Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
Simultaneous chemiluminescence determination of thebaine and noscapine using support vector machine regression
Introduction
Opiates were originally available from the opium poppy (Papaver somniferum), native in Asia Minor. Noscapine and thebaine are alkaloids commercially extracted from ‘opium poppies’. Opiates and their derivatives are very potent analgesics [1]. Noscapine is the second most alkaloid in opium, present in concentrations of 2–8% [2].
Several analytical technique have been developed for the simultaneous determination of noscapine and thebaine such as liquid chromatography [3], [4], capillary electrophoresis [5], [6], gas chromatography–mass spectrometry [7], [8], circular dichroism [9], and automated multiple developments TLC [10]. Chemiluminescence analysis (CL) has been attracted because of its sensitivity, relative ease of application, and inexpensive instruments required. However, the method suffers from the lack of selectivity in the case of structurally similar compounds and/or similar reactions. In recent years, a combination of powerful multivariate calibration methods and some analytical techniques has been used to allow for the simultaneous determination of multi-component compounds without previous separation [11].
This work is based on the difference in the chemiluminescence reactions between Ru(bipy)32+ and acidic Ce(IV) in the presence of noscapine and thebaine. Least squares support vector machine (LS-SVM) regression models were constructed to relate CL profiles of the compounds to their concentrations. These models were able to predict noscapine and thebaine concentrations in pharmaceutical formulations and spiked plasma samples.
Support vector machines (SVMs) based on statistical learning theory, introduced by Cortes and Vapnic [12]. Least square support vector machines are an alternate formulation of SVM described by Suykens et al. [13]. Linear least square models attempt to correlate the spectrum xi and reference value yi, of all samples in X. The X represents a [n × p] matrix containing p spectral responses of n samples. The yi and xi denotes the ith column of Y and X, respectively. Y is computed by following equation:where B is a [p × 1] vector of coefficients and b0 is the model offset. SVMs regression is based on kernel substitution where X is replaced by a [n × n] kernel matrix (K). K is defined as:where ki,j is defined by the kernel function:
Kernel functions are defined as any function in input space that corresponds to an inner product in some feature space. The idea of the kernel function is to map data point from input space to high dimensional feature space where points are linearly separable. There are number of kernels that can be used in support vector machines. These include linear, polynomial, radial basis function (RBF) and sigmoid function. The RBF is by far the most popular choice of the kernel types because of their localized and finite responses across the entire range of the real x-axis. Implementation of LS-SVM requires the specification of only two parameters, kernel parameter and gamma, which controls the tradeoff between maximization of margin width and minimizing the number of missclassed sample in the training set. If parameters were not properly selected overfitting and/or under filling phenomena might occur.
Section snippets
Reagents and solutions
All chemical solutions were prepared using reagent grade chemicals and doubly distilled water.
Noscapine and thebaine standard solutions (0.10 mg mL−1) were prepared daily by dissolving 10.0 mg of each compound (Sigma–Aldrich, Germany) in 100 mL of water, stored in a refrigerator and protected from light. The working solutions were prepared by appropriately diluting the stock solution with water.
Ru(bipy)32+ stock solution (1.0 × 10−2 mol L−1) was prepared by dissolving 0.3740 g of
Kinetic profile of CL reaction of Ru(bipy)32+–acidic Ce(IV)-noscapine and thebaine
In the batch CL mode, we found that light emission-time profile for noscapine was narrow with a high CL intensity at about 0.6 s, whereas the CL intensity of thebaine was broad with the highest intensity at about 2.0 s after mixing of the reactants. Kinetic profiles of thebaine and noscapine in the batch mode are shown in Fig. 2. Generally, batch and flow methods are two basic sample-injection modes commonly used for CL analysis. The batch mode has such advantages as minimized reagent consumption
Univariate calibration graph
Under the optimized conditions including Ce(IV) = 3.0 × 10−3 mol L−1 and Ru(II) = 3.0 × 10−3 mol L−1 and 0.085 mol L−1 H2SO4, the CL signal was found to be linear in the concentration ranges of 0.5–5.0 μmol L−1 noscapine and 1.0–50 μmol L−1 thebaine with the linear equations of ICL = 0.585Cnoscapine + 0.515 (r2 = 0.98) and ICL = 0.0194Cthebaine + 0.650 (r2 = 0.9750), respectively, where ICL is CL intensity and C is the concentration of the drugs in μmol L−1. Under the optimized experimental conditions for both compounds, the
Multivariate calibration graph
The LS-SVM regression was constructed using a radial basis function (RBF) as a kernel function. The parameters of the model consisting of γ and δ2 form the critical steps for the performance of the model. Each of the parameters was changed from 1 to 2000 and LS-SVM models were constructed with all the possible combinations of the parameters. A training set of 25 samples was prepared using a full factorial design. Then, for each combination of γ and δ2, the root mean squared error of cross
Interference study
In order to find the selectivity of the proposed method, the interference effects of some organic and inorganic compounds commonly present in human serum and also some redox active compounds were studied by recovering 2.0 μmol L−1 of noscapine and/or thebaine in the presence of potential interfering substances. The tolerance of each substance was taken as the largest amount yielding an error of less than 3σ in the analytical signal of 2.0 μmol L−1 of noscapine and/or thebaine (σ is the standard
Application
To evaluate the applicability of the proposed method, the recovery of noscapine and/or thebaine was determined in plasma as spike sample and in some drug samples. The standard addition method was used for the analysis of the prepared samples. The data are given in Table 4. In addition, the prediction results using LS-SVM were compared with HPLC-UV as an official method [21]. Comparisons of the prediction capabilty of the proposed method and the HPLC method for determination of noscapine and/or
Conclusion
A new CL method was introduced for simultaneous determination of thebaine and noscapine at trace levels without any separation. The chemiluminescence method combined with LS-SVM as a multivariate calibration method was found suitable for the simultaneous determination of the two structurally similar alkaloid compounds. The method is not only a simple procedure, but is also a fast technique. In addition, the method is capable of analyzing both compounds in plasma samples.
Acknowledgements
The authors express their appreciation to the Isfahan University of Technology Research Council and Center of Excellence in Sensor and Green Chemistry for their financial support.
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