A Box-Behnken design optimization based ecofriendly RP-HPLC method For Estimation of sofosbuvir And velpatasvir - Application to stability indicating assay

doi:10.21203/rs.3.rs-3091594/v1

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A Box-Behnken design optimization based ecofriendly RP-HPLC method For Estimation of sofosbuvir And velpatasvir - Application to stability indicating assay

https://doi.org/10.21203/rs.3.rs-3091594/v1

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In this study, a novel, cost effective, accurate, and ecofriendly stability-indicating RP-HPLC technique was developed and validated for the simultaneous measurement of sofosbuvir (SOF) and velpatasvir (VEL) in tablet dosage form. Box-Behnken design was used for multivariate optimization of the experimental parameters of RP-HPLC. The molarity of heptane sulfonic acid sodium salt (HSA), volume of ethanol, and volume of acetonitrile were used to develop mathematical models and study the effects of these factors on various responses. Heptane sulfonic acid sodium (1mM) : acetonitrile : ethanol (80 : 11 : 9 v/v) as the mobile phase, made up the optimal and expected condition. The SOF and VEL retention times were found to be 5.505 and 3.472 minutes, respectively. System suitability, specificity, accuracy, linearity, precision, and solution stability were all considered in the method's validation. For SOF and VEL, linearity was shown across the concentration range of 20–100 µg/ml and 5–25 µg/ml, respectively with correlation coefficient (R²) > 0.999. Studies on forced degradation under acid, basic, oxidative, photolytic, and thermal conditions revealed the drug's well-resolved peak and the degradation products' peaks as well. For the simultaneous determination of sofosbuvir and velpatasvir in conventional laboratory analysis, this newly suggested approach is one that is quick, reliable, and cost-effective. Furthermore, the greenness was analyzed utilizing four cutting-edge metrics, including GAPI, AES, AMGS, and AGREE, and the greenest findings were determined.

RP-HPLC

sofosbuvir

velpatasvir

Box-Behnken design

stability-indicating

Greenness

The Hepatitis C virus causes a liver ailment known as hepatitis C. The hepatitis C virus is a blood-borne virus, and exposure to tiny amounts of contaminated blood is the most prevalent means of transmission. Approximately 70 million individuals worldwide were infected with Hepatitis C. More than 95% of those with Hepatitis C infection may be cured, and death rates may be decreased, by antiviral drugs such sofosbuvir, velpatasvir, and voxilaprevir, among others. Nucleotide analog sofosbuvir inhibits the RNA-dependent RNA polymerase, which is essential for the human cytomegalovirus to replicate. The metabolism of sofosbuvir results in the production of 2'-deoxy-2'-fluoro—C-methyluridine-5'-triphosphate, an imperfect substrate for NS5B. For the Hepatitis C virus to be transcribed, as well as for it to have a high rate of replication and a diverse genetic makeup, NS5B, an RNA-dependent RNA polymerase, is necessary. Sofosbuvir(Fig. 1a) chemically Isopropyl (2S)-2-[[[(2R,3R,4R,5R)-5-(2,4-dioxopyrimidin-1-yl)-4-fluoro-3-hydroxy-4-methyl-tetrahydrofuran-2-yl]methoxy-phenoxy-phosphoryl]amino] propanoate. A direct-acting antiviral drug known as velpatasvir (Fig. 1b) is used in combination treatment to treat chronic hepatitis C, an infectious liver condition brought on by infection with the hepatitis C virus. Velpatasvir's action is probably comparable to that of other types of selective NS5A inhibitors, which bind to the NS5A subunit's domain I, which contains the amino acids 33–202. US Food and Drug Administration and European Medicines Agency approval of the fixed-dose combination of sofosbuvir and velpatasvir for the treatment of individuals with chronic hepatitis C virus infections of genotypes 1, 2, 3, 4, 5, and 6. A combination drug called Epclusa® contains the antivirals sofosbuvir and velpatasvir.

Many analytical techniques including UV–Visible spectrophotometry [1], high performance liquid chromatography [2–7] and high performance thin layer chromatography, UPLC[8], LC-MS/MS [9–11] have been recorded for both medications alone and in combination with other drugs. There is a documented HPLC technique for sofusbuvir and velpatasvir-related compounds[12]. Since high performance liquid chromatography is more sensitive [13, 14], this work focuses on the development of a green HPLC technique using an AQbD methodology, followed by validation.

