Journal of Pharmaceutical and Biomedical Analysis 72 (2013) 251–260
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Development and validation of a high performance chromatographic method for determining sumatriptan in niosomes M.J. Cózar-Bernal ∗ , A.M. Rabasco, M.L. González-Rodríguez Department of Pharmaceutical Technology, Faculty of Pharmacy, University of Seville, Spain
a r t i c l e
i n f o
Article history: Received 17 May 2012 Received in revised form 23 August 2012 Accepted 31 August 2012 Available online 7 September 2012 Keywords: Sumatriptan succinate Reversed-phase HPLC (RP-HPLC) Method validation Factorial design Taguchi Robustness
a b s t r a c t In this paper, a novel, precise, specific, accurate and rapid reversed-phase high performance liquid chromatographic method was developed, optimized and validated for determining sumatriptan succinate in niosomes with the best chromatographic peak resolution, reduced run time and low cost of analysis. The formulation has been previously optimized in terms of composition and preparation technique to obtain a high drug encapsulation efficiency and adequate vesicle size distribution. This method showed the best resolution by using Spherisorb® OSD2 C18 column (250 mm × 4.6 mm, 5 m) using phosphate buffer (0.05 M):acetonitrile (80:20, v/v; pH adjusted to 6.0) as a mobile phase at a flow rate of 1 mL/min and wavelength of 214 nm. The main objective of this research was to demonstrate the robustness of the reversed-phase HPLC method development by applying the Taguchi robust methodology. The signal-to-noise ratio (S/N) was employed as a quality measurement. This tool permits to establish the influence of some selected factors (acetonitrile:phosphate ratio, pH buffer, oven temperature and flow rate) on two responses (peak areas and retention time). On the basis of the results obtained, we can conclude that this analytical method was robust for all the factors studies, as exception of the flow rate, where the higher quality was obtained for the fewer values (0.8 mL/min). Therefore, this parameter must be carefully controlled when this method was employed, to avoid any modification in the peak areas overall. © 2012 Elsevier B.V. All rights reserved.
1. Introduction Sumatriptan succinate is a selective serotonin 5-HT agonist at the 5-HT1B and 5-HT1D receptors. It was the first of the so-called “triptan” drugs which have had a significant impact on the treatment of acute migraine episodes and it is available in several dosage forms including products for oral, nasal and parenteral delivery [1]. Despite the oral route could become the definitive step towards the control of migraine episodes, important problems leading to a very low oral bioavailability of sumatriptan have discouraged its clinical application [2]. During the last decade, there has been a continuous interest in the use of colloidal drug delivery systems for the development of sumatriptan delivery systems able to prolong their therapeutic effect. The use of colloidal drug delivery systems, such as liposomes and niosomes, is a suitable strategy to enhance the bioavailability of topically administered drugs, because they offer unique features while preserving the ease of delivery in liquid form [3,4].
∗ Corresponding author at: Department of Pharmaceutical Technology, Faculty of Pharmacy, University of Seville, n◦ 2, 41012 Sevilla, Spain. Tel.: +34 95 4556397; fax: +34 95 4556085. E-mail address:
[email protected] (M.J. Cózar-Bernal). 0731-7085/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jpba.2012.08.030
Niosomes attract much attention because of their advantages in many aspects, such as chemical stability, high purity, content uniformity, low cost and convenient storage of non-ionic surfactants, and the existence of a large number of surfactants available for the design of these vesicles [5,6]. With this aim, sumatriptan-loaded niosomes were engineered. However, it is important to develop a specific analytical technique for quantifying the drug from these formulations to have adequate results. Most of the analytical methods found in the literature, carried out by high-performance liquid chromatography (HPLC) to determine sumatriptan, are aimed at quantifying this substance in plasma and pharmaceutical formulations [7–9], to determine the raw material and its related substances. However, neither of the described methods by HPLC was dedicated to the study of sumatriptan from lipid vesicles as final products. When an analytical method has been developed, it is important to confirm that it is suitable for its intended purpose. Therefore, the method validation is today an essential concern in the activity of analytical chemistry laboratories. Taguchi’s methodology has been widely applied to the pharmaceutical process design. This methodology constitutes a strategy that involves the use of mathematical and statistical tools to obtain the maximum information through the experimental data and
