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Scientist Working with Kinetics

Kinetic Models can be developed from targeted experimental programs or with DoE studies. With a good kinetic model, conditions for improved process performance and potential scaling problems can be quickly identified. DynoChem enables users to save time and material and the ability to add value to your work by developing transferable process understanding.

Users describe DynoChem as the Gold Standard for kinetic modelling in their company. DynoChem is provided with many easy-to-customise template models for a range of reaction types, which lab data can quickly be added to. Automated fitting algorithms are used to fit experimental data to user-proposed reaction schemes. Optimisation and in-silico DoE tools enable the best reaction conditions to be quickly identified.

For example, a user recently presented a case of API synthesis with a parallel reaction that formed impurities in excess. By using DynoChem the development team were able to optimise the process to:

  • Identify the optimal reaction temperature profile
  • Find the best reagent concentration level
  • Reduce reaction time by 8 hours
  • Increase product yield
  • Stop the formation of one impurity
  • Reduce the formation of another impurity to within acceptable limits
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Relevant Customer Publications

"Kinetic Studies in Microreactors – Requirements for Reliable Data and Successful Reactor Scale-up", Mannheim University of Applied Sciences (2014)

"Kinetic Investigation of an SnAr Reaction", AstraZeneca (2011)

"A Data Driven Model Based Approach to Scale Up of Hydrogenation Reactions in the API Industry", Pfizer (2011)

"Using DynoChem to determine a suitable sampling endpoint for reaction analysis in a DoE", Wyeth (2009)