Scale Up Optimization Using Simulation Experiments
Moshe Ben Tollila
Ron Kenett
Simona Malca
Roberto Novoa
Benny Yoskovitch
Scale up of chemical processes is a unique challenge facing the chemical and pharmaceutical industry. In this work we have met this challenge by applying modern statistical methodology to simulation experiments using the DynoChem software. We demonstrate the approach using a real case example within limitations of IP protection considerations. In this project we use the TITOSIM software developed under an FP5 European project (Time to Market via Statistical Information Management, project number: GRD1-2000-25724).
The case study consists of an end product that is produced in a pilot plant through three steps from the raw material to the crystallized material. The paper relates to the first step only – the crude material. After research and development (R&D) completes product development, the product is manufactured at the pilot plant prior to being released for full scale production. At the pilot plant the reaction process is conducted in a small two liter reactor (RC1). The process parameters of this reaction are defined by R&D. In this project the pilot engineers performed initial measurements that were feed into chemical dynamic simulation software called DynoChem. These measurements are used to adjust various software parameters.
Using the simulation platform, a statistically designed simulation experiment was designed using TITOSIM and carried out using DynoChem. The results were analyzed using the MINITAB statistical package and optimization was carried using the TITOSIM software. The main outcome of the project was determining the conditions of full scale production under much larger reactors than the one used in the pilot plant.
The project, case study, is carry on in ChemAgis a subsidiary of Perrigo, Perrigo Israel Pharmaceuticals Ltd. As part of the continuous professionals' formation politics of our company ours engineers and operative personal have to permanent learn about causes and consequences of changes in process operational parameters, recipes and/or reactors and stirrer characteristics. All mentioned together is present in scale-up, scale-down challenge. Calculation and understanding every change by separate could be made individually following book indications. Scale-up (or down) is a very complex enterprise and, for to arrive an acceptable results, needs to be faced by an interdisciplinary team-work (as in the present) were technical, chemical process, chemistry, mathematical statistics, computation, and others knowledge are represented together with the experience of each individual work environment. As a result of the team-work we arrive at the desired result and at the same time every participant and their collaborators update his knowledge in a large spectrum of related sciences and arts.
We will present the results of this scale up exercise and discuss the significant implications of relying on simulation experiments. In particular we will demonstrate gains in time and product quality.
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