Simultaneous spectrofluorimetric and spectrophotometric determination of melatonin and pyridoxine in pharmaceutical preparations by multivariate calibration methods

Il Farmaco 60 (2005) 451–458 http://france.elsevier.com/direct/FARMAC/

Simultaneous spectrofluorimetric and spectrophotometric determination of melatonin and pyridoxine in pharmaceutical preparations by multivariate calibration methods Mohammad-Hussein Sorouraddin a,*, Mohammad-Reza Rashidi b, Ebrahim Ghorbani-Kalhor a, Karim Asadpour-Zeynali a a

Analytical Chemistry Department, Faculty of Chemistry, Tabriz University, P. O. Box 51664, Tabriz, Iran b Drug Applied Research Center, Tabriz University of Medical Science, Tabriz, Iran Received 3 January 2005; received in revised form 20 March 2005; accepted 31 March 2005

Abstract Partial least-squares (PLS) calibration and principal component regression (PCR) methods were utilized for the simultaneous spectrofluorimetric and spectrophotometric determination of pyridoxine (PY) and melatonin (MT). Since emission and adsorption spectra of these drugs overlap, PY and MT cannot be directly determined by fluorimetric nor by spectrophotometric methods. Full-spectrum multivariate calibration PLS and PCR methods were developed for both fluorimetry and spectrophotometry. The conditions were optimized for fluorimetric as well as for spectrophotometric determination of both drugs. The simultaneous determination of PY and MT was carried out in mixtures by recording the emission fluorescence spectrum between 324 and 500 nm (kex 285 nm) for fluorimetry, and by recording the absorption spectrum between 250 and 350 nm for spectrophotometry (kmax(PY) 310 nm, kmax(MT) 278 nm). The experimental calibration matrixes were designed orthogonally. At the optimum conditions, dynamic ranges were 0.04–1.3 and 0.1–4 µg ml–1 for fluorimetry and 1–22 and 1–24 µg ml–1 for spectrophotometry for MT and PY, respectively. The calibration concentrations were prepared in the dynamic ranges. The parameters of the chemometrics procedure for the simultaneous determination of MT and PY were optimized, and the proposed methods were validated with prediction set. Finally the procedures were successfully applied to simultaneous spectrofluorimetric and spectrophotometric determination of PY and MT in synthetic mixtures and in a pharmaceutical formulation. © 2005 Elsevier SAS. All rights reserved. Keywords: Multivariate Calibration; Pyridoxine; Melatonin; Simultaneous Determination

1. Introduction Melatonin (MT, Scheme 1a) and pyridoxine (PY, Scheme 1b) are the two active ingredients in medicinal food for healthcaring purposes. Melatonin (N-acetyl-5-methoxytryptamine) is a natural hormone secreted mainly by the pineal gland during the dark phase of the light–dark cycle [1]. Once released, MT can act on different organs through specific receptors [2] and directly on the hypothalamus influencing the ″circadian″ rhythms [3]. For this reason, melatonin is considered to be potentially useful in the management of various forms of

* Corresponding author. Tel.: +98 912 130 7417; fax: +98 411 334 0191. E-mail addresses: [email protected] (M.-H. Sorouraddin), [email protected] (M.-H. Sorouraddin). 0014-827X/$ - see front matter © 2005 Elsevier SAS. All rights reserved. doi:10.1016/j.farmac.2005.03.009

Scheme 1a. Melatonin structure.

Scheme 1b. Pyridoxine structure.

insomnia and sleep disorders [4]. However, several possibilities for the use of melatonin in therapy should also be taken into account, including jet-lag [5], co-treatment in cancer

