Abstract
Modern society is increasingly reliant on sustainable solutions. We suggest a creative study that meets the standards of sustainability in analytical chemistry. The objective is to promote eco-friendly methods for concurrently detecting Gatifloxacin (GAT) and benzalkonium chloride (BEN) in ocular solutions. Using a sustained mobile phase flow rate of 0.8 mL/min–1 and acidic water: 10% 1-butanol in water (40:60, v/v), GAT was retained for 2.242 min at 287 nm, followed by BEN homologues at 215 nm for the next 2.982 and 4.201 min. This process was simple, quick, and precise. The method demonstrated peak symmetry, low processing times, good resolution, and correlation values 0.999. For GAT, the linearity ranged from 0.001 to 0.023 mgmL–1, while for BEN, it was from 0.003 to 0.060 mgmL–1 in the HPLC system, while the UV method in the range of 0.005–0.03 mgmL–1 for all drugs. A unique feature of this study is the integration of multiple sustainability assessment tools, such as AGREE, AGREEprep, ComplexGAPI, ESA, BAGI, and NEMI pictograms, providing an exhaustive appraisal of the methods’ environmental impact and enhancing the robustness of the findings. In addition, eco-friendly and cost-effective alternatives were explored using water as the solvent in complementary spectrophotometric procedures such as mean centering of ratio spectra (MCR). Each technique showed respectable accuracy and precision (RSD ≤ 2%) and high linearity r2 > 0.9990. The proposed methodologies provide inexpensive, eco-friendly alternatives to conventional approaches, promoting a less harmful future for quality control and moving analytical chemistry closer to more sustainable methods.
1. Introduction
Chemistry is a multifaceted field that includes both green and white methods. As a result of its sound methodology, harmful materials can be reduced or eliminated from chemical processes and products. To satisfy societal demands without adversely affecting the environment, scientists and engineers can use green and white chemistry concepts to create safer, more resilient, and eco-friendly products and processes. By the use of renewable resources and reduction of waste, this strategy reduces pollution and waste and makes chemical processes safer. Developing sustainable practices through green and white chemistry is essential for the chemical industry’s future.1,2
In recent years, green analytical techniques in quantitative analysis have grown in popularity. Aspects of the profession that require improvement include the environmental impact of analytical procedures as well as the safety and health of analysts. In terms of greening their analytical techniques, pharmaceutical companies are making significant progress. Environmental responsibility and sustainability are becoming more active topics in the analytical community. It is of utmost importance to develop new eco-friendly procedures, and eco-friendliness has been carefully considered concerning solvents and waste production. Significant strides have been made in analytical chemistry to support sustainability, but additional work is needed to provide even more remarkable results.3,4
There is an intriguing and unique correlation between MCR and HPLC. The use of HPLC in liquid chromatography is novel. This method reduces solvent usage, improves resolution, increases sensitivity, and shortens the analysis time. There are distinct advantages and disadvantages to both MCR detection and HPLC, two widely used analytical techniques for sample analysis. HPLC is suitable for a variety of sample types, including those with complex or closely related ingredients due to its capacity to efficiently separate and quantify a broad spectrum of molecules. HPLC can track and analyze more than 100 samples in a single sequence. HPLC equipment, maintenance, and operation can be expensive. The solvents and columns used are additional elements that may contribute to high operating expenses. The fact that samples usually need extensive preparation, including dilution and filtration, to be compatible with the HPLC system is one of the reasons why HPLC has limitations. The MCR method offers the following benefits: it is easy to use, requires less sample preparation, has shorter run times, and is often faster than HPLC for certain assays. The MCR technique is generally less expensive than HPLC equipment, in terms of both the initial investment and continuing operational costs. The sample can then be recovered because UV analysis often does not harm anything.5,6 One of the limitations of MCR approaches is that they can measure only one sample every run. MCR quantitative analytical techniques can be less exact and accurate than HPLC, especially for complex mixtures with partially resolved components. Whether to utilize HPLC or MCR will depend on the specific study parameters, including the sensitivity, selectivity, cost, and sample complexity. HPLC offers superior sensitivity and selectivity for complex combinations. Additionally, for simpler samples where high selectivity is not as important, UV methods provide a simpler and less expensive option.7,8
Ophthalmic preparations consist of sterile suspensions or aqueous or oily solutions comprising one or more active components. Typically, they are presented in appropriate multidose packaging that delivers the preparation in consecutive drops. Microbiological contamination or growth while using and storing ophthalmic medications could result in the degradation of the product or could result in severe eye infections and is mostly used in antibacterial ophthalmic preparations. GAT is a well-liked medication for treating and preventing eye infections, which belongs to the fourth-generation fluoroquinolones. C19H22FN3O4 is the chemical formula for GAT, and its molecular weight is 384.40 g mol, as presented in (Figure S1a).9,10
Usually, multidose products are preserved with chemicals appropriate for their purpose. Preservatives such as BEN are the most used (Figure S1b).11
Numerous analytical techniques can be employed for estimating GAT or BEN in biological fluids, including spectrophotometric estimation of GAT alone or in combination with other drugs, either in bulk powder or biological fluid,12−18 HPLC19−27 CZE.28 At this point, no analytical technique for the simultaneous measurement of GAT and BEN in ophthalmic formulations has been documented in the official compendia. The current study established precise, accurate, and environmentally friendly HPLC and MCR methods for determining GAT in combination with BEN in ophthalmic drugs, which are two common analytical techniques for examining substances. HPLC is suitable for a variety of sample types, including those with complex or closely related ingredients, due to its ability to accurately isolate and quantify a wide variety of molecules. Compared with HPLC, the MCR method is often faster for some assays, requires less sample preparation, and has shorter run times. It is also easier to use. The MCR technique is generally less expensive than the HPLC equipment. The sample can be recovered later because UV examination typically does not result in any adverse effects.