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to find the optimal conditions for the execution of a particular experimental process. Three specific tools have been used, namely orthogonal arrays, the signal-to-noise ratio (S/N) and analysis of variance (ANOVA) [10]. Successful application of Taguchi method is able to allow operating conditions to be optimized with a minimized sensitivity to noise (a hard-to-control variable). In this approach, the S/N ratio has been introduced as a measurement of the quality characteristic deviating from the desired value. It is also used the S/N ratio to convert the experimental results into a quality parameter to evaluate the optimum analysis [11]. So, the experimental condition having the least variability as the optimum condition can be determined. Also, Taguchi methods are used for maximizing the robustness of products and processes, thereby achieving high quality at a low cost and time. Robustness is essential in the production of nearly all products. The variation in the quality of the product may vary from environmental factors and/or manufacturing variables that cannot be easily controlled. Such factors are called ‘noise factors’. The Taguchi method uses the S/N ratio, which is directly transformed from the quadratic quality loss function, as a measure to determine the robustness of a process. Thus, optimizing process parameters by means of Taguchi method is an attempt not only to bring the average quality near to the target value, but also to simultaneously to minimize the variation in quality. So, S/N ratio is the best index to measure quality in a robust method and it shows the magnitude of the interaction between ‘control factors’ and ‘noise factors’ [12] as showed many authors [13–16]. In this work, two main purposes have been planned. First, the validation process of the analytical method by HPLC for the determination of sumatriptan in niosomes, describing validation parameters stated both by USP 29 and by the ICH guidelines to achieve an analytical method with acceptable characteristics of suitability, reliability and feasibility, ensuring that the findings achieved, when this method was applied, were correct. On the other hand, the Taguchi optimization methodology has been proposed to optimize robustness parameter in this validation process. 2. Materials and methods 2.1. Chemical and reagents Sumatriptan succinate (SS) was received as a gift sample from Glaxo Smith Kline (Brentford, UK). Chloroform, 4-(2hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES), potassium di-hydrogen phosphate, acetonitrile HPLC quality, HCl 37%, sodium hydroxide and hydrogen peroxide 33% (v/v) were received from Panreac Chemistry (Barcelone, Spain). Stearylamine (SA) was purchased from Fluka-Biochemika (Switzerland). Cholesterol (CH) was obtained from Sigma–Aldrich (Barcelone, Spain). Eumulgin® B2 was obtained from Acofarma (Barcelone, Spain). Deionized and purified water using a Milli-Q system (Millipore) was selected as solvent for the standard solutions preparation. All other reagents used in this study were of analytical grade.
5 m). The mobile phase consisted of phosphate buffer (0.05 M):acetonitrile (80:20, v/v) adjusted to pH 6 with sodium hydroxide (0.05 M). The mobile phase was filtered through a 0.22 m nitrocellulose-membrane filter (Millipore, Barcelone, Spain) and degassed under vacuum prior to use. Absorbance was measured at 227 nm and the flow rate was 1 mL/min. The injection volume was 10 L. Peak areas were measured and high-performance liquid chromatography analysis was conducted at room temperature. 2.3. Preparation of sumatriptan niosomes and determination of drug content into vesicles Multilamellar vesicles (MLV) were prepared by a modification of the thin film-hydration method. Briefly, Eumulgin® B2 as non-ionic surfactant was completely dissolved in about 8 mL of chloroform. This solution was deposited as a thin film in a round-bottom flask by rotaevaporating the chloroform under vacuum. Then, 5 mg of SA and a constant amount of CH (3:1 surfactant/CH molar ratio) were added. The mixture was again dissolved in about 8 mL of chloroform and again rotaevaporated to remove the organic solvent and to form a lipid thin film. The vacuum was applied for 1 h to ensure the total removal of trace solvents. The film was then hydrated by adding 6 mL of the hydrophilic phase, containing 15 mg of SS dissolved in HEPES 10 mM. Samples were submitted to five vortexing cycles (each cycle consisting in stirring for 2 min and heating at 58 ◦ C for 5 min) until vesicle formation. The temperature was maintained at 58 ◦ C until the end of the process, above the gel–liquid transition temperature (Tc ) of the amphiphilic and lipid substances. All formulations were quickly sealed in glass containers and stored in the dark at 4 ◦ C. The composition of this formulation has been selected on the basis of previously reported works (data not shown). 2.4. Standard and sample solutions Standard solutions of SS at a concentration of about 2.5 mg/mL have been prepared by dissolving the appropriate amount of SS (2.5 mg) in 1 mL of deionized water. This standard solution will be used to compare with the drug amount in the final product. These solutions have been stored in the dark under refrigeration at 4 ◦ C and have been found to be stable for several weeks. The stability of the standard solutions has been checked over this period by preparing and injecting daily a solution of the analyte. To carry out the sample solution preparation (assay of pharmaceutical preparation), an appropriate amount of niosomes equivalent to 2.5 mg of SS was placed in a 1 mL volumetric flask with 500 L of methanol. This sample was vortexed for 5 min and diluted to volume with water, and was finally filtered through a 0.22 m nylon-membrane filter (Millipore, Barcelone). The resulting filtered solution was placed in a HPLC vial and injected. 2.5. Validation study
