Reversed-phase thin-layer chromatography technique for the comparison of the lipophilicity of selected non-steroidal anti-inflammatory drugs

Journal of Pharmaceutical and Biomedical Analysis 85 (2013) 132–137

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Reversed-phase thin-layer chromatography technique for the comparison of the lipophilicity of selected non-steroidal anti-inflammatory drugs Małgorzata Starek a,∗ , Łukasz Komsta b , Jan Krzek a a

Department of Inorganic and Analytical Chemistry, Faculty of Pharmacy, Collegium Medicum, Jagiellonian University, 9 Medyczna Str, 30-688 Kraków, Poland b Department of Medicinal Chemistry, Medical University of Lublin, 4 Jaczewskiego Str, 20-090 Lublin, Poland

a r t i c l e

i n f o

Article history: Received 13 March 2013 Received in revised form 9 July 2013 Accepted 11 July 2013 Available online 25 July 2013 Keywords: Lipophilicity RP-TLC Coxibs Oxicams NSAIDs

a b s t r a c t The chromatographic behavior of a series of coxibs and oxicams, drugs from a group of non-steroidal anti-inflammatory drugs, was studied by reversed-phase thin-layer chromatography with binary mobile phases containing water and the organic modifiers: methanol, acetone, 1,4-dioxane, acetonitrile and 2propanol. Linear relationships were obtained between the retention RM values of the compounds and the concentration of organic modifier in the mobile phase. Values of RM0 , represent the theoretical RM values at 0% organic solvent in the mobile phase were calculated by extrapolation. These experimental lipophilicity values were correlated with lipophilicity (logP) from databases. The obtained results show that reversed-phase chromatography (experimental parameters) may be a good instrument for analytics in describing the lipophilic nature of investigated compounds as well as the activity. © 2013 Elsevier B.V. All rights reserved.

1. Introduction Lipophilicity is one of the parameters of chemical substances which influence their biological activities [1]. It is an important parameter in medicinal, pharmaceutical and environmental chemistry. Lipophilicity is also a major structural factor that influences the pharmacokinetics and pharmacodynamics behavior of compounds. Partitioning within a biological system and biological activity are governed by forces that are, among others, defined by hydrophobic interactions. Strong hydrophobic interactions can result in an unspecific binding with proteins (target and nontarget) in the aqueous biological environment. A hydrophobic drug molecule has a thermodynamic tendency to reduce the surface area exposed to water. For compounds with extracellular or cell-surface targets it appears prudent to restrict lipophilicity and thereby avoid easy diffusion across biological membranes into cells, cellular compartments, and the central nervous system. Therefore, it is critical to have lipophilicity information at early discovery stage and it can help chemists to design new molecules and enables biologists to interpret screening results better. The lipophilicity of compound is expressed as logP, the logarithm of the partition coefficient of the compound between n-octanol and water, a system which is

∗ Corresponding author. Tel.: +48 126205480. E-mail addresses: [email protected], [email protected] (M. Starek). 0731-7085/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jpba.2013.07.017

conventionally used because of its partitioning analogy with the biological environment. Frequently used methods for determination of partition coefficient can be divided into three groups: direct (shake-flask method, where compound distribution between n-octanol and water or buffer is determined), indirect (chromatographic and electrometric techniques), and computational methods: (different mathematical models, by using special software) [2–4]. Although the traditional shake-flask method enables accurate determination of logP, this approach suffers from numerous drawbacks – it is, for example, extremely time-consuming and tedious, because it requires a very long time for equilibration [5,6]. The method is, therefore, not convenient for routine analysis of a large series of newly synthesized compounds. Besides shake-flask, chromatographic systems [7–10], membranes [11,12], and optical [13] techniques are used. To overcome these drawbacks, partition chromatography has become a potential alternative to traditional determination of lipophilicity [14]. In practice, chromatographic methods provide sufficiently precise logP values if the calibration equation is obtained with compounds of related chemical structures and chemical properties similar to those of the compounds to be investigated [15]. The determination of the lipophilicity by RP techniques can have very high practical importance, especially when high biological activity is also a consideration [16]. In pharmaceutical analysis, chromatographic approaches are extremely important in lipophilicity determination, mainly because they are

M. Starek et al. / Journal of Pharmaceutical and Biomedical Analysis 85 (2013) 132–137

rapid, highly reproducible and suitable for routine analysis of many samples [17]. A reversed-phase thin-layer chromatography (RP-TLC) is suitable for investigation of both lipophilic and hydrophilic substances [18]. Apart from the experimental methods, lipophilicity can be estimated computationally using various chemical software products, based on the different mathematic algorithms [19–22]. The work described in this paper is part of physicochemical studies of a group of non-steroidal anti-inflammatory drugs (NSAIDs) from the group of COX-2 inhibitors – oxicams and coxibs, which are popular in therapy. In this study we have investigated the possibility of development of a RP-TLC method (using a chemically unrelated calibration set) and the applicability of the method for determination of logP values of structurally similar compounds with a wide range of logP, and to compare these results with logP from database [23].