Significantly, micellar HPLC is being used in combination with UV spectrophotometry in this field. The advantages of these methods include minimizing environmental impact, cost efficiency, and superior analytical efficiency. Among the assessment tools utilized to appraise the sustainability of the techniques, multiple sustainability assessment tools are used, including AGREE, BAGI, AGREEprep, ESA, ComplexGAPI, and NEMI pictograms. In addition to offering alternatives to conventional approaches, these methods are useful in pharmaceuticals, which makes them even more valuable.
2. Results and Discussion
The discovery and implementation of sustainable analytical techniques that minimize waste output and the usage of hazardous materials while maintaining high analytical efficiency is one of the largest issues facing current pharmaceutical research.29 The purpose of this work was to develop an effective and environmentally friendly method for determining GAT and BEN simultaneously. This aim has been achieved by utilizing unique and complementary HPLC and spectroscopic techniques with a focus on increased sensitivity and the use of environmentally friendly solvents. The results showed how well our proposed approach performed with regard to standards for the generation of sustainable analytical compounds.
2.1. Methods Development and Optimization of HPLC
The chromatographic settings essential for achieving the separation of GAT and BEN were carefully examined. Our goal was to reduce the duration of analysis while attaining optimal resolution and symmetrical, clear peak forms.
2.1.1. Choosing a Suitable Wavelength for Measurement
The examination was conducted at various wavelengths (210, 215, 270, 280, and 287 nm). The wavelengths of 215 and 287 nm were selected based on scientific reasoning because these are the wavelengths at which both BEN and GAT exhibit their highest UV absorption due to chromophore groups in their structures (Figure 1).
Figure 1.
Zero-order absorption spectra of 10 μg/mL of GAT, BEN, dosage form, and their binary mixture were clearly obtained using solvent as a blank.
2.1.2. Choosing the Column
Four columns were tested to determine the best chromatographic separation. We aimed to create a greener process using columns with shorter lengths, smaller internal dimensions, and fewer particles, thus reducing solvent usage. The columns tested included Kinetex HILIC (250 × 4.6 mm, 5 μm), Zorbax Eclipse XDB-C18 (150 × 4.6 mm, 5 μm), Monolithic RP-C18 (150 × 4.6 mm), and Kinetex C18 (250 × 4.6 mm, 5 μm). The Zorbax Eclipse XDB-C18 provided the best separation of BEN and GAT (Figure 2a,b).
Figure 2.
Typical HPLC charts of GAT and BEN homologues in (a) the mixture’s standard solution and (b) a test solution eye drop.
2.1.3. Choosing the Ratio and Content of the Mobile Phase
Eco-friendliness, economy, and safety were prioritized. Micellar mobile phases using less hazardous organic solvents facilitated ecological analysis. Various mobile phase compositions were tested to optimize the separation of GAT and BEN. Adjusting the concentration of orthophosphoric acid (OPA) within the 0.01–1.0% range, 0.25% OPA achieved the highest resolution. Different organic modifiers (ethanol, n-propanol, methanol, acetonitrile, n-butanol, and n-pentanol) were evaluated. Adding 10% 1-butanol to the mobile phase produced an acceptable resolution, symmetric peaks, and good peak sharpness within a suitable analysis period.