ICH Q8 guidance mentions QbD, stating that "Quality cannot be tested into products, i.e., quality should be built in by design" (Quality by Design) [15–16]. ICH Q8 defines QbD as a systematic approach to drug development that starts with a set of goals and stresses product knowledge, process control, and methods to quality risk management. Analytical Quality by Design (AQbD) produces results that are robust throughout the course of their lifespan and are well understood, making it comparable to process Quality by Design (QbD). AQbD has different aspects such as Analytical Target Profile (ATP), Risk assessment, Screening design, Method Optimization, Design of Experiments (DoE), Design space or Method Operable Design Region (MODR), Method Validation and Continuous Method Monitoring, etc. Even if they do, analytical researchers have little to no expertise with or knowledge with the AQbD approach for analytical procedures. The process of creating and verifying analytical methodologies enhances the product's quality in a way that is comparable to product quality through design and may be profitable. The requirement for rigorous analytical method development and an AQbD is heightened by the dependency of pharmaceutical research and manufacturing on reliable analytical data. The various experimental designs have attracted a lot of attention for the purpose of optimizing the analytical approach in terms of the design space where the response displays the optimal. The most practical three-level factorial designs employed include central composite design, Box–Behnken (BBD) design. Concern regarding the environment-defying impact of different solvents is growing at an alarming rate. Drug analysis analytical techniques also use hazardous and lethal solvents that produce a large amount of waste. The pharmaceutical industry is currently taking steps to create and analyze drugs using an environmentally friendly analytical technology. Additionally, in order to implement Green Analytical Chemistry (GAC) ideas without impairing process performance, it is necessary to closely examine a number of factors and fully comprehend how these parameters relate to one another.

There have been reports of stability indicating RP-HPLC techniques [17–20] for the measurement of Sofosbuvir and Velpatasvir in pharmaceutical formulations, but no QbD-based stability indicating RP-HPLC approach for their quantification has been described. Bringing together the GAC framework with an AQbD strategy creates a synergistic platform for developing eco-friendly, efficient, and adaptable methods. The focus of this research is on BBD's optimization of the HPLC chromatographic settings and greenness profile of the method. Using a set of points that are located in the middle of each edge of a multidimensional cube and center replicates, the BBD response surface design is used for multivariate optimization. An essential component of developing an HPLC technique is the selection of critical parameters and responses. Accordingly, preliminary research and risk analysis were conducted to identify crucial factors based on their impact on response. In addition to preliminary tests, Ishikawa (fishbone) diagrams were utilized to identify and evaluate the essential factors that posed the greatest risk to the effectiveness of the procedure as a whole. Utilizing BBD, variables including molarity of heptane sulfonic acid sodium, ethanol volume, and acetonitrile volume were shown to have a substantial impact on chromatographic separation. On the basis of an optimized BBD experimental domain, these three influent chromatographic parameters— the molarity of heptane sulfonic acid sodium salt (HSA), volume of ethanol—were varied over a wide range, and their quantitative impact on the response variable—velpatasvir retention time, sofosbuvir resolution time, theoretical plates of velpatasvir, and sofosbuvir tailing factor—was identified. Therefore, the primary goal of the current research study was to establish a straightforward, accurate, robust, and the greenness approach appropriate for quality control testing of the combination of velpatasvir and sofosbuvir utilizing BBD.

Materials

Free samples of the two pure antiviral drugs sofosbuvir and velpatasvir were generously provided by Zydus Cadila Pvt. Ltd. in Ahmedabad, India, All chemicals and solvents used were bought from Merck Specialities Pvt. Ltd. in Mumbai, India, and were of HPLC quality. Each film-coated tablet of Epclusa® (Natco Pharma Ltd India) includes 400 mg sofosbuvir and 100 mg velpatasvir.

Instrumentation

The Waters-2695 (Model Alliance) equipment used in the chromatographic system was outfitted with a Spursil ODS column (150 x 4.6 mm; 5 µm), LC-20 AD pumps, and a UV detector. Through an auto sampler, samples were delivered. By using Empower-software version 2, the output signal responses were integrated and tracked. The components' solubility was enhanced by ultrasonication on an ultrasonicator (LAB INDIA). A Mettler Toledo (model-ML303T) balance was used for all the weighing in the research.

Chromatographic conditions

The Spursil ODS column was used for chromatographic separation (150 x 4.6 mm; 5 µm). Heptane sulfonic acid sodium (1mM) : acetonitrile : ethanol (80 : 11 : 9 v/v) were used in the mobile phase. Every day, the mobile phase was produced, then filtered through a 0.45 µm nylon membrane filter and sonicated for 15 minutes. The mobile phase flow rate was tuned to 1 ml/min, and the column temperature was kept at room temperature. The injection volume was 10 µl. The chromatogram was measured at 255 nm detection wavelength. As a diluent, mobile phase was utilized.

