Use of DryLab for Simulation of TLC Separation and Method Transfer from TLC to HPLC

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1 Use of DryLab for Simulation of TLC Separation and Method Transfer from TLC to HPLC Tero Wennberg, Irena Vovk, Pia Vuorela, Breda Simonovska, and Heikki Vuorela* Key Words: TLC HPLC DryLab Optimization Method transfer Summary The computer-assisted simulation program DryLab has been used to simulate TLC separations. The simulations were based on data from preliminary TLC separations. For DryLab data entry R F values from TLC were converted to retention times, the development distance on the plate was used as column length, and the plate thickness was used as the column diameter. To achieve reasonably accurate simulations it was found necessary to run three preliminary runs in which differences between organic modifier concentration in two adjacent runs was more than 5%. The possibility of predicting HPLC separation on the basis of TLC separations was also studied. It was found that the method can be transferred from TLC to HPLC and that DryLab can be used to predict HPLC separation on the basis of the information obtained from TLC experiments. To produce a reasonably accurate HPLC simulation on the basis of TLC data, however, a relatively large number of preliminary experiments is required. 1 Introduction Thin layer chromatography (TLC), a qualitative and quantitative analytical method, has traditionally also been used as a pilot technique for high-performance liquid chromatography (HPLC). TLC has been regarded as a suitable pilot technique for mobile phase or adsorbent optimization because it is more flexible, quicker, and cheaper than column techniques [1]. By use of T. Wennberg and H. Vuorela, Division of Pharmaceutical Biology, Faculty of Pharmacy, P.O. Box 56, FIN University of Helsinki, Helsinki, Finland; and I. Vovk and B. Simonovska, National Institute of Chemistry, Laboratory for Food Chemistry, Hajdrihova 19, SI-1000 Ljubljana, Slovenia; P. Vuorela, Department of Biochemistry and Pharmacy, Åbo Akademi University, BioCity, FIN Turku, Finland. TLC several systems can be checked simultaneously without the use of expensive equipment. It is also possible to optimize the mobile phase by using a Vario chamber (Camag), which enables simultaneous development with six different solvents side-by-side on the same TLC plate. It is possible to use identical, or at least comparable, mobile and stationary phases in TLC and HPLC. There is also much similarity between mechanisms of retention in TLC and HPLC and determination of irreversible adsorption in HPLC is possible by use of TLC [2]. There are, however, some prerequisites for a successful method transfer similar adsorbents, identical mobile phase composition, and use of reproducible chromatographic conditions in TLC and HPLC are essential [2]. The use of planar chromatography for optimization of solute retention in column chromatography is based on fundamental considerations. Differences between the two techniques, e.g. solvent demixing, preadsorbtion, phase ratio gradient, etc., must be taken into account when the TLC and HPLC separations are compared. These so-called thin layer effects make it difficult to achieve complete equivalence between TLC and HPLC [3]. The comparability of the methods is often very case-specific and may, for example, depend on the chambers used in TLC, the nature of the mobile phase, and the properties of the solute [3]. Retention behavior may occasionally be almost identical in TLC and in HPLC [4] and modification of the mobile phase may sometimes have a much greater effect on k (capacity factor) in HPLC than in TLC [5]. It has, however, often been concluded that reversed-phase TLC and HPLC are comparable and that it is possible to predict separation in HPLC on the basis of information from TLC [1, 2, 6 12]. These observations suggest that optimization tools, for example computer-assisted optimization programs, which have been created for the purpose of developing column chromatographic methods could also be used for optimization of TLC 118 VOL. 19. MARCH/APRIL 2006 Journal of Planar Chromatography DOI: /JPC