133

´ organic modifier in eluent (RM0 ), in accordance with Soczewinski– Wachtmeister equation [24]: RM = RM0 + aC where RM0 is the lipophilicity index, C is the volume fraction or percentage of organic modifier in the mobile phase, and a is the slope of the regression curve. 2.4. Statistical methods Statistical analysis was performed using Statistica v10 software (StatSoft, USA) and GNU R 2.15.1 (www.r-project.org). Linear regression analysis was used to evaluate the suitability of the RPTLC analysis examined and the validity of the computer programs. The correlation coefficient (r, r2 ), and the standard errors of the slope, interception and estimate (Sa , Sb , Se ) were used as the basis for testing the linearity of regression plots.

2. Experimental 2.1. Chemicals and reagents The following components of the mobile phases: methanol, acetone, 1,4-dioxane, acetonitrile, 2-propanol (POCH Gliwice, Poland, analytical grade) were used. Methanol was used to prepare the solutions of compounds. Eight compounds: piroxicam, meloxicam, tenoxicam, isoxicam, celecoxib, etoricoxib, valdecoxib and rofecoxib (chromatographic purity, various sources), were studied (Table S-1). 2.2. RP-TLC analyses The mobile phases were prepared by mixing the respective amounts of water and organic modifier (methanol, acetone, 1,4dioxane, acetonitrile, 2-propanol) in the range from 25 to 90% (v/v) in 5% increments (9–11 phases for modifier). The upper concentration depended on the linearity of the RM /polar modifier concentration correlation and retention behavior. The composition of the mobile phases is listed in Table S-2. TLC was performed on 7 cm × 10 cm TLC plates precoated with RP-18 F254 (Merck, Darmstadt, Germany) in vertical chambers 20 cm × 10 cm × 18 cm in size (Sigma–Aldrich, St. Louis, USA). Solutions (10 ␮L) of the analyzed compounds (0.1% (w/v) in methanol) were applied to the plates as 5-mm bands, 10 mm apart and 10 mm from the lower edge and sides of the plates, by means of a Linomat V applicator from Camag (Basel, Switzerland). The chamber was saturated with mobile phase for 20 min. The chromatograms were developed at room temperature until the eluent reached a distance of 9 cm from the starting line. The plates were then dried at room temperature. The final location of the spots was determined with ultraviolet light at 254 and/or 366 nm (UV lamp, Camag, Basel, Switzerland). Bands were symmetric and no tailing was observed. The chromatograms were done in triplicate and mean RF values were calculated. 2.3. Application of RP-TLC for determination of lipophilicity of examined drugs The parameter of lipophilicity determined by RP-TLC can be expressed by RM value. RM values were calculated from experimental RF values by use of the equation: RM = log

 1  RF



−1 .

The RM values obtained for studied compounds on RP-18TLC plates, were extrapolated to zero concentration (0%) of

