Green quality by design HPLC approach for the simultaneous determination of Bilastine and Montelukast
BMC Chemistry volume 17, Article number: 43 (2023)
For the simultaneous estimation of two co-formulated antihistaminic drugs (Bilastine and Montelukast), a novel and eco-friendly reversed-phase HPLC approach with both diode array and fluorescence detection modes was designed. Rather than using the routine methodology, the Quality by Design (QbD) approach was adopted to speed up the method development and to test robustness of the method. To evaluate the effect of variable factors on chromatographic response, a full factorial design was used. The chromatographic separation was performed using isocratic elution on the C18 column. The mobile phase consists of 92% methanol, 6% acetonitrile, and 2% phosphate buffer with 0.1 (v/v) triethylamine adjusted to pH 3, it was pumped at a flow rate of 0.8 mL/min with an injection volume of 20 μL. The developed stability indicating HPLC approach was used to assess the stability of montelukast (MNT). It was subjected to a variety of stress conditions, including hydrolytic (acid–base), oxidative, thermal, and photolytic stress conditions. All of these conditions were found to have relevant degradation pathways. Under the described experimental conditions, MNT degradation followed pseudo-first-order kinetics. The kinetic parameters of its degradation (rate constant and t1/2) were calculated and a proposal for the degradation pathway was postulated.
Seasonal allergic rhinitis, commonly referred to as hay fever, affects millions of people worldwide. Symptoms include sneezing, nasal congestion, runny nose, and itching in your nose, the roof of your mouth, throat, eyes, or ears. The most common seasonal triggers are pollen grains and mold spores in the air, which trigger a chain reaction in your immune system . The combination of bilastine and montelukast has been recently used to relieve the symptoms of seasonal allergic rhinitis .
Bilastine (BIL) is, 2-[4-(2-(4-(1-(ethoxy ethyl)-1H-benzimidazole-2-yl) piperidine-1-yl) ethyl) phenyl]-2-methyl propionic acid (Fig. 1-1), is a unique second-generation H1 antihistamine that has been found to cause no sedation or cardiotoxicity in clinical studies or post-marketing experience. It was established to treat the symptoms of allergic rhino conjunctivitis and urticaria . variable approaches for determining BIL have been investigated, including spectrophotometric , spectrofluorometric , and chromatographic methods [6,7,8].
It is a powerful leukotriene receptor antagonist and is used to treat asthma and seasonal allergic rhinitis .
To give additive benefits, it is recommended that these two drugs be used together in reducing SAR symptoms and allergic rhinitis-associated asthma.
The analytical approaches for determining both drugs have been recently reported. These methods include spectrophotometry  and the HPLC method [17,18,19,20,21,22,23]. However, the proposed method has the advantages of being more sensitive than the reported methods for both drugs, greener as minimum amount of acetonitrile was used compared with these methods and the degradation pathway of montelukast was provided. Additionally, two detectors were investigated during the determination which are fluorescence detection and diode array detection.
There is always a need for essential stability-indicating methods (SIMs) in a modern analytical laboratory. The standards demand that forced degradation tests be carried out under a variety of conditions, including pH, light, oxidation, dry heat, and λ isolation from degradation products. Furthermore, stability testing methodologies and kinetic studies on drug disintegration are required for quality control and to estimate the expiration date of pharmaceuticals .
Analytical Eco-Scale and GAPI approaches were used to estimate the suggested analytical method's greenness.
In this study, a HPLC approach for the simultaneous analysis and quantification of bilastine and montelukast is developed which has the advantages of being more sensitive, and greener compared with reported methods and has a wider range.
With a small number of trials, the design of the experiment (DOE) was used to explore the effect of a variety of conditions on specific responses, as well as their interactions. As a result, the volume of organic solvents and chemicals used during the research was reduced. In addition to applying the approach to dosage forms, we aimed to investigate the stability of montelukast under stress conditions.
Apparatus, materials, solvents, and reagents
Shimadzu Prominence Series LC-2030 C (Shimadzu., Kyoto, Japan) with a Quaternary RS pump, RS auto-sampler, Thermostated RS column compartment, and RS diode array detector (DAD) and fluorescence detector RD-20A.
Knauer® ODS (150 × 4.6 mm, 5 µm) C18 column.
All the chromatographic data obtained were manipulated using Lab solutions software.
Minitab® statistical software was used to perform the factorial design and statistical analysis (release 16 for windows, state college, Pennsylvania, USA).
Consort NV P-901 pH Meter (Belgium) was used to adjust pH.
Bilastine (BIL) was kindly supplied by Mash Premiere (El- Obour City, Egypt), and its purity was 99.3%.