2 separations. One such program, DryLab, has been shown to facilitate optimization of HPLC methods [13]. The function of DryLab is, in principle, based on the idea there is a linear correlation between log k and the amount of organic solvent in the mobile phase in reversed-phase liquid chromatography. The similarities between TLC and HPLC suggest DryLab could be applied to optimization of TLC methods also. It can also be assumed that it is possible to use DryLab to predict HPLC separations from preliminary data is obtained from TLC separations. Thus, DryLab would facilitate method transfer from TLC to HPLC. To compare TLC and HPLC separations it is essential to be able to compare compound retardation in TLC and retention in HPLC. This means R F values should be converted into k values. For this purpose k p and k c values, capacity factors for TLC and HPLC respectively, have been introduced [1]. The correlation of k p with R F can be expressed simply as k p = (1/R F ) 1. The relationship between k p and k c is linear and can be described by the equation k c = a + b k p. The objective of this study was to demonstrate how it is possible to apply the computer-assisted simulation program DryLab to TLC method development. The possibility of predicting HPLC separation using information obtained from TLC separations was also studied. 2 Experimental 2.1 Sample The sample used in both TLC and HPLC consisted of gallic acid (0.6 mg ml 1 ), rutin (0.2 mg ml 1 ), (+)-catechin (1 mg ml 1 ), and naringin and quercetin (0.4 mg ml 1 ) dissolved in HPLCgrade methanol (Rathburn, Walkerburn, Scotland). Gallic acid (GA) and (+)-catechin (CA) were obtained from Sigma (St Louis, MO, USA), naringin (NI) was from Roth (Karlsruhe, Germany), rutin (RU) was from Merck (Darmstadt, Germany), and quercetin (Q) was from Extrasynthése (Genay, France). 2.2 Thin Layer Chromatography TLC was performed on 20 cm 20 cm glass RP-18 F 254 s TLC plates (Merck # ) cut to 4 cm 10 cm. One sample per plate was applied as 5 mm bands by means of a Linomat IV application device (Camag, Muttenz, Switzerland). The application speed was 15 s µl 1 and the volume of sample was 5 µl. The plates were developed in unsaturated, normal, flat-bottomed chambers; the development distance was 81 mm. Mobile phases were mixtures of HPLC-grade acetonitrile (Rathburn) and 0.1% (v/v) aqueous formic acid (Riedel-de Haën, Seelze, Germany). The acetonitrile content (B) was 25, 30, 35, 40, or 45% (v/v). Water was purified by means of a Millipore MilliQ system. After development the plates were scanned at λ = 255 nm in reflectance mode using a Desaga (Wiesloch, Germany) CD 60 densitometer. 2.3 High-Performance Liquid Chromatography HPLC separations were performed with a Perkin Elmer (Norwalk, CT, USA) Series 200 LC pump and autosampler with a 200-µL loop, Perkin Elmer LC 235 C diode-array detector at a wavelength of 255 nm, and a PE Nelson 600 series link. Compounds were separated on a 25 cm 0.46 mm i.d., 5 µm particle, Supelcosil LC-18 reversed-phase column. Two mobilephase gradients prepared from acetonitrile and 0.1% aqueous formic acid were used in the DryLab simulations the amount (% v/v) of acetonitrile organic solvent in the mobile phase (B) was changed from 5 95% in either 20 or 60 min. The flow rate was 1 ml min 1 and the sample volume was 5 µl. 2.4 DryLab Simulation DryLab 2000 plus (DryLab version , LC Resources, Walnut Creek, CA, USA) was used to simulate chromatographic separations in both TLC and HPLC. DryLab simulation is always based on experimental results obtained from preliminary runs, for example two gradient runs or three isocratic separations [13]. In TLC simulations the dead time was considered to be absent and the development distance was used as the column length. The particle size was assumed to be 5 µm. The flow rate in TLC cannot be adjusted in the simulations and was therefore kept constant (1 ml min 1 ). The TLC simulations were based on either two or three preliminary TLC separations. The simulation modes were either LC-RP Isocratic%B 2 runs or LC-RP Isocratic%B 3 runs. The retention times from two or three different isocratic conditions for each substance were used as initial data. The retention times required for DryLab data entry were obtained from TLC by using the inverse of R F values (1/R F ). After the simulation, the simulated retention times were transformed back to R F values and compared with experimental values. To simulate HPLC separations two gradient runs were performed as preliminary runs. Retention times, peak areas, column data, dead time (2.8 min), dwell volume (3.3 ml), and flow rate (1 ml min 1 ) from these preliminary runs were fed into DryLab. All these data were used to simulate HPLC separation under isocratic conditions in which B was 25, 30, 35, 40, or 45% conditions comparable with those in TLC. 3 Results and Discussion DryLab was used to simulate reversed-phase TLC separations on the basis of information from the preliminary TLC separations. Two or three experimental TLC separations were chosen for use as preliminary runs, depending on the simulation mode. The sample was chosen to demonstrate how phenolic compounds would behave in these chromatographic experiments. The most realistic results were obtained when 1/R F values were used directly as retention times in DryLab instead of converting the R F values first to k p values and then to retention times. The results are presented in Table 1, in which experimental R F values are compared with simulated values. The simulated value Journal of Planar Chromatography VOL. 19. MARCH/APRIL

