Multilinear gradient elution optimisation in reversed-phase liquid chromatography using genetic algorithms

Nikitas, P.; Pappa-Louisi, A.; Agrafiotou, P.

doi:10.1016/j.chroma.2006.01.005

Cited by 49 publications

(31 citation statements)

References 21 publications

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“…Figure 4 shows a chromatogram of 18 underivatized amino acids and related compounds recorded by using three detectors in series and under optimal gradient conditions found in the ref. [32]. The MeCN gradient profile used is shown in the UV detected chromatogram (Fig.…”

Section: Resultsmentioning

confidence: 99%

Direct RP‐HPLC determination of underivatized amino acids with online dual UV absorbance, fluorescence, and multiple electrochemical detection

Agrafiotou

Sotiropoulos

Pappa-Louisi

2009

J of Separation Science

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Original PaperDirect RP-HPLC determination of underivatized amino acids with online dual UV absorbance, fluorescence, and multiple electrochemical detectionThe combined use of a dual-UV detector, a fluorimetric one and of a multiple electrochemical (EC) detector equipped with a dual electrode, consisting of a conventional size 3 mm diameter glassy carbon electrode (GCE) and of a pair of 30 lm thick carbon microfibers, is proposed for the determination of 15 amino acids, two dipeptides and creatinine. This online coupling of the above detection modes could partially replace amino acid analysis by derivatization methods, since it solves problems concerning the direct detection of selected underivatized amino acids. Additionally, it was proved that the use of multiple-detection allows positive peak identification in a single chromatographic run, yields more information for free amino acids and solves in some cases the problem of chromatographic resolution. In order to optimize the detection conditions of the underivatized amino acids and related compounds by different detectors, their detection characteristics were determined by adequate preliminary experiments. The electro-oxidation characteristics of the underivatized compounds of interest were determined by hydrodynamic voltammetry using a flow cell with a macrodisc GCE and by ex-situ voltammetry using both a GCE of conventional size and a carbon fiber disk microelectrode. Important practical advantages of microfiber and microdisk electrodes with respect to macroelectrodes were demonstrated.Keywords: Dual electrode / Microdisc electrode / Multiple UV-fluorescence-electrochemical detection / Reversed phase liquid chromatography (RPLC) / Underivatized amino acids and related compounds /

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Section: Resultsmentioning

confidence: 99%

Direct RP‐HPLC determination of underivatized amino acids with online dual UV absorbance, fluorescence, and multiple electrochemical detection

Agrafiotou

Sotiropoulos

Pappa-Louisi

2009

J of Separation Science

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“…In 2006, Nikitas and coworkers reported on the use of Genetic Algorithms to optimize multi-linear gradients [20,21]. However, this optimization approach requires a priori selection of initial parameters such as the number of generations, the population size and the probability of mutation [20]. Concha-Herrara and coworkers investigated the benefit of including more and more segments using a time consuming grid search as optimization strategy.…”

Section: Introductionmentioning

confidence: 99%

“…This software combines chromatogram simulation and fast Monte-Carlo optimization to optimize multi-linear gradients [19]. In 2006, Nikitas and coworkers reported on the use of Genetic Algorithms to optimize multi-linear gradients [20,21]. However, this optimization approach requires a priori selection of initial parameters such as the number of generations, the population size and the probability of mutation [20].…”

Section: Introductionmentioning

confidence: 99%

“…The best "traditional" multi-segment gradient profile (determined by a starting composition 0 and a value for ˇ and t G for each segment) was determined via a similar grid search. Based on our own findings and these of Concha-Herrara et al [12], only 4-segment gradients were considered as these give the best compromise between the achievable selectivity (in gradient elution this is the ratio between the apparent gradient retention factors k eff,1 /k eff,2 [16][17][18][19][20][21][22][23][24][25][26][27]) and the required search time. The grid search was conducted considering different starting concentrations %B between 5 and 95% (step size of 0.5%) and a number of ˇ-and t G -values for each of the 4 segments (ˇ going from 0.001 to 0.2, corresponding to 0.1 to 20%B/min, i.e., ln(ˇ) between −6.9 and −0.70 and t G /t 0 between 1 and 12).…”

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confidence: 99%

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Enhanced selectivity and search speed for method development using one-segment-per-component optimization strategies