Montelukast (MNT) was kindly donated by Novartis Pharma AG, Egypt, and its purity was 99.2%.
Organic solvents (HPLC grade) and triethylamine (≥ 99.5%) were bought from the distribution center of Sigma-Aldrich in Cairo, Egypt.
Orthophosphoric acid (85 percent, w/v) was bought from Riedel de Häen (Seelze, Germany).
Sodium dihydrogen phosphate and sodium hydroxide were obtained from ADWIC Co. (Cairo, Egypt).
Each prepared tablet contained (20 mg of BIL and 10 mg of MNT), 20 mg of talc powder, 15 mg of maize starch, 15 mg of lactose, and 10 mg of magnesium stearate.
Standard solutions and mobile phase
To obtain 100.0 µg/mL standard solutions of each drug, BIL and MNT samples were accurately weighed (0.010 g) and dissolved in methanol in 100.0 mL volumetric flasks. The stock solutions were kept in the refrigerator and were found to be stable for two weeks, MNT should be protected from light.
The mobile phase consists of 92% methanol, 6% acetonitrile, and 2% phosphate buffer with 0.1% v/v triethylamine adjusted to pH 3. Before being filtered via 0.45 µm membrane filters, the fluid was ultrasonicated.
Constructing the calibration graphs
Serial dilutions of each of the BIL and MNT standard solutions were prepared with final concentrations of 1.0–50.0 µg/mL for BIL and 3.0–40.0 µg/mL for MNT with a PDA-detector. For MNT solution with the FLU-detector was (0.2–5.0 µg/mL). Serial concentrations were transferred into a series of 10 mL volumetric flasks, and completed to the mark with the mobile phase and mixed well. The mobile phase flowed at a rate of 0.8 mL/min and 20 µL aliquots were injected in triplicate under the optimum chromatographic conditions. The calibration curves for both analytes were constructed by plotting the average peak area against the final drug concentration (c) in µg/mL and the corresponding regression equation for each drug was derived.
Analysis of pharmaceutical preparations
Ten tablets were prepared by mixing powder proportions corresponding to the weight of one tablet (0.02 g of BIL and 0.01 g of MNT). A quantity of the powder equivalent to one tablet was transferred into a flask then adding approximately 50.0 mL of methanol was. The flask was sonicated for 30 min before being completed with methanol in 100 mL volumetric flasks and then filtered with a syringe filter. Further dilution with distilled water was carried out to produce a working standard solution, which was then assessed using the general procedure described before under 2.3.1. The nominal content was calculated using either previously generated calibration graphs or using the corresponding regression equation.
kinetic studies of degradation of MNT
According to ICH guidelines , different stress conditions were applied to aliquots of MNT solution (10 µg/mL). For the acidic degradation study, the appropriate volumes of MNT were transferred into a series of 10 mL volumetric flasks and exposed to the stated acid (1 mL 0.3 M HCl) at different time intervals (0–3 h) at 40 °C.
Similarly, for basic degradation, it was exposed to alkali (0.3 M NaOH) at different time intervals (0–3 h) at 40 °C.
For thermal degradation, the flasks were kept in a water bath heated at different temperatures (25, 35,45,60, and 70 °C) for 1 h.
For photolytic degradation, UV lamb was used at time intervals (0.0–4 h) in a wooden cabinet at a distance of 10 cm.
For oxidative degradation, 10% v/v H2O2 was added to the flasks at time intervals (0.0–3 h) at room temperature.
Samples were transferred, neutralized, or evaporated under nitrogen (if necessary), diluted with deionized water, and evaluated sequentially using the developed HPLC method, with the remaining MNT concentrations estimated using the corresponding regression equation.
Results and discussion
Optimizing the method
The wavelength of the diode array detector (PDA detector)
The diode array scanning range was from 190 to 400 nm and the detection wavelength was set at 250 nm above the cutoff point of methanol.
Excitation/emission wavelengths of fluorescence detector (FLU-detector)
A spectrofluorometer was used to individually scan 10 µg/mL of each of the BIL and MNT solutions. Only MNT has an emission band at λem = 390 nm (λex = 340 nm) therefore the fluorescence detection was carried out at 340/390 nm.
The mobile phase composition, pH, and flow rate
Each methanol and acetonitrile were tried as organic modifiers, and the optimal combination was found to be a mixture of methanol and acetonitrile, which caused MNT to separate from the column. According to previous trials, decreasing the methanol ratio caused a significant increase in the retention time of MNT with poor sensitivity, hence we used 85 to 92 % (v/v) methanol.