3 Table 1 Comparison of experimental and DryLab-simulated TLC retardation (R F ) for gallic acid (GA), (+)-catechin (CA), rutin (RU), naringin (NI), and quercetin (Q) and different concentrations of acetonitrile (B [%]) in the mobile phase. Simulations (sim 1 14) are based on preliminary experimental (exp;, n = 2 or 3) TLC elution. B [%] in the preliminary runs for each simulation were: sim 1, 25, 30%; sim 4, 25, 45%; sim 7, 30, 45%; sim 10, 40, 45%; sim 13, 25, 30, 35%; sim 2, 25, 35%; sim 5, 30, 35%; sim 8, 35, 40%; sim 11, 25, 35, 45%; sim 14, 35, 40, 45%; sim 3, 25, 40%; sim 6, 30, 40%; sim 9, 35, 45%; sim 12, 30, 35, 40%. DryLab was unable to simulate the retardation of gallic acid in sim 10 because of equal retention times in 40 and 45% preliminary runs. GA CA RU NI Q Exp. B [%] 25 Exp Sim Sim Sim Sim Sim Sim Sim Sim Exp. B [%] 30 Exp Sim Sim Sim Sim Sim Sim Sim Sim Exp. B [%] 35 exp Sim Sim Sim Sim Sim Sim Exp. B [%] 40 Exp Sim Sim Sim Sim Sim Sim Sim Sim Exp. B [%] 45 Exp Sim Sim Sim Sim Sim Sim Sim Sim was regarded as in agreement with the experimental value when it was inside the area of the sample band on the plate. The numerical value of the band area, i.e. the width, was obtained by calculating the peak width at half height for each compound from the densitogram and by adding plus or minus the peak width at half height to the experimental retardation value. From these results it can be seen that DryLab can be used to simulate TLC separation. The most accurate result was obtained when the simulation was based on three preliminary runs and the simulated conditions were in the same B [%] range as the preliminary runs (Table 1, sim 11). In simulation 11 the simulated R F values were, in practice, the same as the experimental R F values. Usually, simulations based on two preliminary runs were also very consistent with experimental retardation values, although occasionally the retardation values differed clearly from the experimental values. Differences between simulated and the experimental values were largest when B [%] in the other preliminary run was 45%. For this value of B [%] most of the compounds tended to lose their capacity to be adsorbed by the layer and eluted very close to the mobile phase front. Thus, the peaks began to converge and their detection became more difficult, which may in part explain this result. This finding indicates that simulation accuracy depends on the quality of the preliminary runs. It can also be seen from Table 1 that at the highest value of B [%] the experimental retardation values quite often differed from the simulated values. This may also be because of difficulties in detecting the converging peaks at the highest B [%]. When resolution and peak retardation decrease in experimental separations comparison of simulated and experimental results becomes more difficult. Another factor found to have a major effect on the results was differences between B [%] in preliminary runs. All the results from both simulation modes, i.e. based on either two or three preliminary runs, suggest that differences between the organic modifier content in two adjacent preliminary runs should be more than 5%. For example, the results from simulations 12, 13, and 14 in Table 1, where the difference between B [%] in adjacent preliminary runs was only 5%, are inferior to results from simulation 11, even though all simulations were based on three observation points. Simulated retardation based on two preliminary separations in TLC was usually found to be adequate when the simulated conditions were inside the B [%] range used in the preliminary runs. The simulated retardations in sim 2, sim 3, and sim 4 and in sim 3, sim 6, and sim 7 for B [%] of 30 and 35% (Table 1), respectively, are very similar to the experimental results. The only exception to this observation was simulation 4 for B [%] of 35%. The other preliminary run for simulation 4 was conducted at 45%, however, which, as mentioned above, was found to lead to inaccurate simulations. To achieve reliable TLC simulation on the basis of preliminary TLC runs it is recommended that three preliminary separations are performed in which differences between B [%] in adjacent runs is more than 5%; it is also advisable to use the R F range [1]. Information necessary for reliable simulation, 120 VOL. 19. MARCH/APRIL 2006 Journal of Planar Chromatography

Figure 1 Experimental densitogram (A) of the TLC separation of the test solution with 30% acetonitrile compared to DryLab simulated (simulation 11) TLC separation (B) at the same B%.