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patients [6,7], free radical-related diseases [8], depressive disorders and oral contraception. Recent investigations suggest that melatonin treatment could improve sex life [9], fight the ravages of AIDS [10] and slow the evolution of Alzheimer’s diseases [11] and ageing [12]. Pyridoxine, as one form of Vitamin B6 consisting of pyridoxine (PY), pyridoxamine (PM) and pyridoxal (PL), is an essential vitamin for humans, which possesses many different physiological properties. However, the clinical application of MT as a therapeutical medicine is still under investigation. It would bring about side effects if it is misused or abused. Only some moderate side effects, such as: nightmares, hypotension, sleep disorders, abdominal pain, etc have been reported [13]. For it’s therapeutically properties, MT has been praised as a ’’panacea’’ leading to a great increase in pharmaceutical preparations containing this drug, and consequently, the need to have analytical methods available for quality control is even greater. MT is associated with PY, probably due to the synergetic effect in the therapy of some diseases. Considering that many pharmaceutical forms combine MT and PY, and that the aging or unsuitable storage conditions may lead to the degradation of the investigated drugs, hence there is a real necessity to develop analytical procedures to determine both drugs in the same analysis. Both the excitation–emission and the absorbance spectra of these compound strongly overlap, their direct determination by conventional fluorimetric and spectrophotometric methods are not possible. In spite of the numerous methods reported for the determination of MT or PY in the absence of each other, there are only few methods available for their simultaneous measurements, such as gas chromatography-mass spectrometry [14], zero-crossing derivative spectrophotometry, spectrofluorimetry with preliminary solvent extraction [15] and capillary electrophoresis with electrochemical detection [16]. These methods are time consuming, require complex and expensive instruments or in some cases (derivative methods) have low sensitivity. For pharmaceutical preparation analysis, however, as far as we are concerned, there is no reported method for simultaneous determination of MT and PY using direct spectrophotometry or fluorimetry without the need for any separation step. In the present work, a spectrophotometric and a fluorimetric method was proposed for direct and simultaneous determination of these chemicals using full-spectrum multivariate calibration methods, partial least-squares (PLS) and principal component regression (PCR) without any separation step. The proposed methods are sensitive, simple, fast, reliable and efficient and were successfully used to monitor the MT and PY in commercial drugs (Melatonex). 2. Experimental 2.1. Apparatus and software All fluorescence measurements were carried out with an RF-5301 PC recording spectrofluorimeter (Shimadzu, Kyoto,

Japan) equipped with a xenon lamp source, using 1.0 cm quartz cell with a cell holder kept in a constant-temperature water circulating device, thermo bath TB-85. Spectral bandwidths of excitation and fluorescence spectra were 3 and 5 nm, respectively. All recorded spectra converted to ASCII format by RFPC software. All pH measurements were made with a digital pH-meter (Metrohm 744). Absorption measurements were carried out on a Shimadzu UV-1650 PC spectrophotometer, using 1.0 cm quartz cells. All spectra were saved in ASCII format and in the next step all data were transformed to Excel and MATLAB formats. All fluorimetry and spectrophotometry data were transferred to a PC computer for subsequent manipulation by either PLS or PCR programs. The data were handled using MATLAB software (6.1 version). PLS and PCR were applied using PLS-Toolbox [17]. 2.2. Regents and solutions All experiments were performed with analytical grade chemicals and solvents. Stock solutions with 100 µg ml–1 of Melatonin (Across, USA) and 400 µg ml–1 Pyridoxine hydrochloride (Merck, Germany) were prepared by dissolving the appropriate amount in deionized hot water (70–80 °C) and stored (refrigerated at 4 °C) in brown glass flasks. At this temperature, Pyridoxine and Melatonin were stable for at least 1 week and 1 month, respectively. Working solutions were daily prepared by suitable dilution. A sodium citrate buffer solution (pH 3.2, 0.02 M) was employed for pH adjustment. Melatonex tablets (Sunsorce, Chattem, Inc. USA) labeled to contain 3 mg MT and 10 mg PY were obtained from the market. 2.3. Sample solutions Ten tablets (Melatonex) were accurately weighed and crushed to a powder; a known amount (corresponded to 3 mg MT and 10 mg PY) was then dissolved and extracted in hot water (70–80 °C). The solution was then filtered through a filter paper, transferred into 25 ml flasks, and made up to the mark with deionized water. Synthetic mixtures were made by adding the filtered extract of the excipient (dicalcium phosphate, glyceryl monostearate and magnesium stearate) with hot water (70–80 °C) to the standard binary mixture of these drugs. Spectral acquisition and the calculations were performed in the same manner as described in Sections 2.4 and 2.5. 2.4. Calibration procedure for the simultaneous spectrophotometric determination MT and PY binary mixtures were prepared as follows: appropriate volumes of the drugs standard solutions were transferred into a 10 ml volumetric flask, 1 ml NaOH 1 M was added, shaken briefly and made up to the mark with

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Fig. 1. The composition of Calibration (♦) and Prediction (•) set for spectrophotometric method.

deionized water. The final concentrations were in the ranges 1–22 µg ml–1 for MT and 1–24 µg ml–1 for PY. The composition of calibration and prediction set for spectrophotometric method was shown in Fig. 1. The absorption spectra of solutions were recorded in the range of 250–350 nm. The optimized calibration models for PLS and PCR methods were applied to the spectra of the samples to calculate the concentration of each chemical in the prediction set. 2.5. Calibration procedure for the simultaneous spectrofluorimetric determination MT and PY binary mixture solutions were prepared by transferring 1 ml sodium citrate buffer solution (0.2 M, pH 3.2) into a 10 ml volumetric flasks and adding the appropriate volumes of the drugs standard solutions, shaking and making up to the mark with deionized water. The final concentrations were in the ranges 0.04–1.3 µg ml–1 for MT, and 0.1– 4 µg ml–1 for PY. The composition of calibration and prediction sets for spectrofluorimetry method was shown in Fig. 2. The mixed solutions were thermostated at 25 °C and their emission spectra (324–500 nm) recorded at kex 285 nm. The optimized calibration model for PLS and PCR methods were applied to the spectra of the samples to calculate the concentrations in the prediction set.