2.2. Chromatographic system The chromatographic apparatus consisted of a Hitachi Elite LaChrom, equipped with a quaternary pump L-2130, a diode array detector L-2455, an automatic injector L-2200 and oven L-2350. For data collection and calculation, EZChromElite Data System Manager Software was used. The chromatographic conditions were used as previously described [17]. This analytical method was optimized by using a column C18 (Waters, Spherisorb® OSD2 250 mm × 4.6 mm,
The method was validated in agreement with the International Conference on Harmonization Guidelines (ICH Q2(R1)), using the following parameters: linearity, precision, accuracy, specificity, detection and quantitation limits and robustness. 2.5.1. System suitability A system suitability test has been performed by injecting the SS solution six times into the HPLC system. From these injections, the RSD was calculated.
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2.5.2. Specificity Specificity is the ability to assess unequivocally the analyte in the presence of components, which may be expected to be present. Typically these might include impurities, degradants, matrix, etc. In this assay, different solutions containing the formulation components in the same quantities and conditions than in samples (placebo sample) were tested, to show that there are not peaks in the retention times corresponding to the analyte. Each solution was injected into the chromatograph, according to the conditions described in the analytical method. The method specificity was evaluated onto three placebo samples and standard solution of SS. Each sample was injected in duplicate. 2.5.2.1. Forced degradation studies. Within the selectivity study, a series of degradation studies were carried out, where the standard solutions and the working samples were subjected to different degrees of stress, by following the ICH guidelines. The forced degradation study was performed by exposing the drug standard to some conditions for several hours and comparing the chromatograms of each condition. The effect of pH was studied after contacting drug standard solutions with appropriate [H+ ] (1 N HCl) or [OH− ] (1 N NaOH) during 24 h. The oxidative degradation was studied by exposing the solutions to H2 O2 (3%, v/v). The effect of exposure to light was studied by placing several flasks [6] containing the drug standard solution under ambient or UV (254 nm) light during 24 h. To check the effect of temperature and ultrasounds on drug degradation, samples were kept during 1 h into an ultrasonic bath thermostatized at 60.0 ± 0.5 ◦ C. After the stress assay, the samples were analyzed by HPLC. 2.5.3. Linearity Linearity is the ability of the method to respond proportionally to the changes in concentration or amount of the analyte in a sample. The linearity study verifies that the sample solutions are in a concentration range where analyte response is linearly proportional to the concentration. This study was performed by evaluating the system and method linearities. This analytical parameter was determined by calculating a regression line from the peak area vs. concentration plot for five standard solutions (1.25, 1.875, 2.5, 3.125 and 3.75 mg/mL) using the method of least squares, and by analysis of the respective response factors (i.e. peak area divided by concentration of each standard sample). In order to confirm the linearity, the variance homogeneity has been checked. For this purpose, the Cochran test was carried out, indicating whether the concentration factor has any influence on the variability of results. For this, the experimental value of G (Gexp ) was calculated as follows: Gexp =
Varmax
k
1
var
where Varmax is the maximum variance and var is the variance value for each concentration. The variance homogeneity was demonstrated if Gexp value is less than tabulated value of G (Gtab ). In our study, the tabulated value Gtab (p = 0.05, n = 3, K = 5) equals 0.6838. If the variance homogeneity is proved, we proceed to calculate the regression line for the same concentration and corrected areas, by the method of least squares. If the variance homogeneity does not comply, the range of data that satisfy this parameter must be investigated. In this range, we proceed to calculate the regression line for the same concentration and corrected areas, by the method of least squares. The obtained areas for each concentration are plotted versus concentration. If
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there is a linear relationship, test results should be evaluated by calculation of a regression line by the method of least squares. Also, the proportionality test was checked. This test is a test “Student’s t” which indicates that the intercept is not significantly different from zero. For sumatriptan, in this study, the experimental value of Student’s-t (texp ) must be less than 1.7613, which is the tabulated value of Student’s-t (ttab ) at p = 0.05 and 14 total degrees of freedom. Finally, the slope test was studied. The response function for an analytical procedure is the existing relationship, within a specific range, between the response (area) and the concentration of the analyte in the sample. For each concentration level, the response factor will be calculated as follows: f =
