Unit Operations - Real World Applications

Session Chair & Co-Chair:

• Frank Zeng, Baxter Healthcare Corporation
• A.J. Howes, Afton Chemical

Session Description:

Unit operations are the building blocks of the process industry, ranging from transport, to mixing, to separation, to reaction. The presentations in this session describe key aspects of the development, scale-up, and commercialization of industrially relevant unit operations. Critical to their success is the determination of process parameter operating ranges, as well as design, validation, trouble-shooting, and de-bottlenecking to improve the performance, reliability and throughput.

Schedule:

Designing Liquid-Liquid Extraction Columns by Pilot Plant Testing

Almost every liquid-liquid extraction (LLE) project involves a pilot test to provide the basis for commercial plant design.  Unlike distillation, which can often be design by simulations and known capacity/efficiency parameters for column internals, LLE usually has many unknown factors such as equilibrium, efficiency, and capacity data.  Small trace impurities can have a significant impact on all of the above.  The development procedure for LLE generally requires three basic steps; (1) solvent selection and generation of liquid-liquid equilibrium data, (2) column selection and pilot plant testing to generate the optimal performance data, and (3) accurate scale-up technique to design the production scale equipment.  As the diameter of an LLE column increases the tendency for back mixing increases resulting in lower efficiency.  Thus, a key for scale-up from the pilot plant test work to the production column is to understand how the efficiency changes with diameter and to correlate this into the design of the production column.  Over years of experience with many different LLE systems, proven scale up correlations have been developed for a number of different types of extraction columns and used for the design of production columns which have met or exceeded expectations.  This presentation will conclude by presenting case studies for two extraction processes including data generated in the pilot plant and then calculations for sizing the production columns.

The Fast Track for Chemical Process Development:
Brains + Experiments + Models = Success

Successful process development and scale-up is hard work.  How can you get more value from your lab experiments and pilot plant runs?  How can you ensure your scale-up will go well? 

We outline a development and scale-up strategy that combines mechanistic thinking, experiments and modeling.  Scientists and engineers at companies around the world routinely apply this approach to work together more effectively; to improve technology exchange within their organizations and with contract research and manufacturing organizations; to design fewer, better experiments; and to scale-up to kilo lab, pilot plant and full-scale manufacturing successfully.  We will present case studies spanning unit operations including chemical reactions, crystallization, solvent exchange and solid-liquid separation to illustrate the strategy and benefits attained.

Filtration and Drying Operations: Experimental and Modeling Techniques to Preserve Particle Properties Upon Scale-up to Agitated Filter Driers (AFD’s)

Agitated Filter Driers (AFD’s) are commonly used in pharmaceutical manufacturing for performing both filtration and drying operations.  Common challenges for scale-up include balling and agglomeration, avoiding grinding or attrition of particles during agitation, preserving the desired crystalline form such as a hydrate, as well as managing the drying time.  Preserving particle attributes of the API is required for a robust process and to ensure batch-to-batch quality of the product is consistently met.  Laboratory tools and techniques are employed to characterize propensity for agglomeration and attrition. Modeling tools are employed to understand drying times and to develop optimal process conditions including design of an effective stirring protocol.  The focus of this presentation will be to describe our laboratory predictive tools, process modeling, and scale-up.