Preparation of standard solutions

Individually, a standard stock solution of sofosbuvir and velpatasvir (1000 µg/ ml) was generated by dissolving 10 mg of drug in a 10 ml volumetric flask in some amount of ethanol, followed by dilution to the mark with ethanol. In order to achieve a final concentration of 100 µg/ml for both sofosbuvir and velpatasvir, a 1 ml aliquot was taken from the stock solution and diluted to the mark with mobile phase in a 10 ml volumetric flask.

Method development by using QbD concept

Step 1: Analytical target profile (ATP)

The first stage was to explicitly identify the method development goals, known as the ATP. The HPLC technique should allow for the simultaneous separation of the two medicines in formulation in a fair amount of time, with no interference from the sample matrix or degradation products. The primary goals were to optimize the chromatographic conditions in order to increase chromatogram quality in terms of resolution and tailing factor, and to effectively utilize the established technique for estimation of sofusbuvir and velpatasvir in tablet dosage form.

Step 2: Risk assessment

Numerous parameters, primarily the column design and the mobile phase, may impact separation quality in HPLC. Other elements that might impact technique performance include column temperature, detection settings, sample makeup, and injection volume. To identify important method attributes (CAA), a Fishbone diagram (Fig. 2) was created, and a systematic risk analysis was performed. All of the parameters impacting analysis quality were shown in this figure, and those that were crucial to quality were chosen for future investigation.

Each analytical process was scrutinized, and risk assessment was carried out based on risk severity, occurrence, and detectability. Although risk assessment seems to be simple based on a mathematical calculation (severity* occurrence *detectability), the right evaluation of each element was guaranteed by reference to good chromatographic science and practical experience in the area.

Step 3: Performing experimental design

Several preliminary experiments were carried out by trial and error to improve knowledge of technique performance and identify crucial independent factors and their influence on dependent variables. The chromatogram was recorded in a range of mobile phase compositions and ratios, including solvents like acetonitrile and ethanol, and ion pair reagent heptane sulfonic acid sodium of varying strength, in order to achieve proper separation of both sofosbuvir and velpatasvir drugs with acceptable system suitability parameters including retention time, theoretical plates, resolution, and asymmetric factor. Before developing an HPLC method employing AQbD, it is important to conduct preliminary testing and risk analysis to determine which parameters and responses will be most useful. Aside from exploratory trials, the Ishikawa (fishbone) diagram was utilized to identify and analyze crucial factors that provide an overall risk to the method's performance. The chromatographic conditions were further optimized using the Box-Behnken design (BBD). BBD is a multivariate response surface design defined by a collection of points at the midpoint of each edge of a multidimensional cube and center replicates. Using a BBD design with a standard set of 3 variables and 3 levels, a total of 17 chromatographic conditions with 5 center points were created (Table 1). The randomization of experimental runs reduced the bias impact of uncontrolled variables. As a consequence of thorough scouting, three major crucial parameters were chosen:, molarity of heptane sulfonic acid, ethanol volume, and acetonitrile volume. For separative analytical techniques like as chromatography, CQAs may be connected to system appropriateness factors such as retention duration, theoretical plates, resolution, and asymmetry factor, as well as method accuracy and robustness. The nominal values for all three parameters, molarity of heptane sulfonic acid sodium, ethanol volume, and acetonitrile volume, were 1 mM, 9% v/v and 11% v/v, respectively. In this setting, the molarity of heptane sulfonic acid sodium salt (A) was fixed between 1 and 5 mM. Similarly, the minimum and maximum volume of ethanol (B) were set at 5 and 10% v/v, respectively. Similarly, the minimum and maximum volumes of acetonitrile (C) were chosen to be 10 and 20% v/v, respectively. Design Expert (Version 9.0.1, Stat-Ease Inc., Minneapolis, MN, USA) statistical software was used to evaluate the produced data.

Table 1

Experimental design domain (BBD) for each run with responses
Run	Factors			Responses
Run	Molarity of HSA (mM) A	Volume of ethanol (% v/v) B	Volume of Acetonitrile (% v/v) C	Retention time of velpatasvir (min) R₁	Resolution factor for sofosbuvir R₂	Theoretical plates of velpatasvir R₃	Tailing factor of sofosbuvir R₄
1	3	10	10	3.412	6.35	4882	1.26
2	5	7.5	20	4.323	4.89	3214	1.21
3	5	5	15	4.221	5.12	3634	1.28
4	5	10	15	3.213	6.42	5218	1.23
5	1	7.5	20	3.724	6.38	3998	1.21
6	1	7.5	10	3.981	6.82	4123	1.15
7	3	7.5	15	3.724	6.41	3998	1.21
8	1	5	15	3.623	6.17	4202	1.28
9	3	7.5	15	3.812	6.67	3834	1.19
10	3	10	20	3.724	6.38	3998	1.21
11	3	5	20	3.222	6.98	4381	1.26
12	3	7.5	15	3.674	6.32	4234	1.18
13	3	5	10	3.724	6.38	3998	1.22
14	1	10	15	3.521	6.12	3813	1.26
15	3	7.5	15	4.772	3.56	3671	1.18
16	5	7.5	10	3.724	6.38	3998	1.21
17	3	7.5	15	4.212	4.81	3782	1.22

