Open AccessOptimization of chromatographic separation of aripiprazole and impurities: Quantitative structure-retention relationship approach
Author(s) -
Bojana Svrkota,
Jovana Krmar,
Ana Protić,
Mira Zečević,
Biljana Otašević
Publication year - 2022
Publication title -
journal of the serbian chemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.227
H-Index - 45
eISSN - 1820-7421
pISSN - 0352-5139
DOI - 10.2298/jsc210709092s
Subject(s) - chromatography , analyte , methanol , chemistry , elution , mean squared error , quality by design , chromatographic separation , volumetric flow rate , artificial neural network , high performance liquid chromatography , analytical chemistry (journal) , mathematics , computer science , thermodynamics , statistics , artificial intelligence , physics , organic chemistry , particle size
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.