2.1.4. pH and Buffer Content Influences
The influence of pH on the chromatographic actions of GAT and BEN was examined using 0.25% orthophosphoric acid across a pH range of 2.0 to 4.5. A pH of 3.0 provided the greatest theoretical plates and the best peak symmetry. Different buffer concentrations (0.01, 0.05, 0.2, and 0.25% sodium dihydrogen phosphate) were tested, with 0.25% orthophosphoric acid at pH 3.0 being the final choice.
2.1.5. Influence of Column Temperature and Flow Rate
The effectiveness of chromatography was also investigated concerning the flow rate and column temperature. Among the flow rates tested (0.6 to 1.2 mL min–1), 0.8 mL min–1 offered good separation and reduced retention time. The column oven temperature was tested from 20 to 45 °C. Higher temperatures increased peak tailing and theoretical plates. Thus, 25 °C was determined to be the ideal temperature, providing the best balance between peak forms and resolution.
2.2. Spectrophotometric Methods
The direct simultaneous estimate was difficult because of the significant overlap between the superimposed UV absorption spectra of GAT and BEN. Thus, a sophisticated spectroscopic method was developed to quantify them.
2.2.1. Applying the MCR Method
The MCR approach works even in the absence of prior separation in the binary mixture of pharmaceuticals. We tested the process with different divisor concentrations to improve it. The results showed that 10 μgmL–1 was the ideal concentration. The spectra of a medication prepared span a wavelength range of 200–400 nm, as shown in Figure 3. A mixture of pharmaceuticals prepared in laboratories with concentrations ranging from 5 to 25 μgmL–1 was imported using the MATLAB software. The applicability of wavelengths 225 and 270 nm for GAT and BEN prediction is shown in Figure 3. We constructed calibration curves using amplitudes versus concentrations.
Figure 3.
Absorbances ranging from 5 to 25 μg/mL for medicines’ (a) BEN and (b) GAT, (c, d) first ratio spectra, and (e, f) MC.
2.3. Meticulous Assessment of Sustainability of the Methods
Currently, there should be a close relationship between analytical chemistry and environmental protection challenges. Furthermore, a variety of factors related to preserving the integrity of our environment must be considered in any analytical process. Therefore, we need to be aware that we need to consider both environmental preservation and operator safety when acting responsibly.1 Presently, creating procedures that adhere to the principles of green analytical chemistry (GAC) is a major concern for analytical scientists. In addition to doing away with the use of dangerous chemicals, green chemistry attempts to be economical, extremely computerized, limit sample utilization, and diminish waste.30 This work incorporates friendly evaluation methods from various viewpoints to address this difficulty using an effective multitool strategy. This predicted integration of assessment approaches enables an additional comprehensive and reliable evaluation of the sustainability of the methods used for analysis.
2.3.1. Green Solvent Selection Tool (GSST)
A free solvent calculator can be found at http://green-solvent-tool.herokuapp.com/x, along with this article. The software analysis showed that butanol and water had higher G scores than hazardous solvents such as formic acid, chloroform, and acetonitrile. Some pharmaceutical companies choose green ecological solvents based on specific criteria. We developed a chemometric tool to select a solvent (G) based on the greenness score. As a result of multiplying the four main feasible components of the equation, the fourth root (G) is obtained. Waste disposal is composed of four components: waste disposal, the environment, health, and safety. Compared with hazardous solvents like formic acid, chloroform, and acetonitrile, butanol and water scored significantly better (Figure 4).31
Figure 4.
GSST scores for the solvents of the proposed methods compared with the hazardous solvents identified by the online tool.
2.3.2. Analytical Eco-Scale Evaluation
The Eco-Scale instrument was originally designed as a means of measuring natural processes. An analytical method assessment was then performed using Eco-Scale. As a result, this penalizes analytical approaches that do not conform to the best green analysis. Subtracting the subtotal penalty points from the number of hazards, we get the total penalty points. Eco-Scale ratings are calculated using the following equation to reduce the total penalty points from 100.
Scale = 100 – Total penalty points.
Eco-Scale scores are calculated based on Table 1. In this case, an excellent green score is 75, an acceptable green score is 50, and an inadequate green score is 50.32
Table 1. Suggested Approaches’ Penalty Points Based on the Analytical Eco-Scale.
| Parameters | PPs of proposed methods |
|---|---|
| Reagents | |
| Ultra purified water | 0 |
| Butanol | 6 |
| Orthophosphoric acid | 4 |
| Instruments | |
| Spectrophotometric | 0 |
| HPLC energy (>0.1 kWh per sample) | 1 |
| Occupational hazard | 0 |
| Waste | 3 |
| Total PPs | Σ14 |
| Analytical eco-scale score | 86 |
2.3.3. National Environmental Method Index (NEMI)
For the NEMI label, a four-field circle is employed. Every section aligns with a certain analysis target, as shown in Figure S2. When these criteria are satisfied, the region is designated as green.33 The following requirements must be met by this method: (1) No toxic, persistent, or bioaccumulative chemicals have been classified as poisonous, persistent, or bioaccumulative (PBT) by the Environmental Protection Agency or Poisonous Release Inventory (TRI); (2) None of the chemicals used in this method are hazardous because they do not belong to the hazardous waste categories U, P, F, or D; (3) the pH level is between 2 and 12; and (4) the waste produced is less than 50 g. Table 2 shows the NEMI pictograms created for each proposed method.
