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Chemical Synthesis Supported by Design of Experiments (DoE)


Peptide Synthesis is naturally subject to a wide range of influences, such as reaction temperature, solvent, catalyst, as well as concentrations of the substrate and reagent. As a result, the target output variables such as the product composition, purity, yield or stereospecificity may vary in wide range.

Rather than adopting a trial and error approach, whereby each parameter is examined on an individual basis and interactions between these parameters cannot be easily detected, in today's industry the statistical Design of Experiments (DoE) is generally applied. In order for the development based on the Design of Experiments (DoE) concept to be regarded as a success, it is essential that any experiments are performed within an accurately controlled framework under accurately maintained and reproducible conditions, thus enabling the target output variable (e.g. selectivity or yield) to reliably achieve its optimum value.

The requirements placed on the experiment setup and execution is therefore high and demands a high degree of flexibility, precision and reproducibility. A partially automated synthesis tool, such as EasyMax, provides the necessary support required for this application.

Didier Monnaie, from LONZA Peptide in Belgium, presents a highly complex application that illustrates the use of statistical methods together with the semi-automated lab reactor system EasyMax.
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