Step 4: Analysis of experimental results and optimization of method

Design expert Software was used to do a systematic statistical analysis of the experimental outcomes (version 12). Following the specification of variable constraints, numerical and graphical optimization was performed. To assess each individual response parameter, statistical methods such as predicted versus actual plots, ANOVA, lack of fit, prediction equations, and contour plots were employed, and design space was developed.

Step 5: Defining analytical method performance strategy

Overall knowledge of method performance under different experimental situations permitted the development of a control plan to limit risk and guarantee that the technique produces acceptable quality features.

Validation of method

According to ICH Q2 (R1) recommendations, the technique was validated in terms of several characteristics such as system suitability testing, linearity, limit of detection, limit of quantitation, precision, accuracy, specificity, and robustness.

System suitability test

Before the sample analysis, six replicates injections of the standard solution of sofosbuvir and velpatasvir (100 µg/ml) were performed to establish system suitability. The findings of system suitability factors such as resolution, theoretical plate (N), and tailing factor (T) were analyzed in terms of % RSD for six replicate drug injections.

Linearity and range

By completing five replicate measurements, the linear connection between peak area and concentration of both drugs was investigated across concentration ranges of 20–100 µg/ml for sofosbuvir and 5–25 µg/ml for velpatasvir. The analytical range was chosen based on the highest and lowest analyte concentrations at which acceptable linearity, accuracy, and precision were achieved.

Limit of detection (LOD) and limit of quantitation (LOQ)

Limits of detection (LOD) and quantitation (LOQ) for the proposed technique were determined in accordance with ICH guidelines by dividing the standard deviation of the response by the slope of the calibration curve for each drug by formula (LoD = 3.3 σ/S, LOQ = 10 σ/S).

Precision

Research on the repeatability and intermediate precision of the suggested approach was conducted. Three repetitions at each concentration were evaluated on the same day for repeatability and on separate days for intermediate precision (40, 60, and 80 µg/ml of sofosbuvir and 10, 15, and 20 µg/ml of velpatasvir). An overall mean and RSD (in %) were determined.

Accuracy

The methodological recovery experiments that examined the recovery of both medications at various levels using an optimal approach evaluated the accuracy. The experiment was conducted by adding a known quantity of each drug's standard to formulation at levels of 50, 100, and 150%, and then analyzing the samples using the suggested technique in triplicate. Three different concentrations of sofosbuvir standard (30, 60, and 90 µg/ml) were spiked into the formulation to conduct recovery experiments for sofosbuvir. Similar to this, velpatasvir recovery trials were conducted by adding three different concentrations of the velpatasvir standard (7.5, 15 and 22.5 µg/ml) to the formulation using the conventional addition technique. Then, recovery percentages for both drugs were determined.

Robustness

Several factors were purposefully changed, including the amount of acetonitrile used (89 and 81 ml), the wavelengths (257 and 253 nm), and the flow rates (0.93 and 0.89 ml/min), in order to test the ability of this newly developed analytical procedure to withstand small intentional changes in the method.

Specificity

To identify excipient interference, a synthetic mixture's chromatogram was compared to blank and standard solutions of the same medicines. The retention times of both sofosbuvir and velpatasvir on the chromatogram of the excipients must not exhibit any appreciable interference. The specificity of the technique was also assed by force degradation studies.

Analysis of developed formulation

The marketed tablet dosage form of sofosbuvir and velpatasvir was quantified using the developed HPLC technique. A formulation containing 400 mg of sofosbuvir and 100 mg of velpatasvir underwent analysis. The tablets were crushed in a mortar and pestle, and the amount of powder weighing out to 100 mg of sofosbuvir was weighed. This powder was then carefully transferred into a volumetric flask containing mobile phase, sonicated for five minutes, diluted to the appropriate concentration with the same diluent, and filtered through a 0.45 µm nylon membrane filter. For sofosbuvir and velpatasvir, the ultimate concentrations achieved were 1000 and 250 µg/ml, respectively. To create working sample solutions with final concentrations of 60 and 15 µg/ml of sofosbuvir and velpatasvir, respectively, suitable dilution of stock solutions with mobile phase was used. After injecting this solution into the HPLC system, the peak area was determined using the technique stated above, and triple analysis was carried out using the same steps.