Table 2. Greenness and Whiteness Assessment of the Recommended Methods.
2.3.4. Evaluation of Complementary Green Analytical Procedure Index (ComplexGAPI)
Figure S3 shows how the main GAPI graphic design includes an additional hexagonal sector that highlights the steps involved in sample preparation and analysis. Red, yellow, and green colors indicate high, medium, and low environmental consequences, respectively, for preanalysis processes in this sector.34 The exceptionally low E-factor and the preponderance of green icons illustrate the extraordinary greenness of our given strategy. The E-factor minimizes waste generation and improves the ecological impact by reducing waste generation. As outlined in Table 2, the ComplexGAPI examination confirms that the recommended methods combine analytical efficiency with a waste-minimizing, ecologically sensitive layout that is necessary for quality control procedures looking to adopt green chemistry concepts.
2.3.5. Analytical Greenness (AGREE) Tool
A tool for assessing analytical greenness (AGREE) was developed by Pena-Pereira et al.35 based on a weighted average of the 12 criteria of GAC. Afterward, each criterion is converted into a scale from 0 to 1, resulting in a final evaluation. In a graph that resembles a clock, each criterion’s influence is displayed in different color shades ranging from green to yellow to red. According to the AGREE evaluation, the recommended approach performs more efficiently in terms of green principles and demonstrates exceptional greenness, earning high scores of 0.86 and 0.88 for the HPLC and spectrophotometric methods, respectively. A further benefit of this method is that it is consistent with sustainable analytical practices, as shown in Table 2.
2.3.6. An Analytical Greenness Metric for the Collection of Samples (AGREEprep)
A score is calculated by dividing each subscore on a 0–1 scale by the weight assigned to each factor to determine the overall evaluation score. Chemicals, solvents, reagents, sample treatment, waste, energy use, and outcomes are some of the factors considered in this analysis.36 In addition to AGREEprep’s 10 criteria, the 12 GAC principles are abbreviated. Using HPLC and spectrophotometry, the suggested approaches for this investigation were noted to be very green, achieving remarkable scores of 0.80 and 0.92, respectively; see Table 2.
2.3.7. Assessment of BAGI Tool
BAGI uses an analysis of ten factors to develop a score and pictogram that illustrate an analytical technique’s usefulness and efficiency. Blue shades were used to denote high, medium, low, and insufficient compliance with the criteria, with different shades of blue signifying high, medium, low, and insufficient compliance. HPLC and spectrophotometric methods proved to be excellently practicable, with high throughput, automatability, and low operating costs, with BAGI scores of 75 and 77.5, respectively.37
2.3.8. Characteristics of the Multi-Tool Assessment Method
This diverse approach avoids the drawbacks of concentrating only on one technique by employing many assessment techniques to foster an awareness of the approaches’ applicability, ecological impact, and overall environmental sustainability. Switching from an MS to a UV detector can have potential drawbacks. In this work, we address several strategies to reduce matrix effects and false positives. These include the implementation of improved techniques for sample preparation, ensuring standardization throughout the organization, optimizing detector parameters, and reducing the use of chemicals that interfere. By combining the characteristics of each indicator, we can evaluate the techniques’ effectiveness across a variety of sustainability qualities. The improved sustainability of the proposed analytical methods has been shown by aspects such as less waste and toxicity, cost-effectiveness, high productivity, automated possibilities, efficient use of materials, and superior analytical accuracy. In combining qualitative and quantitative assessments, the newly developed methods proved to be highly feasible and accessible best practices that are ecological, financial, and operationally sustainable.
2.4. Greenness and Whiteness Evaluations
In our comprehensive evaluation of sustainability approaches, we investigated the proposed methodology scores. The results are outlined in Table 2. In our thorough assessment, we included NEMI, BAGI, AGREEprep, ESA, CompleteGAPI, and AGREE.
Several factors contributed to the proposed method’s superiority over those published previously,19−27 including minimal waste generation, safe chemical substitution, and maximum sample analysis per hour. As shown in Table 2, AGREE and AGREEprep pictograms scored 0.86 and 0.88, respectively, with regard to these aspects. The varying intensities of green hues in the pictograms indicate ecological sustainability.