Tyteca

Vanderlinden

Favier

et al. 2014

Journal of Chromatography A

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a b s t r a c tLinear gradient programs are very frequently used in reversed phase liquid chromatography to enhance the selectivity compared to isocratic separations. Multi-linear gradient programs on the other hand are only scarcely used, despite their intrinsically larger separation power. Because the gradient-conformity of the latest generation of instruments has greatly improved, a renewed interest in more complex multisegment gradient liquid chromatography can be expected in the future, raising the need for better performing gradient design algorithms. We explored the possibilities of a new type of multi-segment gradient optimization algorithm, the so-called "one-segment-per-group-of-components" optimization strategy. In this gradient design strategy, the slope is adjusted after the elution of each individual component of the sample, letting the retention properties of the different analytes auto-guide the course of the gradient profile. Applying this method experimentally to four randomly selected test samples, the separation time could on average be reduced with about 40% compared to the best single linear gradient. Moreover, the newly proposed approach performed equally well or better than the multi-segment optimization mode of a commercial software package. Carrying out an extensive in silico study, the experimentally observed advantage could also be generalized over a statistically significant amount of different 10 and 20 component samples. In addition, the newly proposed gradient optimization approach enables much faster searches than the traditional multi-step gradient design methods.

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“…For example, Nikitas et al [7] optimized a stepwise gradient so as to maximize differences in retention time of different solutes. The same authors later generalized this optimization problem to multilinear elution and minimization of a predefined cost function [8]. Nonlinear gradient shapes were also considered.…”

mentioning

confidence: 99%

High Throughput Screening for the Design and Optimization of Chromatographic Processes: Automated Optimization of Chromatographic Phase Systems

et al. 2008

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Chromatographic processes can be optimized in various ways. However, the two most prominent approaches are either based on statistical data analysis or on experimentally validated simulation models. Both approaches heavily rely on experimental data, the generation of which usually imposes a significant bottleneck on rational process design. Hence, here a closed-loop optimization strategy is proposed in that an automated high throughput liquid handling platform is combined with a genetic algorithm. This setup enables process optimization on the mini-scale and thus saves time as well as material costs. The practicability and robustness of the proposed high throughput method is demonstrated with two exemplary optimization tasks: first, optimization of the buffer composition in the capture step for a binary protein mixture (lysozyme and cytochrome), and second, optimization of multilinear gradient elution for the separation of a ternary mixture (ribonuclease and cytochrome, and lysozyme). IntroductionChromatography is widely used as a separation technique in the biotechnological industry. High selectivity and gentle conditions have made it an essential step in current purification processes for biological macromolecules, for instance, proteins. However, due to complex and dynamic interactions between protein molecules and adsorbent materials, the design of optimal separation processes is very difficult and time consuming. Heuristic design methods that are based on previous experiences with similar separation problems require a great amount of expert knowledge and usually do not lead to the global process optimum. Furthermore, process optimization is often restricted by time-to-market requirements and must, hence, be performed as fast as possible.Most methods for process optimization that are found in the literature today divide into two classes: model-based optimization and direct process optimization. In model-based optimization, mathematical models are utilized to mimic the studied processes. Optimization is performed in-silico and thus has the clear advantage of not restricting the optimization by lab schedules. Limiting factors are only computational effort and reliability or validity of the applied simulation models. The development of mechanistic models requires good process understanding, initial experiments for parameter estimation, and independent experiments for model validation. The latter is also true for black box models (for example [1,2]). The determination of mechanistic model parameters, such as effective mass transfer coefficients and isotherm coefficients, is generally very complex and requires large amounts of material and time, especially when the interactions of realistic multi-component mixtures are considered without significant model simplifications.An alternative to the model-based approach is to directly identify process optima based on the results of experiments that are iteratively planned by an optimization algorithm, such as repeated design of experiments (DoE) or an evolutionary strat...

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Multilinear gradient elution optimisation in reversed-phase liquid chromatography using genetic algorithms

Cited by 49 publications

References 21 publications

Direct RP‐HPLC determination of underivatized amino acids with online dual UV absorbance, fluorescence, and multiple electrochemical detection

Direct RP‐HPLC determination of underivatized amino acids with online dual UV absorbance, fluorescence, and multiple electrochemical detection

Enhanced selectivity and search speed for method development using one-segment-per-component optimization strategies

High Throughput Screening for the Design and Optimization of Chromatographic Processes: Automated Optimization of Chromatographic Phase Systems

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