Factorial design approach
Chromatographic conditions screening and optimization "Univariate optimization" is a complex procedure that necessitates a large number of experiments to attain the best results. The study only examines one variable at a time while the others were kept constant, which is time-consuming.
Full factorial design is a form of DOE "multivariate optimization" that permits researchers to explore the effect of all parameters while simultaneously varying them, and evaluating the actions of independent elements and their interactions . The method of factorial design requires few runs for each investigated parameter, allows identifying influential process parameters without time consuming and costly tests.
QbD allows for a more efficient and effective development process, reducing the time required for method development and optimization. This is achieved by identifying the critical parameters and their impact on the responses, which allows for a more focused and targeted approach to method development. it also ensures that the method is robust, and any variations in the parameters will not affect the quality of the final results. This is achieved by identifying and controlling the critical parameters and understanding the effect of changes in these parameters on the responses.
In this investigation, a full factorial design with two levels and four independent factors was used to test and optimize the chromatographic conditions. The percent of methanol, acetonitrile, buffer pH, and flow rate were the most essential elements influencing the HPLC process, and DOE optimized them.
Methanol ratios of 85 and 92% were tested, while acetonitrile ratios varied from 3 and 6%. The pH of potassium dihydrogen phosphate was between 3 and 6. For the analysis of acidic and basic drugs in a reversed-phase system at these pHs, flow rates of 0.8 and 1.2 mL/min were selected. As a result, the two levels were (− 1) for the lower level and (+ 1) for the higher level, with the four independent parameters being percent of methanol (A), percent of acetonitrile (B), buffer pH (C), and flow rate (D) .
The interaction of each level on the responses including tailing of montelukast peak (T2) (R1), number of theoretical plates of MNT (NTP) (R2), Run time and resolution between the two drugs (R3) (R4) was studied using a 23 full factorial design that suggested 16 runs. Tables 1 and 2 shows the two levels, independent variables, and dependent variables.
The significance of independent factors was determined using an approximated Fisher Statistical Test for Variance Analysis (ANOVA) model  that was applied to the responses to investigate the effect of these independent factors on the responses as well as their interactions. The equation for the four-factor experimental design is as follows:
where R stands for a response, β stands for regression coefficients, and A, B, C, and D stand for methanol %, acetonitrile %, buffer pH, and flow rate, respectively.
To be sure that the best possible circumstances are achieved, the Minitab response optimizer determines the composite desirability of a response (D), which varies from zero to one, and determines whether the responses are within reasonable limits. Zero is not acceptable because it indicates that many of the responses are outside their acceptable ranges, whereas one indicates that the conditions obtained are ideal, hence its value should be one or close to one.
The full factorial design yielded the best results; thus, the optimization plot (Fig. 2) demonstrates how the four variables and their interactions affect the composite desirability and response to achieve the best results.
Factorial design can also provide half-normal plots and Pareto charts (Figs. 3, 4) show that methanol % (A) has a significant effect on the tailing of MNT (R1), methanol% (A) and methanol with pH (AC) have a significant effect on NTP of MNT (R2), also methanol with pH (AC) has a significant effect on resolution between the two drugs (R3) while methanol% (A) and flow rate (D) have a significant effect on run time (R3) with statistically significant effect for a 95% confidence level.
Which were confirmed by the interaction and main effect plots (Figs. 5, 6) show that minimizing the tailing of MNT and the run time, while maximizing the NTP of MNT could be achieved by increasing the percentage of methanol in the mobile phase, reducing the flow rate and using a buffer with pH 3.
Thereafter, the mobile phase was obtained using a mixture of 92 (v/v) % methanol, 6% acetonitrile, and 2% phosphate buffer with 0.1 percent v/v triethylamine adjusted to pH 3 according to DOE (Fig. 7).
Validation parameters were evaluated following the International Conference on Harmonization (ICH) Q2R1 guidelines . After analyzing six concentrations for each of BIL and MNT, regression equations were used to investigate the linearity and ranges for the two drugs. As indicated in Table 3, the recommended HPLC procedure was applied to pure samples of BIL and MNT over the ranges of 1.0–50.0 and 3.0–40.0 µg/mL using the PDA-detector, respectively. and MNT (0.2–5.0 µg/mL) using the FLU detector. For the two drugs, the peak area (y) was plotted against the concentration (c), and the correlation coefficients (r) were determined to be 0.9999. Regression equations of the data were calculated and given as:
When statistically comparing the results obtained using the suggested method with those obtained from the comparison method  as shown in Table 4, it was found that no significant difference regarding accuracy and precision . The comparison method was RP-HPLC using a C18 column and ACN with water as the mobile phase (70:30 v/v, flow rate 0.8 mL/min, UV detection at 215 nm).