The suggested methodologies evaluated with ComplexGAPI generate a waste volume of less than 1.0 mL, a significant reduction from previously reported waste volumes.19−27 Unlike other extraction and treatment techniques, this method requires no sample preservation, transit, or special storage conditions. We found that the technique has significant ecological benefits, as summarized in Table 2. As a result of a simple, high-purity procedure, and a slightly hazardous reagent, ComplexGAPI achieved superior results over BAGI. Table 2 provides an overview of several aspects of these strategies. In addition to the evaluation of methodologies based on GAC attributes, ComplexGAPI gives a comprehensive overview of the complexity of a method.
According to BAGI, our technique’s applicability and practicability are high compared to published methods.19−27 At BAGI, we excel in reagent utilization, sample preparation, and automated analysis. More samples can be analyzed per hour, reagent and material consumptions are reduced, sample preparation is simplified, and automation is increased.
The results of this study provide a more practical solution for analytical chemistry applications through an advancement in the field. Furthermore, our method contributes to the field by addressing key aspects of efficiency, sustainability, and ease of use.
2.5. Method Validation
The ICH guidelines were followed in the validation of the suggested micellar HPLC and spectroscopic techniques.38
2.5.1. System Suitability Parameters
System suitability factors, such as retention period (tR), column efficiency (N), and resolution (Rs), were studied as system suitability criteria to assess system efficacy. The optimum chromatographic conditions produced the two analytes’ remarkable baseline resolution with barely noticeable peak tailing. Table 3 shows that the chromatographic peaks are very symmetrical, which is indicative of an accurate and precise measurement.
Table 3. System Suitability Parameters of the Studied HPLC Method.
| Item | HPLC |
Reference values | ||
|---|---|---|---|---|
| GAT | BEN |
|||
| C12 | C14 | |||
| Tailing factor | 0.85 | 1.1 | 1.2 | T ≤ 1.5 |
| Injection precision | 0.24 | 0.27 | 0.25 | RSD ≤ 2% |
| Number of theoretical plates (N) | 3875 | 4250 | 4356 | N> 2000 |
| Resolution | 3.1 | 4.5 | - | Rs > 1.5 |
| Retention time (Rt) | 0.2 | 0.3 | 0.2 | RSD ≤ 2% |
2.5.2. Linearity and Range
Charts of HPLC calibration were carefully created for GAT concentrations between 1 and 23 μg mL–1 and BEN values between 3 and 60 μg mL–1. Both GAT and BEN have a linearity range of 5–25 μg mL–1for the method of spectroscopy. These high correlation values confirm the linear relationship between medication concentrations and analytical results, as shown in Table 4.
Table 4. Modeling of Regression and Validation Analysis for Assessing the Analyzed Drugs.
| HPLC |
MCR |
|||
|---|---|---|---|---|
| Parameters | GAT | BEN | GAT | BEN |
| Linear | ||||
| Range (μg mL–1) | 1–23 | 3–60 | 5–25 | 5–25 |
| Wavelength (nm) | 287 | 215 | 333 | 210 |
| Intercept (a) | 31.6250 | –33.46363 | 21.100 | –3.100 |
| Slope (b) | 59978.712 | 1520.47 | 71.80 | 53.90 |
| Sa | 103.61 | 11.24 | 13.13 | 5.44 |
| Sb | 17.89 | 0.80 | 0.79 | 0.33 |
| Sy/x | 359.734 | 43.44 | 12.52 | 5.19 |
| Correlation coefficient | 0.9999 | 0.9999 | 0.9998 | 0.9999 |
| System precision | 0.3 | 0.6 | 0.17 | 0.20 |
| LODa (μg mL–1) | 0.006 | 0.003 | 0.60 | 0.33 |
| LOQa (μg mL–1) | 0.017 | 0.008 | 1.83 | 1.01 |
Limit of detection (3.3 × σ /Slope) and a limit of quantitation (10 × σ /Slope).
2.5.3. Sensitivity
The minimal doses needed for proper identification (limits of detection, LOD (3.3σ/S), and quantification (limits of quantification, LOQ (10 σ/S)) were determined following the ICH’s criteria. Table 4 illustrates that the recommended methods have sufficient sensitivity for accurately recognizing and calculating BEN and GAT due to their low LOD and LOQ values.