3. Results and discussion 3.1. Optimization of the conditions for the simultaneous spectrofluorimetric and spectrophotometry determination of MT and PY in pharmaceutical preparation In order to investigate the possibility of simultaneous determination of MT and PY in their mixtures, the working conditions were optimized as described in Sections 3.1.1 and

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Fig. 2. The composition of Calibration (♦) and Prediction (•) set for spectrofluorimetry method.

3.1.2. Optimum conditions must be such that maximum fluorescence and absorbance spectral separation of MT and PY is achievable with as high as possible fluorescence and absorption intensity. 3.1.1. Fluorimetric determination In order to ascertain whether the simultaneous determination of the mixture components was feasible, the influence of the variables potentially affecting the fluorescence intensity or the position of the emission maxima was studied. The stability of the drug solutions was checked as a function of the preparation time and pH. The fluorescence intensity of PY solutions maintained at 4 °C was found not to vary within 7 days after preparation. MT solutions were stable for at least 1 month at 4 °C. Influence of pH on the fluorescence range and it’s intensity for each drug was studied by adding small volumes of dilute solutions of HCl and NaOH to adjust pH. Maximum excitation (kex 278 nm) and emission (kem 351 nm) wavelengths of MT were constant over pH 1–14. Also there was no change in the fluorescence intensity of MT in the pH ranges 2.8–11.2. Quenching of fluorescence was observed for MT below pH 2.8 and above pH 11.2. This result is in agreement with the decrease in fluorescence quantum yields reported for indole derivatives in highly acidic or basic solutions [18,19]. On the other hand PY has three different excitation and emission spectra versus pH range. Sequentially three different maximum excitation and emission wavelengths were observed for PY over pH ranges 1–14. Maximum excitation and emission wavelengths were 290 and 390 nm in the pH range 1–4, 324 and 390 nm in the pH range 6–9, and finally 310 and 379 nm in the pH range 10–14. In the pH range 2–3.8, the fluorescence intensity of PY did not change. Therefore, optimum pH range for simultaneous determination of MT and PY is 2.8–3.8. In this range of pH, the excitation spectra of MT (kex 278 nm) and PY (kex 290 nm) show

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M.-H. Sorouraddin et al. / Il Farmaco 60 (2005) 451–458 Table 1 Analytical data of the calibration graphs for the determination of melatoninand pyridoxine hydrochloride by fluorimetry

Fig. 3. Excitation and emission spectra of MT (0.2 ppm) and PY (1 ppm) in optimum Condition: (sodium citrate buffer pH 3.2 0.02 M, temperature 25 °C) [MT: kex 278 nm, kem 351 nm]; [PY: kex 290 nm, kem 390 nm].

maximum overlapping (highest excitation and therefore maximum emission intensity), the best separation between emission spectra of MT and PY, and the emission intensity of both drugs remained constant. Hence all experiments were carried out in pH 3.2 and the Common excitation wavelength was set in 285 nm. Emission and excitation spectra of MT (0.2 µg ml–1) and PY (1 µg ml–1) in pH 3.2 are shown in Fig. 3. The extensive overlapping makes it difficult to distinguish between the two compounds in their mixture. Trials involving the use of either acidic or basic media in order to resolve the fluorescence emission spectra of these compounds by either direct or synchronous fluorescence were not successful. Therefore, MT and PY in mixtures were determined by multivariate calibration methods. For pH adjustment in 3.2 two types of buffers were studied. Monocholoro acetate buffer decreased the fluorescence intensity of both drugs even at low concentrations. On the other hand, sodium citrate buffer did not cause any changes in the fluorescence intensity of MT (kem 351 nm) and PY (kem 390 nm) up to 0.03 and 0.09 M, respectively. Therefore, in all fluorimetric measurements, 0.02 M sodium citrate buffer was used for pH adjustment. Increasing temperature in the range 10–40 °C resulted in little decrease in fluorescence intensity, hence the solutions were thermostated at 25 °C (near room temperature) in all experiments. The fluorescence spectra were recorded between 324 and 500 nm, since water scattering spectrum was lying between 308 and 324 nm with kem(max) 317 nm. Table 1 shows analytical characteristics for MT and PY determination under optimum experimental conditions. Detection limit was obtained according to equation µB + 3sy/x, where µB: average of the blank and sy/x: standard deviation of residuals of regression line. 3.1.2. Spectrophotometric determination Absorption spectra of MT did not change over the pH range of 1–14. Absorbance intensity at kmax(278 nm) was nearly constant in this pH range. However, maximum absorbance wavelength of PY varied with pH and were as follows: 290 nm