4 Figure 1 Experimental densitogram (A) of the TLC separation of the test solution with 30% acetonitrile compared to DryLab simulated (simulation 11) TLC separation (B) at the same B%. Simulation conditions corresponding to the experimental conditions were: column length (development distance): 8.1 cm; diameter (layer thickness): cm; flow rate: 1 ml min 1 ; particle size: 2 µm. The order of compounds is 1, quercetin, 2, naringin, 3, rutin, 4, (+)-catechin and 5, gallic acid. which should be obtained from preliminary runs, may not be obtained if the sample is too complex or if the polarity of the compounds of interest is either too similar or too different. The required initial data cannot be obtained if the spots are not separated or if all the compounds are not moved from the origin. Some other observations were made concerning the simulation procedure. Particle-size data in DryLab do not affect retention times. For clear visualization of the peaks in the simulations, however, it was found practical to use relatively small particle sizes. In this study the simulations were originally performed using a particle size of 5 µm, which, especially with higher acetonitrile concentrations, brought most of the peaks together in the simulations. When the particle size was changed to 1 or 2 µm it was, again, usually possible to visualize individual simulated peaks. The DryLab-simulated chromatogram was found to mimic the TLC densitogram when the small particle size was used in simulation settings, except that peak order was reversed. DryLab simulated and experimental TLC separations are compared in Figure 1. Figure 2 Values of k p from TLC separations (p) and k c from HPLC simulations (n) as a function of B [%] for each compound. When all the necessary data are fed into DryLab the program produces a resolution map which gives a reasonable concentration range for organic modifier. When the concentration of the organic modifier is changed in the resolution map, peak movement can be seen in the simulated chromatogram; this aids optimization of the TLC separation. The peak movement is easier to observe and the relationships between simulated peaks are more realistic when the particle size is set to a level for which the simulated peaks mimic bands (peaks) in the densitogram. Studies have been published which discuss the possibility of converting separation methods from TLC to HPLC [1 12, Table 2 Comparison of k c values converted from k p [(1/R F ) 1] values (k c conv.) to k c [(t r t 0 )/t 0 ] values obtained from DryLab simulations (k c sim). Both k c values are presented for each compound. Converted k c values are calculated from the regression equations (Figure 2) which gave the best correlation. B [%] Gallic acid Rutin (+)-Catechin Naringin Quercetin k c conv. k c sim k c conv. k c sim k c conv. k c sim k c conv. k c sim k c conv. k c sim Journal of Planar Chromatography VOL. 19. MARCH/APRIL

5 effect in HPLC than in TLC. For example, if the acetonitrile concentration was increased from 25 to 30%, the k c value of naringin in HPLC was reduced by 70% whereas in TLC the k p value was reduced by 30% only. Thus, to be able to convert a separation method from TLC to HPLC in which neither retention times nor selectivity would change remarkably, this behavior must be taken into account. Comparison of k p and k c similar to that published by Reuke and Hauck [2] was also performed in this work (Figure 3). The k c values for isocratic HPLC separations were calculated from DryLab simulations based on two preliminary HPLC gradient runs. The k p values were calculated from data from experimental TLC separations by use of the equation k p = (1/R F ) 1 [1]. The regression between k p and k c for each compound was studied; the results are presented in Figure 3. The different functions describing the regression were compared on the basis of their correlation values. Interestingly, unlike the study published by Reuke and Hauck [2], in our experiments it was found