3. Results and discussion Chromatographic indices are widely used as alternative to logP values obtained by extractive method, because partitioning between a non-polar stationary phase and aqueous mobile phase in chromatography often seems to be similar to partitioning in membranes in biological systems. In our work RP-TLC technique was used to study the lipophilicity of some oxicams (piroxicam, meloxicam, tenoxicam, isoxicam), and coxibs (celecoxib, etoricoxib, valdecoxib, rofecoxib). Because these drugs have not yet been investigated in this way, the retention study should provide relevant information about this important physicochemical property, which affects pharmacodynamics and pharmacokinetic aspects of their action. We performed regression analysis to discover relationship between chromatographic retention and theoretical partition coefficients. ´ The slope of the Soczewinski–Wachtmeister equation is related to the specific hydrophobic surface area of the compound and has also been proposed as an alternative measure of lipophilicity [25]. Relationship between the concentration of organic modifier (methanol, acetone, 1,4-dioxane, acetonitrile, 2-propanol) in the mobile phase, and retention, RM , were established for each drug over the examined range of organic modifier concentration in the mobile phase. Chromatographic RM0 values were determined on the basis of these relationships. Values of RM0 corresponding to 100% water were obtained by extrapolation. The chromatographic data collected for all the compounds by use of those aqueous-organic mobile phases are listed in Table S-3. The relative lipophilicity, expressed as RM0 values, and data obtained from regression analysis are given. A linear relationships obtained between RM0 values (intercept) and the slope, a, of equations (RM = RM0 + aC) for the used mobile phases, is one of the basis features of chromatographic determination of the lipophilicity of the compounds [26]. In this study the correlation between RM0 and a is linear for analyzed series of compounds. The good correlation obtained between RM0 and a confirms the suitability of these systems for estimation of the lipophilicity of the drugs (Fig. S-1). The relationship between RM0 and a for analyzed compounds suggest that the mechanism of chromatographic retention are similar within the groups (Table 1). The RM values of the compounds decreased linearity as the organic modifier content of the mobile phase was increased. Table S-3 shows the RM0 (intercept), a (slope), r (correlation coefficients) and S (standard deviations) values obtained for the examined compounds. The results indicate that linear relationship RM = RM0 + aC was obtained over all of the studied substances in various mobile phases. The high correlation coefficients (r2 > 0.96) were indicated

M. Starek et al. / Journal of Pharmaceutical and Biomedical Analysis 85 (2013) 132–137

6

CEL

VAL

ETO

ROF

MEL

PIR

ISO

k – slope; b – intercept; Sk – standard error of the slope; Sb – standard error of the intercept; Se – standard error of the estimate.

TEN

0.1416 0.1079 0.0576 0.4227 0.3492 0.1817 0.2706 0.2564

5

Se

0.1835 0.1671 0.1046 0.6082 1.1608 0.6267 0.6297 0.5403

4

Sb

−0.4404 −0.8271 −0.9436 −0.2622 −1.2732 −1.7680 −0.7959 −0.6898

Height

b

9.7527 9.2078 6.4603 38.4835 23.7939 18.9332 16.8188 16.1962

2

Sk

−75.3828 −85.7906 −88.9841 −45.9222 −99.3104 −123.6620 −85.5640 −82.6988

1

k

Piroxicam Meloxicam Tenoxicam Isoxicam Celecoxib Etoricoxib Valdecoxib Rofecoxib

0

Compound

7

Table 1 Data of the linear correlation equations RM0 = b + ka for analyzed drugs by the different organic modifiers.

3

134

Fig. 1. Similarity between chromatographic data (slopes, intercepts) of analyzed compounds, shown as dendrogram based on Euclidean distance.

that all the equations obtained were highly significant. The calculated RM0 values are different for each compound and probably depend on its chemical structures. For the oxicams RM0 values were in the range from 0.0011 to 1.7032, whilst RM0 values for the coxibs always achieved higher values, in the range from 1.0325 to 4.1971. We cannot definitely say which equation better describes the retention–eluent composition relationship, and which one can be taken to determine intercept, RM0 values, which can show lipophilicities of all investigated compounds. Generally, higher RM0 values, as a lipophilicity parameter, indicate greater lipophilicity of the compound. The lowest RM0 values was obtained for oxicams, especially for tenoxicam and isoxicam, which, in contrast with coxibs have no benzothiazine group and less carbon atoms in their structures. This implies that those factors can increase the lipophilicity of this series of compounds. The different regression curves for each examined group of compounds depends not only on the of solvent applied as a component of the mobile phase, but also to a considerable extent a specific interaction between solutes, solute–solvents, and solute–stationary phase. Obtained RM0 values extrapolated for the drugs from methanol–water system were usually larger than the respective data from the remaining systems. RM0 values from 1,4-dioxane–water and acetonitrile–water mobile phases were larger than values from acetone–water and 2propanol–water mobile phases. This differences can be explained by better solubility of the tested compounds in 1,4-dioxane and methanol than in acetone, acetonitrile and 2-propanol (solvents with different eluting power). There was, however, satisfactory correlation (r2 ≥ 0.98). The obtained values of RM0(methanol) , RM0(acetonitrile) , RM0(acetone) , RM0(1,4-dioxane) , and RM0(2-propanol) , lipophilicity parameters indicate that tenoxicam and isoxicam show the lowest lipophilic properties. Rofecoxib, piroxicam and meloxicam have intermediate lipophilic properties. However, celecoxib, valdecoxib and etoricoxib have the highest lipophilicities. Arranging the compounds gave the following list: tenoxicam < isoxicam < meloxicam < piroxicam < rofecoxib < etoricoxib < valdecoxib < celecoxib. Extrapolated RM0 values from TLC systems employing two different organic modifiers were correlated. Good correlations were obtained. Table 2 shows results of the relationship between RM0 values obtained on RP-TLC layers in the system methanol–water with the values obtained in the other systems with acetonitrile and acetone as modifiers, as well as RM0 values obtained in eluent systems with 1,4-dioxane and 2-propanol. Regression coefficients of those correlations are relatively high, when we compare all modifiers. The highest correlation was for system containing methanol with acetonitrile (r ∼ 0.99), and the lowest for acetonitrile with 1,4-dioxane (r = 0.9282). The obtained data showed that polarity parameters (used systems) also influenced retention, which suggested on mixed retention mechanism. The most frequently used mathematical models are based on either the substructure or whole molecular approaches. The first