Compound kex (nm) kem (nm) Linearity range (µg ml–1) Regression equation (F = aC + b) a

Melatonin 285 351 0.04–1.3 676 × C + 5.5

rb CLOD (µg ml–1) (n = 6) c RSD (n = 6) d

0.9995 0.035 0.9% (CMT 0.2 µg ml–1) 0.08

CLOQ (µg ml–1) (n = 6) e

Pyridoxine 285 390 0.1–4 183 × C + 14.5 0.9995 0.075 1.95% (CPY 1 µg ml–1) 0.12

a Relative fluorescence intensity (F) versus concentration (C) of each drug in µg ml–1. b Correlation coefficient. c Limit of detection. d Relative standard deviation. e Limit of quantification.

in pH range of 1–4, 290 and 320 nm in pH range of 5–6, 320 nm in the pH range of 7–9 and 310 nm in the pH range of 10–14. Although in the pH range of 5–9, there is high separation between maximum wavelengths of MT (kmax 278 nm) and PY (kmax 320 nm), however, absorbance of PY in this wavelength is much lower than in the pH range of 10–14. Hence the pH range of 10–14 was taken as the optimum range for simultaneous determination of both drugs and pH 13 (NaOH 0.1 M) was used for all experiments in spectrophotometric determinations. Fig. 4 shows the absorption spectra of standard MT (4 µg ml–1) and PY (4 µg ml–1) solutions in pH 13, which show an extensive overlapping. The univariate analysis method cannot be applied for resolving this mixture. Hence full-spectrum multivariate calibration methods such as PLS and PCR were used for the determination of these components in the same analysis. The characteristics of calibration graph and the statistical parameters for determination of MT and PY with spectrophotometric method under optimum conditions are summarized in Table 2.

Fig. 4. The absorption spectra of MT (4 ppm) and PY (4 ppm) standard solutions in pH 13.

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Table 2 Analytical data from the calibration graphs for the determination of melatonin and pyridoxine hydrochloride by spectrophotometry Compound kmax (nm) Linearity range (µg ml–1) Regression equation (A = aC + b) a rb CLOD (µg ml–1) (n = 6) c RSD (n = 10) d CLOQ (µg ml–1) (n = 6) e

Melatonin 278 1–22 0.0257 × C + 0.005 0.9996 0.5 1.24%(CMT 5 µg ml–1) 1.3

Pyridoxine 310 1–24 0.0357 × C – 0.004 0.9997 0.4 2.6% (CPY 5 µg ml–1) 1.2

a

Absorbance value (A) versus concentration (C) of each drug in µg ml–1. b Correlation coefficient. c Limit of detection. d Relative standard deviation. e Limit of quantification.

3.2. Multivariate analysis Multivariate calibrations such as PCR and PLS methods involve the decomposition of the experimental data, such as spectrofluorimetric and spectrophotometric data in this case, into systematic variations (principal components or factors) that explain the observed variance in data. The purpose of both methods is to build a calibration model between the concentration of the analyte under study and the factors of the data matrix. The main difference between PLS and PCR methods is in the process of the decomposition of the experimental data. PCR performs the decomposition of data matrix into principal component without using the information about the analyte concentration. On the other hand, PLS performs the decomposition using both spectrum data matrix and analyte concentration [20]. The first step in the simultaneous determination by PCR and PLS methods, involves constructing the calibration matrix for the binary mixture. In this study calibration sets were optimized with the aid of the orthogonal design method [21]. Figs. 1 and 2 show the composition of the calibration and prediction samples. The ranges of concentrations used for MT and PY were 0.1–1 and 0.5–3 µg ml–1 in spectrofluorimetric method, respectively, and there were 1–10 µg ml–1 in spectrophotometric method, for both. These intervals were at the linear ranges of the analytes. In the calibration procedure for these two methods, the first step is to select the optimum number of factors, which depend on the number of independent chemical variables, and other sources of systematic signal variation, such as any interactions between the chemical components, changes of shape of the component peak and detector noise [20]. Fig. 5 shows the individual spectrums, mixtures and sum of the spectrums for MT and PY in spectrofluorimetric (A) and spectrophotometric (B) methods. As can be seen from the figures, there are not any interactions between analytes, and the signals have very good additive properties. To select the number of factors in PLS and PCR and in order to model the system without over fitting the concentra-