2.5.4. Accuracy and Recovery
Using the micellar HPLC method, nine different readings were made at three concentrations (6, 7.5, and 9 μg mL–1) for GAT and 32, 40, and 48 μg mL–1 for BEN. As pointed out in Table S1, the spectroscopic approach was employed to measure the accuracy of the GAT and BEN, respectively. Table 5 illustrates the examination of the experiment’s repeatability and intermediate precision to assess the experiment’s precision. We believe that the six replicates’ relative standard deviation (RSD) was less than 2.0%.
Table 5. HPLC and MCR Methods: Intraday and Interday Precision, Robustness, and Stability of Analytical Solutions.
| HPLC |
MCR |
||||
|---|---|---|---|---|---|
| Parameter | GAT | BEN | GAT | BEN | Limit % |
| Day to day | 0.6 | 0.7 | 0.7 | 0.9 | RSD ≤ 2.0% |
| Analyst to analyst | 1.1 | 1.3 | 0.5 | 0.8 | |
| Column to column | 1.3 | 1.5 | - | - | |
| Flow rate change (0.8 ± 0.1 mL/min) | 0.7 | 1.0 | - | - | |
| pH changes of mobile phase (3.0 ± 0.1) | 0.6 | 0.9 | - | - | |
| Butanol concentration (10 ± 5%) | 0.8 | 1.1 | - | - | |
| Fresh sample | 0.2 | 0.3 | 0.7 | 0.9 | |
| Stored sample in fridge | 0.6 | 0.7 | 0.8 | 1.1 | |
| Stored sample in autosampler | 0.7 | 0.9 | - | - | |
| Stored sample at room temperature | 1.1 | 1.5 | 1.3 | 1.6 | |
2.5.5. Robustness
This technique was checked by examining the effects of minor adjustments to the pH (±0.1), flow rate (±0.1), and concentration (±0.1%) of the mobile phase. No considerable effect was observed, as described in Table 5.
2.5.6. Stability of Standard Solution
Based on the outcomes of the study, the standard solution demonstrated excellent quality. Even after being kept at room temperature or in a refrigerator for 72 h, it continued to operate effectively. There was significant compatibility between the freshly made solution and the previous one. With an RSD of less than 2.0 and a range of 100% ± 2.0%, the newly created standard and the stored one likewise matched well. These outcomes show that the standard approach is stable and predictable (Table 5).
2.5.7. Assay of Ophthalmic Solution
Utilizing HPLC and MCR methods, the results of the test solution were analyzed. Six samples were subjected to a meticulous inspection. The test data demonstrated that the drugs being tested were in excellent working order. Table S2 provides more information about the experiment’s outcomes.
2.5.8. Specificity
2.5.8.1. Selectivity
Testing multiple laboratory-prepared combinations comprising GAT and BEN independently within the range of linearity allowed for a confirmation of the methods’ selectivity produced satisfactory results. The conclusions acquired are satisfactory and are laid out in Figure S4.
2.5.8.2. Forced Degradation
To guarantee consistent findings, the specificity test method was tested with heat, acid, base, and oxidation. As shown in Figures 5 and 6, the pharmaceutical components and products were put through a variety of pressures to assess their forced degradation. All degradation products could be clearly identified, and the peaks of the GAT and BEN homologues did not interact with one another. The peak purity angles for GAT and BEN homologues, which were no more significant than the peak purity threshold (see Table 6), showed that the suggested method had great specificity.
Figure 5.
HPLC charts of forced degradation for GAT including (a) heat, (b) acid hydrolysis, (c) base hydrolysis, and (d) oxidation conditions.
Figure 6.
HPLC charts of forced degradation for BEN including (a) heat, (b) acid hydrolysis, (c) base hydrolysis, and (d) oxidation conditions.
Table 6. Degradation Results for GAT and BEN were Obtained Using the Proposed Technique.
| Condition | % Degradation | Purity Angle | Purity Threshold | |
|---|---|---|---|---|
| GAT | Heat | 3.40% | 0.270 | 0.243 |
| Acid | 5.10% | 0.298 | 0.267 | |
| Base | 4.90% | 0.310 | 0.278 | |
| Oxidation | 6.8% | 0.350 | 0.293 | |
| BEN | Heat | 1.01% | 0.297 | 0.235 |
| Acid | 3.92% | 0.287 | 0.241 | |
| Base | 3.45% | 0.263 | 0.221 | |
| Oxidation | 4.90% | 0.336 | 0.288 |
3. Conclusion
Our goal was to develop and validate sustainably an environmentally friendly micellar HPLC technology and additional spectrophotometric approaches for medicinal products GAT and BEN. By successfully validating the method under ideal conditions, we demonstrated excellent linearity, accuracy, precision, sensitivity, and selectivity. The efficient use of these techniques on medicinal items additionally showed their applicability to frequent analysis. Likewise, the excellent environmental sustainability metrics, effectiveness, and useful capability were confirmed by comprehensive greenness and blueness assessments utilizing methods like NEMI, ComplexGAPI, AGREE, ESA, and BAGI. Consequently, the established methodologies regularly incorporate environmental and commercial objectives, putting analytical science into sustainable practices.