one predict logP according to the contributions of each molecular fragments, while the second utilizes the molecular characteristics such as molecular lipophilicity potentials, molecular properties (e.g. volume weight, molecular surface are) or topological indices. Nevertheless, the molecular approach is preferred since it takes into account steric and conformation effects and therefore it is able to distinguish the structural isomers and overall it considers the whole molecule as a complex. When chromatographic lipophilic parameters were compared with molecular weights of the studied compounds, we observed that the highest lipophilicity was determined for the celecoxib (RM0 ∼ 2.2–4.1) with the highest molecular weight (381), and the lowest for isoxicam and tenoxicam (RM0 ∼ 0.001–1.1) with high molecular weight (335 and 337). Unfortunately, no simple correlation of lipophilicity with molecular weight, was observed. As the lipophilicity values are different among modifiers, to explore and visualize similarities and differences of obtained results among the studied drugs, we have also decided to examine the retention dataset by scaled Principal Component Analysis (PCA). The matrix subjected to PCA had 8 rows (compounds) and 10 columns (5 slopes converted to positive values and 5 RM0 values for each compound). PCA decomposes original data matrix onto a series of scores and loadings. Loadings represent trends found inside data, i.e. intercorrelations between TLC systems. Scores (Principal Component Values) can be treated as new variables, representing intensities of these scores. PCA orders these trends according to decreasing variance, so first principal component with corresponding loading represents major trend in data – in TLC case mainly an average retention. The results are shown in Fig. 1. In general, both slopes and intercepts are highly intercorrelated and differences are very small. 96.6% of whole variance is located inside first component, representing average retention (lipophilicity value). In general, slopes and intercepts obtained with the same modifier are very highly correlated (the arrows almost overlap). By inspecting the loading values, one can interpret further trends, located in remaining part of the variance. In this case, differences among modifiers represent only 1.98% of data variability, but they can be easily interpreted from the loadings (denoted as arrows in Fig. 2). It can be concluded, that some compounds (with high PC2, such as valdecoxib and rofecoxib) have visibly higher values obtained with methanol and acetonitrile, whereas lower values with 1,4-dioxane. It can be interpreted in context of presence of five-membered ring with oxygen. The compounds with low PC2 represent opposite trend (celecoxib, having two nitrogens in five-membered ring). The oxicams form distinct cluster, well separated from coxibs. This clustering is more visible in hierarchical cluster analysis, performed on Euclidean distance matrix (Fig. 1). An interesting discussion can be done inspecting the loading vectors of modifiers. Dioxane is most distinct one and the high

M. Starek et al. / Journal of Pharmaceutical and Biomedical Analysis 85 (2013) 132–137

135

Table 2 Terms of the linear correlation equations RM0(1) = b + aRM0(2) for different mobile phase modifiers. Organic modifiers (1)/(2)

a

Sa

b

Sb

r

Se

Methanol/acetonitrile Methanol/acetone Methanol/1,4-dioxane Methanol/2-propanol Acetonitrile/acetone Acetonitrile/1,4-dioxane Acetonitrile/2-propanol Acetone/1,4-dioxane Acetone/2-propanol 1,4-Dioxane/2-propanol

0.9543 0.9068 0.8570 1.3083 0.9375 0.8803 1.3412 0.9652 1.4214 1.4047

0.0459 0.0651 0.1266 0.1005 0.0809 0.1441 0.1419 0.0897 0.1082 0.1637

0.8607 0.9443 1.0083 1.3253 0.1076 0.1827 0.5105 0.0388 0.4372 0.4667

0.0887 0.1273 0.2501 0.1140 0.1582 0.2847 0.1609 0.1772 0.1228 0.1856

0.9931 0.9849 0.9403 0.9827 0.9784 0.9282 0.9680 0.9751 0.9830 0.9616

0.1455 0.2157 0.4237 0.2303 0.2681 0.4823 0.3251 0.3001 0.2480 0.3750

a – slope; b – intercept; Sa – standard error of the slope; Sb – standard error of the intercept; r – correlation coefficient; Se – standard error of the estimate.

