2002
DOI: 10.1016/s0021-9673(02)00731-8
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Computerized design of separation strategies by reversed-phase liquid chromatography: development of DryLab software

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Cited by 180 publications
(83 citation statements)
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“…With the input data of training runs the software evaluates the resolution, R s , as a function of one or two chromatographic parameters for each peak pair. A "critical resolution map" is produced by plotting smallest value of resolution of any two critical peaks as a function of one or two varied experimental parameters revealing not only the optimum chromatographic conditions but also the robust regions of an HPLC method [43].…”
Section: Optimization Of Hplc Methodsmentioning
confidence: 99%
“…With the input data of training runs the software evaluates the resolution, R s , as a function of one or two chromatographic parameters for each peak pair. A "critical resolution map" is produced by plotting smallest value of resolution of any two critical peaks as a function of one or two varied experimental parameters revealing not only the optimum chromatographic conditions but also the robust regions of an HPLC method [43].…”
Section: Optimization Of Hplc Methodsmentioning
confidence: 99%
“…The development of gradient methods with conventional HPLC can be complex and often requires time-consuming gradient screens with computer-assisted development. Molnar discusses the general strategy for computer-supported gradient method development in DryLab [13].…”
Section: High Productivity Applicationsmentioning
confidence: 99%
“…(iii) The migration times were entered into the Drylab  program, and choosing the area with the highest resolution in the calculated 3-D resolution map optimized the separation [21][22][23][24]. The retention times or retention factors are adapted by a cubic fit (polynom containing linear and quadratic terms) to predict the 3-D resolution map [25][26][27].…”
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%