2000
DOI: 10.1081/jlc-100100475
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A Review of Criteria Functions and Response Surface Methodology for the Optimization of Analytical Scale HPLC Separations

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Cited by 49 publications
(25 citation statements)
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“…(ii) The chromatographic functions CRF [10][11][12][13], CRS [10,14], CEF [10,15,16], COF [10,17], ATR [18], Rp [19], and r [20] were calculated according to Eq. (5)- (10) within each group and used as a response in MODDE.…”
Section: Optimization Of Separationmentioning
confidence: 99%
See 1 more Smart Citation
“…(ii) The chromatographic functions CRF [10][11][12][13], CRS [10,14], CEF [10,15,16], COF [10,17], ATR [18], Rp [19], and r [20] were calculated according to Eq. (5)- (10) within each group and used as a response in MODDE.…”
Section: Optimization Of Separationmentioning
confidence: 99%
“…Furthermore, different strategies for optimization of the separation were investigated. The compounds were divided into five subgroups and each group was optimized separately by maximizing the selectivity of the critical peak pair using response surface plots in MODDE, by calculating the chromatographic response function (CRF) [10][11][12][13], chromatographic resolution statistic (CRS) [10,14], chromatographic exponential function (CEF) [10,[15][16], chromatographic optimization function (COF) [10,17], arcs tangens resolution (ATR) [18], resolution product (Rp) [19] and relative resolution product (r) [20], and by using the software DryLab  [21][22][23][24][25][26][27]. CRF, CEF, COF, ATR, and r have all been used for optimization of separation in electrodriven techniques.…”
Section: Introductionmentioning
confidence: 99%
“…High performance liquid chromatography represents nowadays the most widespread separation technique applied commonly in pharmacology, toxicology, clinical analysis as well as various research fields [1][2][3][4].…”
Section: Introductionmentioning
confidence: 99%
“…Methodologies such as response surface analysis (RSA) can help to visualize which are the main experimental variables affecting separation as well as the main interactions between the variables. It models the responses, finds the optimal combination of factors, and it can also predict the most suitable experimental conditions [19][20][21][22]. In the case of HAs, mobile phase pH and buffer composition have shown to be critical parameters for retention factor (k) [23] and, experimental design has also been used for optimization purposes [24].…”
Section: Introductionmentioning
confidence: 99%