area concentration
These values are plotted versus the concentration and a straight line must be obtained. 2.5.4. Limit of detection (LOD) and limit of quantification (LOQ) The LOD is defined by the USP as the lowest concentration of analyte that can be detected, but necessarily not quantified. The LOQ is the lowest concentration in a sample that may be measured within an acceptable level of accuracy and precision, under the selected experimental conditions. This value must be lower than or equal to the reporting level or reporting threshold (RTH), as defined in ICH Q3B guidelines, which is based on maximum daily dose (MDD) for any drug product. LOD is defined for a peak that gives a signal-to-noise ratio of about 3:1, and LOQ is defined for a peak that gives a signal-to-noise ratio of about 10:1. In this paper, these parameters were determined based on the response and slope of a calibration curve obtained from six standard solutions, which are near to these limit concentration values. The range selected from 0.01% to 0.1% of the target value and the most diluted standard solution with a linear response was considered the LOQ. 2.5.5. Accuracy The test for accuracy is intended to demonstrate the closeness of agreement between the value found and the value that is accepted either as a conventional true value or as an accepted reference value. Therefore, accuracy can be defined as the agreement between the result obtained and an accepted reference value. 2.5.5.1. Recovery. The accuracy can be demonstrated by recovering the substance spiked into a placebo formulation. The recovery method was studied at concentration levels of 50% (I), 75% (II), 100% (III), 125% (IV) and 150% (V), where a known amount of the active was added to a given amount of placebo solution. The amount of SS recovered in relation to the added amount (recovery percent), was determined by an external calibration standard. 2.5.6. Precision Precision provides some information about the random errors and can be divided into repeatability and intermediate precision. Repeatability involves the analysis of replicates by the same analyst. This parameter is divided into: injection repeatability and analysis repeatability. 2.5.6.1. Injection repeatability. It is based on multiple injections of a single preparation of a sample in a specified day. For sumatriptan, a same standard solution of drug (2.5 mg/mL) was injected 10 times, and the RSD was calculated. Similarity, the same sample solution was treated.
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Table 1 Factors and their levels included in the Taguchi orthogonal design L9 . Factor
ACN in the mobile phase pH buffer Oven temperature (◦ C) Flow rate (mL/min)
Table 2 Experimental matrix corresponding to the orthogonal array L9 .
Level −1
0
+1
18 5.8 24 0.9
20 6.0 25 1.0
22 6.2 26 1.1
2.5.6.2. Intermediate precision. The aim of this study consists at establishing the effects of the random events on the analytical method. This parameter was performed by different analysts, on a different day and on different samples. 2.5.7. Robustness The robustness of any analytical procedure according to ICH is “a measure of its capacity to remain unaffected by small, but deliberate variations in method parameters and provides an indication of its suitability during normal usage”. Prior to evaluation of robustness testing, a set of system suitability must be established. Typically, these system suitability criteria and their respective ranges are defined during the method development. During the evaluation of robustness testing, the series of system suitability requirements must be met to ensure that the validity of the analytical procedure is maintained whenever used. For the determination of robustness of analytical method, some chromatographic parameters were varied within a real range, and their quantitative influence on the response variables was determined. The obtained data from these effects will allow to judge whether a method needs to be revalidated when one or more parameters are changed. For this, a fractional factorial design has been used, to analyze multiple factors minimizing time-consuming and economical cost. The selected design was Taguchi approach, which provides a mathematical tool, called the orthogonal arrays and allows the analysis of a large numbers of design parameters using only a limited number of experimental runs. As was exposed in the introduction section, a key concept in the Taguchi methodology was to quantify losses, which occur because of poor quality, using “loss functions” that increase in proportion to the square of the deviation of the performance from the target. The uncontrollable factors which cause the functional characteristics of a product to deviate from their target values are called noise factors. The overall aim of quality is to make products that are robust with respect to all noise factors. Typically, factors are chosen symmetrically around a nominal value, forming an interval that slightly exceeds the variations