that a power function usually resulted in better correlation than a linear equation. Both linear and power functions as regression equations, with the corresponding R 2 values, are presented in Figure 3 for each compound. In this study it was not possible to achieve 1:1 transferability for compounds from TLC to HPLC as demonstrated by Reuke and Hauck [2]. It was, however, found that when k p values from experimental TLC separations were converted to k c values using the regression functions giving the best correlation factors, the converted k c values were very similar to simulated k c values (Table 2). This observation suggests that if the regression function relating k p and k c is known for each compound to be separated, the TLC separation can be transferred directly to HPLC. It is thus possible to optimize an HPLC separation on the basis of information from TLC separations, and the simulation program DryLab can be used for this purpose. The simulations would be performed in LC-RP isocratic%b (3 runs) mode in which all the necessary retention data are obtained from TLC separations. This information would then be applied to the same column conditions as were used for measurement of k c values. Figure 3 Relationship between k p and k c for each compound obtained by linear regression and use of power functions, with R 2 values ]. Most of these studies, however, require many experiments to provide a convenient way of converting the separation method from TLC to HPLC. In this study we illustrated the possibility of transferring the separation from reversed-phase TLC to reversed-phase HPLC by comparing k values (k p and k c) as a function of B [%] (Figure 2). The results in Figure 2 illustrate there is a clear difference between the slopes of the linear functions for k p and k c. Similar results have previously been reported, for example by Rózylo et al. [4, 14] and Vuorela et al. [5]. These results mean that changes in B [%]have a greater 4 Conclusion The computer-assisted simulation program DryLab can be used to simulate reversed phase TLC separation when initial data are obtained from TLC separations. Method transfer from TLC to HPLC is possible by means of DryLab, although a relatively large number of experiments are required for reasonably accurate prediction of separations after the transfer procedure. Acknowledgements This study was supported by grants from the Ministry of Education, Science and Sport of the Republic of Slovenia and the European Commission through a project with contract no. ICA1-CT VOL. 19. MARCH/APRIL 2006 Journal of Planar Chromatography

6 References [1] F. Geiss, Fundamentals of Thin Layer Chromatography (Planar Chromatography), Hüthig, Heidelberg, [2] S. Reuke and H.E. Hauck, Fresenius Z. Anal. Chem. 351 (1995) [3] J.K. Rózylo and M. Janicka, J. Planar Chromatogr. 4 (1991) [4] J.K. Rózylo and M. Janicka, J. Planar Chromatogr. 9 (1996) [5] P. Vuorela, E.-L. Rahko, R. Hiltunen, and H. Vuorela, J. Chromatogr. A 670 (1994) [6] W. Golkiewicz, Chromatographia 14 (1981) [7] G.C. Kiss, E. Forgács, T. Csetháti, and J.A. Vizcaino, J. Chromatogr. A 896 (2000) [8] H.J. Issaq, B. Shaikh, N.J. Pontzer, and E.W. Barr, J. Liq. Chromatogr. 1(2) (1978) [9] W. Jost, H.E. Hauck, and F. Eisenbeib, Fresenius Z Anal. Chem. 318 (1984) [10] H. Jork and B. Roth, J. Chromatogr. 144 (1977) [11] W. Golkiewicz, Chromatographia 14 (1981) [12] E. Von Arx and M. Faupel, J. Chromatogr. 154 (1978) [13] I. Molnar, J. Chromatogr. A 965 (2002) [14] J.K. Rózylo, M. Janicka, and R. Siembida, J. Liq. Chromatogr. 17(17) (1994) [15] M. Janicka and J.K. Rózylo, J. Planar Chromatogr. 6 (1993) [16] T. Tuzimski and E. Soczewinski, Chromatogr. 56 (2002) [17] J.K. Rózylo and M. Janicka, J. Liq. Chromatogr. 14(16/17) (1991) [18] M. Janicka and J.K. Rózylo, J. Planar Chromatogr. 3 (1990) Ms received: October 27, 2005 Accepted by SN: November 21, 2005 Journal of Planar Chromatography VOL. 19. MARCH/APRIL

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