4. Experimental Section
4.1. Chemicals and Reagents
Novartis Pharmaceutical Co. (Cairo, Egypt) kindly provided the powdered GAT (B. No. 4108395007), which has a purity of 99.6%, as stated by the supplier. BEN (B.No. R1300324) was provided generously by RAMEDA Company (Cairo, Egypt). The supplier reported that the purity was 99.50%. The Tymer eye drop package (B. No. AL0358) was purchased from a local pharmacy and manufactured by Jamjoom Pharmaceuticals Co., Jeddah, Saudi Arabia. Each 1 mL sample includes 3.0 mg of GAT and 0.05 mg of BEN (as a preservative), according to the instruction booklet.
There was no need to use any chemicals other than HPLC-grade solvents and analytical laboratory-grade elements. In addition to orthophosphoric acid, n-butanol (SDS, 99.5%) was also available (Sigma-Aldrich, Darmstadt, Germany). Analyses were conducted using distilled water of the highest purity.
4.2. Apparatus
A great option in terms of dependability and cutting-edge technology is the Shimadzu 20A HPLC (Tokyo, Japan). Its features include a diode array detector, an autosampler, and a pump that supplies quaternary solvents and works with Empower 3 software. The device also provides state-of-the-art technology and unmatched precision for food safety, environmental, and pharmaceutical analysis testing. This machine is simple to use and maintain because of its sturdy design and user-friendly UI.
Shimadzu UV-1800 double-beam UV–vis spectrophotometer, made in Tokyo, Japan, has matching 10-mm quartz cells implanted.
Torrey Pines Scientific Hot Plate (USA).
4.3. Preparation of Standard Solution
Water was used to generate the stock standard solution of both prescribed drugs under study (1 mg mL–1). For HPLC analysis, working solutions (0.1 mg mL–1) were made by diluting 10 mL of each drug solution to 100 mL using a mobile phase, and 100 μg mL–1 for spectroscopic analysis through the dissolution of precisely weighed reference standards in very pure water.
4.4. Analysis of Pharmaceutical Formulation
The combined eye drops containing GAT and BEN were formulated using the recommended approaches for quantification. Every 1 mL bottle of TYMER eye drops contains 3.0 mg of GAT and 0.05 mg of BEN, according to the package. In a 10 mL volumetric flask, 1.0 mL of an ophthalmic solution was aliquoted and then diluted with water to volume. The solution was then passed through a 0.45-m membrane filter, and the first few milliliters of the filtrate were discarded. Once this solution had been diluted properly with water, the final concentrations of each analyte were determined within the linear limits of the calibration graphs.
4.5. Chromatographic Conditions
4.5.1. For Micellar HPLC
A Zorbax Eclipse XDB-C18 (150 mm × 4.6 mm, 5 μm) (Germany) was used for isocratic separation. As a first component, orthophosphoric acid is present at a percentage of 40%. In addition to 1-butanol, water (60% v/v) is the other component of the mobile phase. After filtering, the mobile phase was ultrasonically degassed for 15 min before use. It was found that a 0.8 mL min–1 flow rate, 25 °C column temperature, and 215 nm detection wavelength resulted in good separation at the optimal flow rate. Using the mobile phase to dilute stock solutions, linearly related concentrations of each analyte were produced as calibration standards. During the 20-min HPLC setup, the mobile phase was introduced into the system to ensure baseline stability. To properly calibrate the HPLC system, aliquots of each calibration standard or sample were introduced using the autosampler. As can be seen, an example chromatogram shows how the two compounds were separated.
4.5.2. For Methods of Spectroscopy
The UV–visible absorption spectrum of standard solutions of GAT and BEN was recorded across a wavelength range of 200–400 nm, using ultrapure water as a reference. Superimposing the zero-order absorption spectra of the two analytes illustrates the extent of spectrum overlap.
4.6. Construction of Calibration Graphs
4.6.1. HPLC Technique
Using the micellar mobile phase, stock solutions were serially diluted to create calibration graphs for the HPLC technique, including concentration ranges of 1–23 μg mL–1 for GAT and 3–60 μg mL–1 for BEN. In triplicate, each standard solution (20 μL) was injected using optimal chromatographic conditions as detailed above. Plotting mean peak areas against the corresponding concentrations resulted in the construction of calibration curves, and linear regression analysis was used to obtain the equation of the line and correlation coefficient (r2).