Three separate concentrations of each drug were assessed on three consecutive days between one and three days to evaluate the intraday and interday precisions. Table 5 summarizes the analytical data.
A half-factorial design with eight experiments was used to test the robustness of the proposed HPLC method. The robustness of the method was demonstrated by varying the chromatographic conditions such as methanol (92 ± 0.2%), ACN (6 ± 0.1), pH (3 ± 0.2), and flow rate (0.8 ± 0.1 min/mL). As seen in Table 6 and Fig. 8, such minor alterations had little effect on drug resolution, confirming the method's robustness.
Application to prepared tablets and synthetic mixtures
The results obtained using the proposed approach for assessing BIL and MNT in prepared tablets and synthetic mixtures were statistically compared to the results of a previously reported method. . Tables 7, 8 demonstrates that statistical analysis using Student's t-Test and Variance Ratio F-test , revealed no significant differences between the two methods regarding accuracy and precision.
Degradation kinetic studies
The kinetics of MNT degradation were studied using the proposed approach. Calculating the remaining MNT concentration (Ct) at predefined time intervals was used to get kinetic data. MNT kinetics were investigated in terms of acid, alkali hydrolysis, thermal, photo, and oxidative degradation, where k is the pseudo-first-order rate constant with a negative sign and t is the time. The results obtained match with a reported method for the degradation of MNT under similar stress conditions . The measured reaction rate constants (k) for MNT acid and alkali hydrolysis were 0.414 h−1and 0.385 h−1, respectively, with half-life times (t1/2) of 1.67 h and 1.8 h. MNT kinetic rate constants for thermal, photolytic, and oxidative degradation pathways were 0.183 h−1, 0.17 h−1, and 0.075 h−1, respectively, with t1/2 values of 3.7, 4.0, and 9.12 h, as shown in Figs. 9, 10.
The acidic and basic degradation pathways are in agreement with those reported in previous studies .
In oxidative degradation, the Sulphur atom is supposed to be oxidized to the corresponding sulphoxide giving a more polar compound . This means the drug undergoes degradation by hydrolytic (acid and base), thermal, photolytic, and oxidative actions. The degradant peaks did not interfere with the MNT peak in any of the above conditions, confirming that the approach allowed for the analysis of MNT in the presence of its degradation products (Table 9).
A proposal for the degradation pathways is shown in Fig. 11.
Greenness evaluation methods
Analytical Eco-Scale and GAPI approaches were used to estimate an analytical method's greenness [33,34,35,35]. The proposed approach is a great green method of analysis with few laboratory’s needs, according to the two methods (Table 10; Fig. 12) Using the Analytical Eco-Scale approach, the total number of penalty points for the entire procedure was determined. The results show that the suggested approach worked well for green analysis using the analytical eco-scale of 84.
A quality-by-design approach to the HPLC method with a Diode array and fluorescence detection modes was designed to determine BIL and MNT in their tablets and to determine MNT in presence of its forced degradation products. MNT is susceptible to acid, alkali hydrolysis, heat, UV, and oxidative-induced degradation. Furthermore, degradation rates were investigated, and it was found that they followed pseudo-first-order kinetics. At three separate levels, a multivariant investigation of various essential process variables was conducted, including % of methanol, % of acetonitrile, and buffer pH. The method is green, precise, accurate, and robust, according to statistical analysis of data. Factorial design provides the most run efficient (economical) data collection plan to learn the relationship between your response variables which allows the method to be used further for routine analysis in quality control labs in the pharmaceutical industry.
Availability of data and materials
All data analyzed during this study are included in this published article and raw data are available from the corresponding author upon reasonable request.
Diode array detector
Design of experiment
Green analytical procedure index
Number of theoretical plate
Quality by design
- % RSD:
Percentage relative standard deviation.
Seasonal allergic rhinitis
Stability indicating methods
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The authors would like to thank Horus University-Egypt for allowing the use of the instrument in this study (Shimadzu Prominence Series LC- 2030 C (Shimadzu., Kyoto, Japan) with a Quaternary RS pump, RS auto-sampler, Thermostated RS column compartment, and RS diode array detector (DAD) and fluorescence detector RD-20A).
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Roshdy, A., Salam, R.A., Hadad, G. et al. Green quality by design HPLC approach for the simultaneous determination of Bilastine and Montelukast. BMC Chemistry 17, 43 (2023). https://doi.org/10.1186/s13065-023-00953-y
- Quality by design