Table 3 Experimental determined (RM0 = logPexp ) and calculated partition coefficients (logPref ) for the studied drugs.

RM0(methanol) RM0(acetone) RM0(1,4-dioxane) RM0(2-propanol) RM0(acetonitrile) AlogPS ChemAxon ChemIDplus PhysProp XlogP3 ClogPs

Piroxicam

Meloxicam

Tenoxicam

Isoxicam

Celecoxib

Etoricoxib

Valdecoxib

Rofecoxib

1.70 0.69 0.96 0.15 0.95 1.22 0.6 3.06 3.0 3.1 3.06

1.46 0.57 0.63 0.03 0.63 2.28 1.6 3.43 1.9 3.4 2.62

1.11 0.32 0.40 0.02 0.41 1.82 1.22 2.4 1.9 2.2 1.56

1.11 0.41 0.54 0.001 0.07 – – 2.83 – 3.0 1.02

4.08 3.77 4.20 2.25 3.34 3.99 4.01 3.47 3.9 3.4 –

3.26 2.18 2.09 1.57 2.36 3.7 2.79 – – 3.3 –

3.31 2.50 2.13 1.30 2.51 3.32 2.82 – 3.2 2.6 –

2.88 2.08 1.71 1.03 2.33 2.32 2.56 – 3.2 2.3 –

–: no data; RM0(X) : RM0 value with (X) organic modifier.

-3

-2

-1

1

2

ROF

1

ETO

0

PIR MEL

DIO.I DIO.S

ISO

-1

0.0

MET.S ACN.S ACN.I MET.I ACT.S ACT.I PRO.S PRO.I

-0.2

PC2

0.2

2

0.4

VAL

0

-0.6

-3

-0.4

-2

TEN

CEL -0.6

-0.4

-0.2

0.0

0.2

0.4

PC1

Fig. 2. Scaled Principal Component Analysis performed on slopes (S) and intercepts (I), obtained with several modifiers.

retention value lowers value of PC2. Acetonitrile and 2-propanol have almost no impact on PC2, whereas impact of methanol is positive. Therefore, methanol can be treated as opposite to dioxane (when retention increases with methanol it decreases with dioxane and vice versa). Lipophilicity scales are dependent by the experimental conditions. Moreover, in some cases the obtained values can be a consequence of specific interactions that take place between the investigated compounds and the employed stationary and mobile phases. As a stationary phase we used RP-18 F254 plates, the most

popular phase used for RP-TLC lipophilicity studies due to their ability to separate a wide range of compounds. The examined compounds contain heterocyclic fragments such as azole, oxazole, pyridine, thiazole and thiophene rings, and some polar groups, such as OH, C O. As a consequence they exist in several electrical states among others depending on pH. Therefore, various mixtures of the mobile phase (especially buffer solutions) may be used to choose the optimal pH for subsequent experiments. Presented study comprised only various combinations of solvents, not buffer solutions. As it is well known, water shows the strong cohesive energy density. From than reason other solute molecules, especially non-polar are excluded from the water mobile phase. Tendency for this effect grows according to the increase of molecular volume of the solute. Highly significant correlations obtained between different experimental solutes suggest that all mobile phases are suitable for estimating the lipophilicity of the investigated drugs, and RP-TLC appears as a suitable and estimation of this compounds. The investigated compounds were characterized by several logP values computed to various algorithms included in the various software and Internet modules. Calculation methods are based on the theoretical fragmentation of the molecule into suitable substructures for which reliable logPcalc increments are known. The logPcalc is obtained by summing the fragment values and the correction terms for intramolecular interactions. They are very useful but have some limitations. Values of logPcalc are often not sufficiently precise and differ substantially from logP values determined experimentally. This is particularly true for compounds with complex structures, the properties of which are highly dependent on conformation, tautomerism, ionization, hydrogen bonds, ion-pair formation, etc. Such interactions can significantly affect calculated lipophilicity values. The aim of this study was also the comparison of lipophilicity values determined chromatographically (RM0 ) with lipophilicity values (logPref ) calculated by use of different software products (Table 3). Theoretical calculations gave different results, depending on the software used. Some of algorithms from databases based on atom or group contributions, others based