4.6.2. Spectrophotometric Analysis
Serial dilution was used to create a series of working standard solutions that produced concentration ranges of 5–25 μg mL–1 for GAT and BEN. UV–visible absorption measurements were recorded between 200 and 400 nm in wavelength using extremely pure water, serving as the basis for the blank.
4.6.2.1. Method of Mean Centering of Ratio Spectra (MCR)
Background Theory of the Method
This is a tried-and-true spectrophotometric technique for figuring out mixtures and kinetic profiles.39 This method yields the ratio spectra, which are mean-centered in order to eliminate the constant:
In the presence of no interactions among the compounds, Beer’s rule is applied to each substance in a mixture of medications (X) and (Y):
 |
X and Y’s molar absorptivity vectors are represented by aX and aY, respectively, and X and Y’s concentrations are represented by CX and CY.
By dividing Am by αY corresponding to the spectrum of a binary mixture of Y, the first ratio spectrum is obtained as follows:
 |
While the mean centering of B (MC) is zero, the mean centering of a constant (CY) is also zero:
 |
 |
The data indicate a linear correlation, free from the influence of the other chemical (Y), between the quantity of (X) in the solution and the amount of MC(B). Likewise, (Y) might be obtained by dividing Am by aX, which represents the spectrum of a typical solution of (X) and continues as previously.
The acquired ratio spectra were exported to MATLAB to generate the mean-centered ratio spectra (MC) for both medications after mean centering concerning the wavelength was performed. Curves for calibration were created by documenting and preserving the spectra of standard solutions with various GAT concentrations. The solution’s stored spectra were divided by the BEN standard spectrum. After that, the vectors’ mean wavelength centering was determined. Calibration graphs were created using either the minimum or maximum of these vectors. BEN calibration curves were generated similarly to GAT calibration curves. In order to calculate the regression equations, we plotted the peak amplitude of MC at 270 and 225 nm for GAT and BEN, respectively, against the concentrations.
4.7. Assessment of Combinations Constructed in Laboratories
4.7.1. HPLC Method
Laboratory-prepared combinations of GAT and BEN were established to evaluate the precision and suitability of the developed HPLC method. Aliquots of each analyte stock solution were added to the ten mL volumetric flask. After the mobile phase was added to the volume, distinct concentration ratios were achieved over the specified linearity ranges. Within the ideal HPLC setting, which is outlined in Section 4.5.1, the produced solutions were carefully mixed and inspected. Peak areas were assessed for every analyte, and the chromatograms were saved. Using the appropriate calibration equations, the concentrations of GAT and BEN in the produced mixtures were determined. By measuring the percentage recovery (%R) for every analyte in each of the combinations, the procedure’s accuracy was assessed.
4.7.2. Spectroscopic Method
Several laboratory-prepared combinations with various ratios of GAT and BEN were generated to assess the efficacy of the established spectroscopic approach. This technique was used to achieve concentrations within the stated linearity limits by depositing suitable aliquots of each analyte stock solution into a 10 mL volumetric flask and filling it with ultrapure water to the mark. Section 4.5.2 states that absorption spectrum results of different lab combinations were obtained between 200 and 400 nm. To ascertain the accuracy, the concentrations of each analyte were calculated, compared to the nominal values, and expressed as a percentage (%) R.
5. Study Limitations and Future Research Plans
It provides a foundation for future research, despite some limitations. In spite of the large sample size and diversity of formulations, further research should be able to extend the generalizability of the initial findings. Studies currently focusing on in vitro conditions may provide valuable insight, but future studies should prioritize in vivo evaluations for a more accurate assessment of the pharmacokinetics and pharmacodynamics. With Quality by Design (QbD), factors and their interactions on measured responses can be determined without conducting extensive experiments, allowing the intended goal to be achieved. Using this approach, the drugs mentioned could be detected more rapidly and with greater selectivity.
Aside from enhancing sensitivity and accuracy, UPLC reduces solvent and energy consumption, as well as analysis time by up to five times. With UPLC-MS/MS, it is possible to identify and characterize the degraded GAT and BEN products.
Acknowledgments
The authors acknowledge Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2025R227), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Supporting Information Available
The supporting information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.4c10508.
The chemical structures of Gatifloxacin (GAT) and Benzalkonium Chloride (BEN); pictograms of NEMI and ComplexGAPI; HPLC chromatograms of placebo and mobile phase; recovery and accuracy data for GAT and BEN; estimation of ophthalmic solution according to documented methods (PDF)
The authors declare no competing financial interest.
Supplementary Material
References
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