases of such efforts in a microspheres product.

Microencapsulation process development demands understanding of the impacts of various material properties and process parameters to achieve the right product characteristics. Employing appropriate modeling approaches at different scales can aid in developing this understanding. In this work, a first principle based diffusion model which uses Monte Carlo simulation helps link the impact of microsphere product attributes like size distribution, porosity, and polymer properties on the sustained release of drug from microspheres.[1] Results from a numerical simulation of this model gauge the risk of each of the product characteristics on the release. This understanding identifies the key product attributes to focus on and manipulate with the process conditions.

Manufacture of such micro-encapsulated products consists of multiple unit operation steps like phase separation, extraction and drying to get the desired product characteristics. A combination of first principle, and CFD based approaches for the unit operations links how each of the process steps impacts the product attributes. Some of the important linkages made include scale dependent variations of: mixing conditions on particle size using vessel averaged Reynolds and Weber number obtained from CFD simulations; cycle times for extractions by single particle spherical diffusion model; and drying cycle predictions by first principle discrete element model with mixing simulated by randomization of the discrete elements. Custom lab scale experimentation provides the necessary model parameters and enables extension of the understanding towards the plant scale. This provides the necessary framework for a successful scale-up.

[1] J. Siepmann, N. Faisant, J.P. Benoit, A new mathematical model quantifying drug release from bioerodible microparticles using Monte Carlo simulations, Pharm.Res. 19 (2002) 1885–1893.

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