Forced degradation

To demonstrate the stability-indicating capability and specificity of the suggested approach, forced degradation tests were conducted. To test the suggested method's capacity to distinguish between degradation products and active components, intentional deterioration under stressful circumstances, including water hydrolysis, acid hydrolysis, oxidative degradation (using 3.0% H₂O₂), and heat degradation (40°C and 60°C) was undertaken.

Acid degradation

After transferring 1.5 ml of the degradation stock solution to a 10 ml volumetric flask, 3 mL of 0.1N HCl was added, and the mixture was refluxed for 24 hours at 60 ⁰C before being cooled to room temperature for the acid degradation research. Diluent was added to the solution after it had been neutralized with 3 mL of 0.1N NaOH. When the sample solution was ready, it was filtered through a 0.45 µm filter, transported to HPLC vials, and injected into the HPLC system.

Alkaline degradation

In order to conduct the alkaline degradation study, 1.5 mL of the degradation stock solution was pipetted into a 10 ml volumetric flask. This was then mixed with 3 ml of 0.1N NaOH, refluxed for 10 hours at 60⁰C, and allowed to cool to room temperature. The solution was diluted with the diluent after being neutralized with 3 ml of 0.1N HCl. The aforementioned sample solution was placed into HPLC vials and injected into the HPLC system after being filtered using a 0.45-micron filter.

Oxidative degradation

In order to conduct the oxidative degradation study, 1.5 mL of the degradation stock solution was pipetted into a 10 mL volumetric flask. 1 mL of 3% hydrogen peroxide was then added, allowed to sit for 10 hours, and then diluted with the diluent. In order to transfer the sample solution into HPLC vials and inject it into the HPLC system, a 0.45 filter was used to filter it.

Photolytic Degradation

Ten tablets were precisely weighed for the photolytic degradation study, triturated into a fine powder, and then put onto a petri plate. The sample included in the petridish was exposed to harsh conditions for one week at 1.2 million lux in the UV chamber. Equivalent amounts of 15 µg/mL of velpatasvir and 60 µg/mL of sofusbuvir were used to generate the sample solutions. The sample solution was placed into HPLC vials and injected into the HPLC system after being filtered via a 0.45 µm filter.

Thermal degradation

Ten pills were precisely weighed, ground into a fine powder, and then put into a petri dish for the heat degradation study. Thermal stress was applied to the petridish-containing material for around one week at 110 ⁰C. Equivalent amounts of 15 µg/mL of VEP and 60 µg/mL of SOF were produced for the sample solutions, which were then transferred to vials and injected into the HPLC system.

Statistical analysis

Utilizing the Microsoft Excel 2007 program, statistical analysis was carried out, including the calculation of linear regression analysis, standard deviation, mean, and relative standard deviation. For response surface optimization using an ANOVA and the creation of a perturbation plot and 3D response surface plot, Design Expert software version 12.0.1 was utilized.

AQbD assisted method development

The main objective of analytical quality by design (AQbD) was to separate both peaks with excellent peak shape and satisfied characteristics in a shorter run time. Secondary objectives included robust technique with low variability and accuracy and precision of HPLC method with% RSD less than 2. The mobile phase settings were made to be as efficient as possible so that both medications could be separated quickly. In order to meet the system suitability parameter, several mobile phases and their various ratios, including acetonitrile, ethanol, and heptane sulfonic acid sodium with varying molarity and their combinations, were tested. Different pHs of heptane sulfonic acid sodium were investigated, however, it was found that the velpatasvir peak widened as the buffer pH rose. After that, the sample was made using mobile phase as a diluent to eliminate solvent interference. Furthermore, in early trials, the volume of ethanol and acetonitrile significantly affected the retention time. Critical factors were chosen for further investigation based on Ishikawa diagram and early tests, including the molarity of HSA (mM), the volume of the ethanol (% v/v), and the volume of the acetonitrile (% v/v), which were determined to have the most significant effects on system suitability characteristics (Fig. 2). A collection of points located in the middle of each edge of a multidimensional cube and center replicates define the BBD response surface design for multivariate optimization. By taking into account the effects of various variables, including the molarity of the HSA (A), volume of ethanol (B), and volume of acetonitrile (C), on the retention time of velpatasvir (R1), resolution of sofusbuvir (R2), theoretical plates of velpatasvir (R3), and tailing factor of sofusbuvir (R4), BBD was used to optimize the chromatographic conditions. Retention duration of velpatasvir (R1), resolution of sofusbuvir (R2), theoretical plates of velpatasvir (R3), and tailing factor of sofusbuvir (R4) were chosen as responses, and Table 1 shows the influence of these three variables on responses/CQAs.