that can be expected when the method is implemented or transferred [18–24]. Table 1 illustrates the factorial design study for four factors: ACN percent in the mobile phase, pH of the buffer solution, oven temperature and flow rate. Once selected the factors, the experimental matrix to be developed is shown in Table 2. The design was generated by using DOE Pack® 2000 software. Once the design has been chosen and fixed the factors and their levels, responses to be evaluated were generated: retention time and peak area of drug standard solution. Then, from the chromatographic data generated, data must be analyzed, by means of the ANOVA test and other statistical studies, such as the marginal means of factors. The aim of this study was also to demonstrate that Taguchi design was an appropriate design for robustness testing, because this methodology constitutes a systematic approach for studying the effects of multiple factors. In this work, the Taguchi method for the design of experiment, signal-to-noise ratio (S/N ratio), analysis
Run
ACN (%) in the mobile phase
pH buffer
Oven temperature (◦ C)
Flow rate (mL/min)
1 2 3 4 5 6 7 8 9
18 18 18 20 20 20 22 22 22
5.8 6.0 6.2 5.8 6.0 6.2 5.8 6.0 6.2
24 25 26 25 26 24 26 24 25
0.9 1.0 1.1 1.1 0.9 1.0 1.0 1.1 0.9
of means (ANOM) and analysis of variance (ANOVA) have been applied to accomplish the planned objectives.
3. Results and discussion 3.1. Method development In this study, a RP-HPLC method for the determination of SS in niosomes has been developed and validated with the best chromatographic peak resolution. This method permits the analysis of a large series of samples, avoiding possible degradation associated to a long analysis time. A simple sample preparation, short separation time and a low LOQ were considered when the study started. The aim for sample preparation method was to remove the interferences from the other niosome constituents to be reproducible with a high recovery involving a minimum number of working steps.
3.2. Specificity The peaks were separated with a retention time at around 8 min. Possible interferences by other substances in the dissolution medium were also tested by comparing the chromatograms. It was observed the absence of interferences because none of the peaks appears at the same retention time than sumatriptan peak. No peaks from possible degradation products were observed in the chromatograms, corroborating the purity of the sumatriptan used in the study and its stability in standard solutions. Thus, the HPLC method is selective for sumatriptan and the other related compounds, which coexist in the synthesis processes. The specificity was also demonstrated by inducing the degradation of sumatriptan (Table 3). The stress studies involving heat, sunlight, acid and ultrasounds revealed that around 15% was degraded. On the other hand, the UV light and the alkaline conditions revealed that around 20% of sumatriptan succinate was fully degraded. According to the areas obtained, it can be concluded that the drug is unstable in these conditions.
Table 3 Degraded percentage of sumatriptan succinate standard after the forced stress degradation test. Stress condition
Mean (%) degraded
SD
UV Heat Acid Basic Peroxide Ultrasound Sunlight
19.04 14.68 17.02 21.02 9.83 15.20 15.81
0.06 1.93 0.89 1.10 0.97 1.86 0.45
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Table 4 Data corresponding to sumatriptan succinate standard solutions for determining the system linearity. Level (%)
Replicate
Final concentration (mg/mL)
Area (mAU s)
I (50%) II (75%) III (100%) IV (125%) V (150%)
3 3 3 3 3
1.250 1.875 2.500 3.125 3.750
23,002.3 34,537.5 45,036.5 58,714.2 71,093.0
Mean f SD f RSD (%) Slope of f Gexp
Response factor (f) 18,397.3 18,415.4 18,010.1 18,783.9 18,902.9
Variance 4307.2 249,177.1 566,47.8 205,812.1 849.7
18,501.92 349.45 1.89 0.00454 0.4821
3.3. Linearity The purpose of this test was to demonstrate that the entire analytical system exhibits a linear response and was directly proportional over a relevant concentration range for the target concentration of the analyte. According to the preparation method of sample, the 100% test solution concentration was 2.5 mg/mL. Then, the linearity was evaluated from 50% (1.25 mg/mL) to 150% (3.75 mg/mL) of the test solution concentration. Results were reported in Table 4. The calibration curve obtained by plotting the SS peak area versus the concentration of standard solution was linear in the above mentioned concentration range. The equation of the regression line obtained, with all the values, relating the tested concentrations and the response obtained corresponds to y = 19192x − 1554.3 (y: SS concentration (mg/mL); x: peak area, with a standard error of 821.9866 and a correlation coefficient that exceeds 0.9989 (n = 15). With respect to the method linearity, the regression line (y = 116,264.13x + 127.198) showed a good linearity in the same concentration range, obtaining a correlation coefficient (r) of 0.999 (n = 15)). Also, from the statistical analysis of ANOVA corresponding to the collected data for both system and method linearity, the F test statistic (F) and its corresponding
Fig. 1. Graphical representation of the response factors corresponding to different sumatriptan succinate standard solutions vs. concentration.
