Quantitative Structure Retention Relationship Models in an Analytical Quality by Design Framework: Simultaneously Accounting for Compound Properties, Mobile-Phase Conditions, and Stationary-Phase Properties

2013 ◽  
Vol 52 (35) ◽  
pp. 12269-12284 ◽  
Author(s):  
Koji Muteki ◽  
James E. Morgado ◽  
George L. Reid ◽  
Jian Wang ◽  
Gang Xue ◽  
...  
Keyword(s):  
Stationary Phase ◽  
Mobile Phase ◽  
Quality By Design ◽  
Design Framework ◽  
Quantitative Structure ◽  
Analytical Quality ◽  
Structure Retention ◽  
Quantitative Structure Retention Relationship ◽  
Phase Properties

scholarly journals Optimization of chromatographic separation of aripiprazole and impurities: Quantitative structure-retention relationship approach

2021 ◽  
pp. 92-92
Author(s):  
Bojana Svrkota ◽  
Jovana Krmar ◽  
Ana Protic ◽  
Mira Zecevic ◽  
Biljana Otasevic
Keyword(s):  
Flow Rate ◽  
Mobile Phase ◽  
Gradient Elution ◽  
Response Surfaces ◽  
Quantitative Structure ◽  
Optimization Strategy ◽  
Mobile Phase Flow Rate ◽  
Torsion Energy ◽  
Structure Retention ◽  
Quantitative Structure Retention Relationship

New optimization strategy based on mixed Quantitative Structure-Retention Relationship (QSRR) model was proposed for improving the RP-HPLC separation of aripiprazole and its impurities (IMP A-E). Firstly, experimental parameters (EPs) (mobile phase composition and flow rate) were varied according to Box-Behnken Design and afterwards, artificial neural network (ANN) as QSRR model was built correlating EPs and selected molecular descriptors (ovality, torsion energy and non-1,4-Van der Waals energy) with analytes log-transformed retention time. Values of root mean square error (RMSE) were used for ANNs quality estimation (0.0227, 0.0191 and 0.0230 for training, verification and test set, respectively). Separations of critical peak pairs on chromatogram (IMP A-B and IMP D-C) were optimized using ANNs for which EPs served as inputs and log-transformed separation criteria s as outputs. They were validated applying leave-one-out cross-validation (RMSE values 0.065 and 0.056, respectively). Obtained ANNs were used for plotting response surfaces upon which analyses chromatographic conditions resulting in optimal analytes retention behaviour and optimal values of separation criteria s were defined and they comprised of 54 % of methanol at the beginning and 79 % of methanol at the end of gradient elution programme with mobile phase flow rate of 460 ?L min-1.

Ionic Liquids as Novel Solvent Additives to Separate Peptides

2006 ◽  
Vol 61 (11-12) ◽  
pp. 827-832 ◽  
Author(s):  
Tomasz Bączek ◽  
Barbara Sparzak
Keyword(s):  
Ionic Liquid ◽  
Ionic Liquids ◽  
Thin Layer ◽  
Mobile Phase ◽  
Analytical Approach ◽  
Quantitative Structure ◽  
Methyl Sulfate ◽  
Liquid Content ◽  
Structure Retention ◽  
Layer Chromatography

Abstract A novel analytical approach involving the addition of an ionic liquid into the mobile phase of the thin-layer chromatography (TLC) system during the optimization of chromatographic separation of peptides was demonstrated. Different behavior of peptides in the TLC sytem was observed after the addition of 1,3-dimethylimidazolium methyl sulfate to the eluent in comparison to the system without the ionic liquid. The objective of the work was to study the effect of the addition of different contents of ionic liquid to the mobile phase comprising mostly water and to observe the behavior of peptides’ retention. The potential usefulness of environmentally friendly ionic liquids for the optimization of separation of peptides was demonstrated. An increase of Rf values was observed with increasing the ionic liquid content in the mobile phase. The benefits of the used approach were related to the separation achieved. Finally, quantitative structure-retention relationships (QSRR) were used for the studies on the predictions of peptides’ retention in the TLC systems with the addition of ionic liquid in terms of the predictions performed recently in HPLC systems.

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