Using Design Expert software, the model was also verified by analysis of variance (ANOVA), with the results shown in Table 2. Based on the PRESS value, the resolution of sofosbuvir (R2), the retention duration of velpatasvir (R1), and the tailing factor of sofosbuvir (R3) of quadratic models and two factor interaction model for theoretical plates of velpatasvir (R3), respectively, were chosen. Effects that were significant had p values lower than 0.05. Adequate Precision, defined as a signal-to-noise ratio higher than 4, is desired, and the signal-to-noise ratios achieved for each response showed appropriate signal strength (Table 2). The low standard deviation (% CV) and high adjusted R-square value suggested that the fitted models and experimental data were well correlated. For all responses, the predicted R-square value and the adjusted R-square value agreed to an acceptable degree. The final equation, in terms of actual components and factors, which can be used to make predictions about the response for given levels of each factor are for retention time of velpatasvir (R1) = 4.04 + 0.0790A – 0.1150B + 0.0190C – 0.2265AB + 0.2140 AC + 0.2035 BC + 0.0116 A² − 0.4059 B² − 0.1124 C² ; for resolution of sofosbuvir (R2) = 4.61 + 0.1650 A + 0.0775B + 0.3375 C + 0.3375 AB + 0.7375 AC − 0.1425 BC + 0.9722 A² + 0.3772 B² + 1.54 C²; for theoretical plates of velpatasvir (R3) = 4057.53–9.00 A + 212.00 B – 176.25 C + 493.25 AB – 164.75 AC – 316.75 BC; for Tailing factor of sofosbuvir (R4) = 1.22 + 0.0037A − 0.0100 B + 0.0063 C -0075AB -0.0150 AC -0.0225 BC + 0.0120 A² + 0.0545 B² – 0.0130 C². A positive value represents an effect that favors the optimization, while a negative value indicates an inverse relationship between the factor and the response.

To assess the impact of the variables on particular responses, response surface and perturbation plots were created. Perturbation plots show the shift from its nominal value, and curvature shows factor magnitude. The Fig. 3b shows that volume of ethanol showed most prominent effect on resolution of sofosbuvir, retention time for velpatasvir and tailing factor for sofosbuvir. The change in concentration of buffer have a impact on tailing factor of sofosbuvir.

As shown in Fig. 4(b–e) and Fig. 5(a-d) represents the two dimensional and three- dimensional graphs of RSM are generated as a function of the significant variables while the third variable was held constant at a specified level, usually the proposed optimum. The representative plots for responses are presented in Fig. 5(a–d) in which the interaction between the variables (factors A and B) and their mutual dependence is clearly observed, while factor C is kept constant. Figure 5(a) and (b) indicates that volume of ethanol showed prominent effect on retention time of velpatasvir and resolution of sofusbuvir. The retention time of velpatasvir decreased with an increase in volume of ethanol. The resolution of sofusbuvir increased with increase in volume of ethanol and decrease in concentration of HSA. Figure 5(c) represents that number of theoretical plates of velpatasvir increases with decrease in molarity of HSA. Figure 5(d) Depicts that the molarity of HAS and volume of ethanol showed prominent effect on tailing factor of sofusbuvir. The desirability plot for the responses was shown in Fig. 4a. The design provided 30 solutions for the optimal chromatographies condition during numerical optimization, however the number of solutions was decreased by establishing the targets. Three options were chosen to optimize the chromatographic conditions after a number of limits on factors and responses were specified. It was shown that the improved chromatographic condition's observed value was very near to its anticipated value, yielding a lower error rate and a higher desirability. Hence, the optimized condition; molarity of HSA (1 mM), the volume of ethanol (9% v/v) and volume of acetonitrile (11% v/v ml) resulted in the retention time of velpatasvir and sofosbuvir at 3.474 and 5.505 min, respectively. Using the design space, a multidimensional space can be established based on the characteristics and settings of the method, and this space can then be utilized to deliver optimal method performance in terms of system suitability and retention time.

