Last year the Nobel Prize for Chemistry was granted to scientists, who were modeling physico-chemical interactions in biochemistry. Although we are modeling since 1985, the recognition of the importance of modeling for the whole Life Science is a great motivation for the Molnar-Institute to continue in finding the best column and the best separation in HPLC, by modeling a large number of possible chromatograms. It is 40 years ago, that Csaba Horváth discovered in 1975 the reason for the success of Reversed Phase Chromatography at Yale – changes in the structure of water as part of the eluent. Complex calculations were required, but computers were just starting to emerge. He used a PDP11 “cabin” to describe, how acids dissociation might be modeled by equations. Today we are modeling separation choices in a multi-variable Design Space to the most robust separation for industrial drug production. The talk will demonstrate on case studies, how modeling software can work together with modern instruments to produce the best separation instead in months in only as fast as in a few hours. With a computer generated separation model at hand, one can calculate the influence of various experimental parameters on the separation and, therefore, also model the robustness of a separation. This is extremely useful if a method should be used for a long time where one has to take into account day-to-day variations in method conditions.
Presenting author:
Imre Molnár
Molnár-Institute for Applied Chromatography, Schneeglöckchenstr. 47, 10407 Berlin, Germany
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Authors:
Imre Molnár - Molnár-Institute for Applied Chromatography
Hans-Jürgen Rieger - Molnár-Institute for Applied Chromatography