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M. Starek et al. / Journal of Pharmaceutical and Biomedical Analysis 85 (2013) 132–137

Table 4 Correlation between logPref and RM0 values in the calibration equations: RM0 = b + a logPref . Database Methanol–water system AlogPS ChemAxon ChemIDplus PhysProp XlogP3 ClogPs 2-Propanol–water system AlogPS ChemAxon ChemIDplus PhysProp XlogP3 ClogPs

a

Sa

b

Sb

r

Se

1.2002 0.8987 1.8131 1.3439 0.4809 0.2958

0.2445 0.1609 1.2395 0.3050 0.9496 0.0608

−0.8230 0.5397 −3.6145 −1.4065 0.9632 0.7354

0.1720 0.3977 3.7978 0.8971 2.7990 0.1349

0.9100 0.9284 0.6452 0.9106 0.2025 0.9603

0.5080 0.4554 1.1025 0.5435 1.2193 0.0989

0.9524 0.7127 1.2279 0.9912 0.4201 0.0575

0.1686 0.1072 1.0627 0.2659 0.7079 0.0291

−1.7638 −0.6812 −3.2405 −2.0284 −0.4299 −0.0682

0.4909 0.2649 3.2559 0.7820 2.0865 0.0645

0.9298 0.9479 0.5550 0.8812 0.2355 0.8135

0.3503 0.3033 0.9451 0.4737 0.9089 0.0473

a – slope; b – intercept; Sa – standard error of the slope; Sb – standard error of the intercept; r – correlation coefficient; Se – standard error of the estimate.

on atomic-type electropotogical-state indices and neutral network modeling, or calculated octanol–water partition coefficients. To examine more detailed relationships between the chromatographic data, RM0 , and calculated lipophilicity the values were compared by linear correlation RM0 = a logPref + b. Linear dependences with high regression coefficients for analyzed compounds were obtained, and gave the calibration relationships presented in Table 4. The results indicate that the RM0 values obtained by RP-TLC are lower for oxicams, but similar for coxibs to, those obtained by computational methods (logPref ). The best agreement of RM0 values was in water with methanol and acetone systems. The statistical results show that the correlation between experimentally obtained values of lipophilicity parameters, with the theoretical values from databases is not always satisfactory. The best fit for most of studied compounds was observed for ChemAxon, PhysProp and AlogPS databases. The results show that the RM0 values are strongly correlated between them, correlation coefficients being in the range from 0.88 to 0.95. Also the RM0 values are strongly correlated with ClogPs data, with r ∼ 0.81–0.96. Much lower correlation coefficients (r ∼ 0.6) attempts to correlate experimental RM0 with ChemIDplus. The worst correlations between experimental and theoretical values were obtained for XlogP3 software (r ∼ 0.2). The best correlations between compared parameters found in case of RP-18 plates and methanol–water systems, may suggest that the specific hydrophobic surface of the compounds play an important role in their retention mechanism. In the case of logP for molecules containing ionizable groups such as the examined compounds, which exist in several electrical states depending on pH (it leads to intricate lipophilicity profiles) a direct comparison of the experimental data to the calculated logP could be difficult. 4. Conclusions The results of our analysis led us to the conclusion that the relatively simple RP-TLC technique can be successfully used for study of this property for coxib (celecoxib, etoricoxib, valdecoxib, rofecoxib) and oxicam (piroxicam, meloxicam, tenoxicam, isoxicam) compounds. The chromatographic parameters of lipophilicity (RF , RM , RM0 ) were estimated and compared with the calculated partition coefficients. The values obtained for different organic modifiers (methanol, acetone, 1,4-dioxane, acetonitrile, 2-propanol) proved to be a reliable alternative for classic shake-flask lipophilicity estimates. On the basis of the presented correlations, it may be appreciated that the lipophilicity indices determined on RP-18 F254 stationary phase might be the good choice for the lipophilicity prediction of some of COX-2 inhibitors. It can be concluded that the achieved experimental lipophilicity parameters better reflect

the real physic-chemical properties of studied drugs, than some of software data, which are often not sufficiently precise and differ substantially from logP values determined experimentally. Although the proposed chromatographic systems cannot explain all the intermolecular interactions which are important for drug activity, the RP-TLC experiments may be a good instrument for analytics, especially in the analysis of the candidates in the early phase of drug research.

Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at http://dx.doi.org/10.1016/j.jpba.2013.07.017.

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