Table 5 Recovery percentages of sumatriptan from niosomes sample (100% level corresponds to 2.5 mg/mL of sumatriptan). Replicate Recovery 50% Sample 1 Sample 2 Sample 3 Average Recovery 75% Sample 1 Sample 2 Sample 3 Average Recovery 100% Sample 1 Sample 2 Sample 3 Average Recovery 125% Sample 1 Sample 2 Sample 3 Average Recovery 150% Sample 1 Sample 2 Sample 3 Average
Area (mAU s)
Theoretical concentration (mg/mL)
Corrected Area
Real concent
Recovery (%)
23,045 22,927 23,035
1.250 1.250 1.250
23,039.41 22,921.04 23,029.28
1.281 1.275 1.281
102.49 101.99 102.45 102.31
34,099 34,655 34,968
1.875 1.875 1.875
34,090.48 34,645.98 34,958.97
1.857 1.886 1.902
99.03 100.57 101.44 100.35
45,994 45,861 45,307
2.500 2.500 2.500
45,982.50 45,849.54 45,296.05
2.477 2.469 2.441
99.05 98.77 97.62 98.48
58,211 59,093 58,838
3.125 3.125 3.125
58,196.88 59,078.19 58,823.53
3.113 3.159 3.146
99.60 101.07 100.65 100.44
71,059 71,111 71,109
3.750 3.750 3.750
70,852.68 70,904.27 70,901.67
3.772 3.775 3.775
100.31 100.38 100.38 100.36
Average recovery of samples SD recovery of samples RSD (%)
100.39 1.45 1.44
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Table 6 Peak area values of sumatriptan succinate standard and niosomes samples (2.5 mg/mL) for intermediate precision study. Days
Standard
Standard/Sample 1
Sample
Day 1
Day 2
Day 1
Day 2
Analyst X
45,537.02 46,094.93
45,399.20 46,106.46
45,357.01 45,192.85
44,489.18 44,786.25
Analyst Y
45,111.44 45,221.27
45,391.82 45,360.67
45,789.75 45,254.09
Analyst X
44,512.18 43,224.60
43,338.93 44,400.51
44,871.92 45,106.46
Analyst Y
45,576.71 45,207.57
45,800.92 45,793.27
44,967.32 44,746.58
RSD% = 0.80%
RSD% = 0.45%
RSD% = 0.29% Standard/Sample 2
45,162.17 44,923.74 RSD% = 0.99%
RSD% = 1.55%
44,895.17 43,846.38 RSD% = 1.06% 44,323.79 44,456.12
RSD% = 0.61%
RSD% = 0.88%
RSD% = 0.81%
RSD% = 0.85%
p-value (significance F) certainly indicate an overall goodness of fit for the model (p = 6.56E–19 for system linearity and p = 1.77E–20 for method linearity). To enhance the quality of the results, other linearity assessment methods have been studied. Thus, an analysis of the response factors for the proposed range was performed. The visual inspection and linear regression (y = 220.34x + 17,950) by the method of least squares revealed that the response factors plot (peak area divided by concentration at each standard sample concentration level) vs. standard sample concentrations showed a near zero slope (0.00454) and RSD of 1.89% considering all the standard concentration levels, thus reinforcing the evaluation of the method as linear. From the variance obtained for each level, the Gexp was calculated, considering the Varmax = 249,177.09, Gexp = 0.4821, thus the variance homogeneity was demonstrated, because this value is lower than tabulated one (0.6838). Additionally, the correlation coefficient obtained (0.998) is higher than 0.995. On the other hand, the Student’s t-test indicates that the intercept is not significantly
different to zero. The texp is 1.00 (