Table 2

ANOVA, regression analysis of models and responses
Response	Standard deviation	Mean	% C.V.	PRESS	Adjusted R-square	Predicted R-square	Adequate Precision	p value
Retention time of velpatasvir (min) R₁	0.0943	3.80	2.48	0.9957	0.9849	0.9843	19.94	< 0.0001
Resolution factor for sofosbuvir R₂	0.5026	6.01	8.36	28.29	0.9804	0.9832	6.37	0.0255
Theoretical plates of velpatasvir R₃	228.59	4057.53	5.63	140005	0.9863	0.9805	13.51	< 0.0001
Tailing factor of sofosbuvir R₄	0.0155	1.22	1.27	0.0061	0.9817	0.9891	13.95	< 0.0001

a) Desirability plot

Validation of method

System suitability testing is used as a tool for method control. System suitability experiments were conducted to assess the behavior of the chromatographic system as part of the method development process. The results of system suitability testing, retention time (3.46 min ± 0.635 for VEL and 5.49 min ± 0.686 for SOF), resolution (6.35 ± 0.877), theoretical plate (4822 ± 0.147 for VEL and 4722 ± 0.499 for SOF), tailing factor (1.36 ± 0.826 for VEL and 1.26 ± 0.952 for SOF), and % RSD evaluated for six replicate injections were found to be acceptable. Velpatasvir and sofosbuvir showed a good correlation coefficient (r² = 0.9999 for Velpatasvir and 0.9991 for sofosbuvir in the given concentration range 5–25 µg/ml for Velpatasvir and 20–100 µg/ml for sofosbuvir respectively (Table 3 and Fig. 6). The LOD and LOQ were found to be 0.282 and 0.885 µg/ml, respectively for Velpatasvir and 1.05 and 3.15 µg/ml respectively for sofosbuvir Repeatability and intermediate precision was carried out by performing three replicates of three different concentration (10, 15 and 20 µg/ml of velpatasvir and 20, 60 and 80 µg/ml of sofosbuvir) showed % RSD less than 2% (Table 3), indicating acceptable precision in terms of repeatability of peak area measurement and sample application. The percentage recovery for both the drugs at three concentration levels (50, 100, 150%) was found in the range of 99.15–101.86%, suggesting suitability of method to perform routine drug analysis (Table 3). The robustness of the suggested approach was assessed by changing the liquid chromatography settings slightly. In addition, the approach was determined to be specific since the excipients did not interact with the retention time of both medicines. The chromatographic parameters assessed in this investigation were retention time and area. Table 3 displays the findings of the analysis of the robustness study, where a % RSD less than 2 indicates that the approach is robust and unaffected by slight changes in regular usage.

Table 3

Method validation data
Parameters	Velpatasvir	sofosbuvir
Linearity	5–25 µg/ml	20–100 µg/ml
Sensitivity LOD LOQ	0.282 µg/ml 0.885 µg/ml	1.05 µg/ml 3.15 µg/ml
Precision^a Repeatability(% RSD) Intermediate precision (% RSD)	0.412–1.013 1.021–1.459	0.219–0.987 0.877–0.912
Accuracy^b Recovery studies(%)	99.80-100.38	99.62–101.50
Robustness Change in flow rate(% RSD) Change in mobile phase composition (% RSD) Change in wavelength(% RSD)	1.12 0.89 1.11	0.88 0.72 1.01
^aMean of three replicates
^bAverage of three determinations at each level

Forced degradation study

During forced deterioration, it was discovered that SOF is vulnerable to degradation under acidic and oxidative stress conditions, while VEL is stable under all stress conditions. In each instance, the peak purity was between 99.96% and 100%. The findings from the peak purity analyzer revealed that the peak response of the active components was pure, demonstrating that no other drugs had the same retention time. The chromatograms with peak purity plot for each degradation condition were shown in supplementary file.

Analysis of formulation

In the current work, the HPLC technique developed was employed to quantify velpatasvir and sofosbuvir in tablet dosage form. The percentage of drug recovered in triplicate analyses of velpatasvir and sofosbuvir was 99.782 ± 0.699 and 99.958 ± 1.1354% w/w, respectively; thus, the established technique may be utilized regularly for the analysis of velpatasvir and sofosbuvir.

Eco-friendly method assessment

GAC has put out a number of ideas for developing sustainable analytical methods. Among such tactics, the 3R philosophy (Replace, Reduce, Reuse) called for the replacement of harmful solvents with more affordable, environmentally friendly alternatives when doing away with the need for them. The suggested approach efficiently substituted safer ethanol for hazardous acetonitrile or methanol when compared to earlier methods that had been applied for each medication combination. The amount of energy and solvents used by the suggested HPLC process is minimal. All of these traits proved that the suggested approach was more ecologically friendly than the one that had been previously published. Four cutting-edge measures, namely GAPI, Analytical Eco-Scale, AMGS, and AGREE metrics, which classify a process as eco-friendly, were used to evaluate the greenness profile.

