Combining Chemometric Models with Adsorption Isotherm Measurements to Study Omeprazole in RP-LC

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• 作者：Dennis Åsberg ; Marek Leśko ; Jörgen Samuelsson ; Anders Karlsson…
• 关键词：Liquid chromatography ; pH ; Adsorption isotherm ; Design of experiments ; Omeprazole
• 刊名：Chromatographia
• 出版年：2016
• 出版时间：October 2016
• 年：2016
• 卷：79
• 期：19-20
• 页码：1283-1291
• 全文大小：749 KB
• 刊物类别：Chemistry and Materials Science
• 刊物主题：Chemistry
  Analytical Chemistry
  Organic Chemistry
  Pharmacy
  Biochemistry
  Plant Sciences
  Measurement Science and Instrumentation
  
• 出版者：Vieweg Verlag
• ISSN：1612-1112
• 卷排序：79

文摘

The adsorption of the proton-pump inhibitor omeprazole was investigated using RP-LC with chemometric models combined with adsorption isotherm modelling to study the effect of pH and type of organic modifier (i.e., acetonitrile or methanol). The chemometric approach revealed that omeprazole was tailing with methanol and fronting with acetonitrile along with increased fronting at higher pH. The increased fronting with higher pH for acetonitrile was explored using a pH-dependent adsorption isotherm model that was determined using the inverse method and it agreed well with the experimental data. The model indicated that the peaks exhibit more fronting at high pH due to a larger fraction of charged omeprazole molecules. This model could accurately predict the shape of elution profiles at arbitrary pH levels in the studied interval. Using a two-layer adsorption isotherm model, the difference between acetonitrile and methanol was studied at the lowest pH at which almost all omeprazole molecules are neutral. Omeprazole had adsorbate–adsorbate interactions that were similar in strength for the acetonitrile and methanol mobile phases, while the solute–adsorbent interactions were almost twice as strong with methanol. The difference in the relative strengths of these two interactions likely explains the different peak asymmetries (i.e., tailing/fronting) in methanol and acetonitrile. In conclusion, thermodynamic modelling can complement chemometric modeling in HPLC method development and increase the understanding of the separation.