Fig. 5. A) Emission spectra of MT (0.2 ppm), PY (1 ppm) and their mixture in theoretical (THEO) and optimum experimental (EXP) condition. B) Absorption spectra of MT (4 ppm), PY (4 ppm) and their mixture in theoretical (THEO) and optimum experimental (EXP) condition.

tion data, a cross-validation method [22] leaving out one sample at a time, was used. Given the set of calibration spectra corresponding to the samples that shown in Figs. 1 and 2, the PLS and PCR on calibration spectra were performed. Using this calibration, the concentration of the compounds was predicted in the sample left out during calibration. This process was repeated 50 and 60 times for spectrophotometry and fluorimetry methods, respectively, until each sample had been left out once. The predicted concentrations of the compounds in each sample were compared with the known concentrations of the compounds in this reference sample, and the prediction error sum of squares (PRESS) was calculated. The PRESS was calculated in the same manner each time when a new factor was added to the models. These calibrations were repeated for one to 10 principal components, which were used in the PLS and PCR modeling. This procedure was repeated for each analyte. For finding the smallest model (the

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fewest number of factors), the F-test was used to carry out the significance determination [23]. Figs. 6 and 7 show a plot of the PRESS against the number of factors for each individual analyte. In all cases, two factors were selected as optimum number of factors. Also, when a plot of PC2 versus PC1 (corresponding to a PCA model) is made (Fig. 8), the score matrix is certainly rotated and not very distorted with respect to the calibration matrix (Figs. 1 and 2). In fact, the distribution of the scores in the plane formed by these first two PCs reproduces the experimental design used (Figs. 1 and 2). This confirms that two factors are enough to construct a PCR calibration model. The same results were obtained from PLS method [24].

Fig. 7. Plot of PRESS against the number of factors for MT and PY in spectrophotometric method.

The prediction error of a single component in the mixture was calculated as the relative standard error (RSE) [25]: RSE = 100 ×

冉

兺

共 C Pre. − C Pre. 兲 `

兺 共 C Pre. 兲 2

2

冊

1⁄2

(1)

^

where CPre. andCPre. are the experimental and calculated concentration for prediction samples, respectively.

4. Application in synthetic and real samples

Fig. 6. Plot of PRESS against the number of factors for MT and PY in spectrofluorimetric method.

The proposed methods were evaluated in the assay of synthetic mixtures and commercial tablets (Melatonex). Table 3 shows the results obtained by the application of the PCR and PLS models on the prediction sets, synthetic samples, and a pharmaceutical formulation (Melatonex tablet). Five replicate determinations were carried out on each experiment. These results confirm satisfactory to the label claim, synthe-

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Table 3 RSE for prediction sets, tablet and syntheticsamples in spectrofluorimetric (A) and spectrophotometric (B) methods A

Spectrofluorimetry PCR

Prediction set Synthetic samples Tablet B

Melatonin 3.3 4.5 7.0

PLS Pyridoxine 4.4 5.2 5.8

Melatonin 3.1 4.5 6.7 Spectrophotometry

Pyridoxine 3.0 3.5 5.6

Melatonin 2.0 4.1 6.0

PCR Prediction set Synthetic samples Tablet

Melatonin 2.1 4.3 6.2

Pyridoxine 4.4 5.0 5.6 PLS Pyridoxine 2.8 3.3 5.4

simplicity and speed, which render them suitable for routine analysis in control laboratories. In addition, spectrofluorimetric method possesses the advantage of high sensitivity (expressed by the detection limits), which may be an incentive to other workers to consider it for the biological fluids. Moreover, utilizing chemometrics widens the applicability of both spectrophotometry and spectrofluorimetry to some areas, which is not considerable without it.

Acknowledgments The authors sincerely thank professor Rainer Haag and Mr. Mohsen Adeli, Organische Chemie, Universität Dortmund, Germany for cooperation and Dr. Hamid Abdollahi, Department of Chemistry, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran for his valuable comments.

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sized concentration and indicate the high precision and accuracy of the proposed methods when applied to tablets.

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5. Conclusions Spectrophotometry and spectrofluorimetry are suitable techniques for the reliable analysis of combination of MT and PY either in a pure form or in their mixtures such as tablets. The most striking features of the methods are their

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