Complex GAPI is a modified form of NEMI that has 11 subdivisions and is labeled with red, yellow, and green to indicate hazard, mild, and eco-friendliness, respectively. The technique specifics that must be evaluated must be applied in the program, which consists of 11 easy stages to obtain the outcome. Figure 7 depicts the created outcome, which demonstrates the method's sustainability and potential reach. The AES is an additional evaluation tool that deals with the penalty points (PP) that are tallied by the procedure. Four main divisions are utilized to compute PP: the quantity of reagents or chemicals required, the instrument and energy consumption, the volume of waste produced by the whole procedure, and the occupational risk to analysts. AES is determined by dividing the total penalty points from the previous four phases by 100 to get at PP. This sophisticated procedure produced four PPs, and the final AES score of 90 demonstrates the system's effectiveness in terms of sustainability. Table 4 illustrates the entire AES computation. AMGS is a combined and modified version of the HPLC environmental assessment instrument (HPLC-EAT) and the Safety Health and Environmental assessment (SHE). The AMGS findings were classified into three categories: instrument, solvent energy, and solvent Environmental Health and Safety (EHS) score. The method's total score is based on the sum of these three scores, which should be as low as feasible to make the technique as green as possible. After entering the relevant data into the AES Green Chemistry Institute's spreadsheet for the green evaluation, the final score achieved for the suggested technique was 59.49 (Fig. 7), indicating that the created approach has a positive influence on the environment. The most recent green evaluation tool, AGREE metrics, encompasses all 12 green analytical concepts. Based on the scores for each of the various principles, the total result, which was given as 1, was calculated. The method's greenness is indicated by a value that is nearer one. The overall result (Fig. 7) indicates that the method's impact on the environment is highly favorable and sustained for a longer period of time once the method's specifics have been entered into the software.

Table 4

Detailed calculation of AES for the proposed method
Reagents/Instruments	Penalty points(PP)
Solvents Ethanol (solvent) Acetonitrile(solvent) Heptane sulphonic acid(reagent) Instrument Energy (For HPLC ≤ 1.5 kWh/sample) Occupational Hazard Waste	2 2 2 1 0 3 ∑PP = 10 Analytical Eco Scale = 100 − 10 = 90

For the simultaneous measurement of velpatasvir and sofosbuvir in tablet dosage form, an AQbD-GAC principles based HPLC analytical technique that is green, simple, sensitive, accurate, reliable and cost-effective has been established. In order to achieve the ideal circumstances, the experimental design's use of the AQbD technique allowed for the simultaneous evaluation of the chosen parameters, including their interactions. The most important determinant for velpatasvir retention and sofosbuvir resolution by BBD was determined to be the volume of ethanol and acetonitrile. The use of experimental design and multi-criteria decision making is flexible, able to reduce the number of experiments required for the development and optimization of HPLC method, and can generate the most information in the shortest amount of time with the fewest number of experiments. The high formulation recovery rate indicates that there is no interference from the excipients in the formulation with the measurement. Additionally, the force degradation investigations demonstrated that the degradants peak was well defined and did not hinder the analyte's elution. The validation study confirmed the method's specificity, accuracy, linearity, precision, and robustness, which supported the choice of the ideal conditions. Finally, the outcomes of the green evaluation tools also demonstrated that the approach was the most environmentally friendly and readily adaptable for industrial and quality control objectives.

Acknowledgment: The authors are thankful to management of SVKM’s NIMIMS Shirpur for providing necessary facilities to carry out the research.

Conflict of Interest: None

Ethical Approval: Not Applicable

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No competing interests reported.

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A Box-Behnken design optimization based ecofriendly RP-HPLC method For Estimation of sofosbuvir And velpatasvir - Application to stability indicating assay

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Abstract

Figures

Introduction

Experimental

Materials

Instrumentation

Chromatographic conditions

Preparation of standard solutions

Method development by using QbD concept

Step 1: Analytical target profile (ATP)

Step 2: Risk assessment

Step 3: Performing experimental design

Step 4: Analysis of experimental results and optimization of method

Step 5: Defining analytical method performance strategy

Validation of method

System suitability test

Linearity and range

Limit of detection (LOD) and limit of quantitation (LOQ)

Precision

Accuracy

Robustness

Specificity

Analysis of developed formulation

Forced degradation

Acid degradation

Alkaline degradation

Oxidative degradation

Photolytic Degradation

Thermal degradation

Statistical analysis

Results and Discussion

AQbD assisted method development

a) Desirability plot

Validation of method

Forced degradation study

Analysis of formulation

Eco-friendly method assessment

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

Status:

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