Method operable design region for robust RP-HPLC analysis of pioglitazone hydrochloride and teneligliptin hydrobromide hydrate: incorporating hybrid principles of white analytical chemistry and design of experiments

There are no published RP-HPLC methods for simultaneously estimating THH and PIO in their fixed-dose combinations (FDCs). Earlier RP-HPLC techniques used hazardous organic solvents like acetonitrile and methanol to estimate PIO and THH separately in their prescription dose forms. These solvents endanger the environment, animal life, and human health. It is essential to eliminate, swap out, or minimize the use of these potentially harmful solvents in the RP-HPLC analysis of THH and PIO following the principles of green analytical chemistry (GAC) and the only recently developed idea of white analytical chemistry (WAC).

Ethanol, a more sustainable and environmentally friendly organic solvent, was used for sample preparation and mobile phase composition in the simultaneous estimation of PIO and THH to adhere to the principles of GAC and WAC. Compared to acetonitrile and methanol, ethanol is less harmful and volatile. It is a natural resource-based biodegradable solvent. As a result, the organic waste produced by chromatographic analysis using ethanol would not endanger aquatic life or humans.

The cost-effective RP-HPLC analysis of PIO and THH is further supported by the fact that ethanol is more affordable than acetonitrile and methanol. To maintain regulatory compliance with the ICH Q14 criteria and reduce waste generation during sample analysis, the Analytical Quality by Design (AQbD) approach was used in addition to adhering to the WAC concept. Analytical quality risk assessment and Design of Experiments (DoE) principles were used in this strategy.

The developed RP-HPLC method for the simultaneous measurement of THH and PIO offers a green and sustainable analytical solution that complies with regulatory requirements, minimizes waste generation, and lessens environmental effects by incorporating GAC, WAC, and the AQbD approach.

Implementation of analytical quality by design approach

The simultaneous determination of PIO and THH using a targeted RP-HPLC method was accomplished using the Analytical Quality by Design (AQbD) methodology. To enable chromatographic separation of the drugs following the system suitability testing criteria listed in IP 2018, the Analytical Target Profile (ATP) was developed. Its goal was to provide a method that was economical, reliable, and environmentally friendly. This led to the identification of critical method variables such as resolutions, tailing factors, retention factors, and the number of theoretical plates.

The development of the targeted RP-HPLC method was discovered to be dependent on the resolution between the peaks of THH and PIO (Response R1) and the tailing factor for the peak of THH (Response R2). The volume ratio of ethanol to water (Critical method variable A), pH of the mobile phase (Critical method variable B), flow rate (Critical method variable C), column oven temperature (Critical method variable D), and detection wavelength (Critical method variable E) for the desired responses R1 and R2 were also identified as potential critical method variables. Figure 2 contains a list of potential procedure variables, responses, and the analytical target profile.

The method development procedure for the RP-HPLC technique was optimized to simultaneously estimate PIO and THH while taking into account critical variables and responses for successful chromatographic separation by using the AQbD approach, which guides method development by particular analytical aims.

An analytical quality risk assessment was performed on the potential procedure variables to determine how they would affect the chosen responses (R1 and R2). The risk priority number (RPN) ranking and filtering method through the Plackett–Burman design was used to conduct this evaluation. Critical procedure variables A and B were determined to be high-risk based on the analysis; thus, they were further investigated for the RP-HPLC method's optimization using DoE-based response surface methodology. This strategy attempted to boost the method's overall performance and dependability by enhancing the identified critical procedural variables.

Using DoE-based response surface methodology, the high-risk critical procedural variables A and B were further examined for their substantial main effects, two-way interactions, and quadratic effects on responses R1 and R2. A central composite design was implemented using the Minitab 18 software to carry out this process. The volume ratio of ethanol to water (critical process variable A) should be between 60:40 and 70:30%v/v, and the pH of the water (critical procedure variable B) should be adjusted to be between 2.5 and 3.5 using glacial acetic acid, it was found through optimization. Finally, by employing ethanol/water (65 + 35%) at pH 3.0, the final chromatographic separation of THH and PIO was accomplished. Figure 5 illustrates the retention times for the THH and PIO peaks, which were determined to be 2.41 and 3.75 min, respectively. Notably, for the chromatographic peaks of THH and PIO, the resolution, tailing factors, retention factors, and the number of theoretical plates all fulfilled IP 2018 criteria for system suitability testing (n = 7). The following mathematical models (Eqs. 1 and 2) were used to forecast the responses and navigate the method operable design region for the optimization of the RP-HPLC process. These models were crucial in helping to improve the process and get the desired results.

$$} - } = - . + .0 } - A \, + . } - B \, - 0.000 } - A*} - A \, - 0. } - B*} - B - 0.00 } - A*} B$$

(1)

$$} - } =\; .0 - 0.0 } - A \, - . } - B \, + 0.000 } - A*} A \, + 0. } - B*} - B \, + 0.00000 } - A*} B$$

(2)

Red model-based assessment for validation efficiency

According to the ICH Q2 (R1) recommendations, the Red model-based assessment (R1 to R4) was used to evaluate the effectiveness of the validation of published and proposed RP-HPLC techniques. When calculating THH and PIO separately in their pharmaceutical dose forms, the published RP-HPLC methods showed a flawless score of 80 out of 100 for all four principles. Due to its wider scope and application, the proposed method, which uses ethanol as the solvent and the analytical quality by design approach, was able to simultaneously estimate THH and PIO in their Fixed-Dose Combination (FDC) and earned an additional 20 points. As a result, the proposed method received an impressive validation assessment score from the Red model of 100 out of 100.

Green model-based assessment for procedure greenness

The Green model-based assessment was carried out to evaluate the environmental impact of the published and suggested RP-HPLC methods for the simultaneous determination of THH and PIO. The four core GAC principles (G1 to G4) were applied in this evaluation, which also made use of a variety of GAC tools, including the AGREE calculator, NEMI standards, Eco-scale assessment (ESA), and the complex GAPI programme. The procedure greenness profile of the published RP-HPLC procedures has been found to require the use of hazardous organic solvents (acetonitrile and methanol) and produce more than 300 mL of organic waste, suggesting serious environmental risks. As a result, these techniques scored 51 out of 100 in the evaluation based on the Green model. As opposed to acetonitrile and methanol, the suggested RP-HPLC estimation of THH and PIO in FDCs used ethanol, a less volatile, biodegradable, and environmentally benign solvent. Additionally, it produced only 100 mL of organic waste, thus lessening its impact on the environment. As a result, the suggested strategy received an evaluation of 80 out of 100 using the Green model. Figure 6 compares the complex GAPI software-based pictograms, the AGREE calculation, and the NEMI scale evaluation for the proposed and published RP-HPLC analyses of FDCs containing PIO and THH. These visual representations provide a thorough picture of how each strategy affects the environment.

Fig. 6figure 6

A Green profile assessment of proposed method for estimation of PIO and THH using AGREE, NEMI and GAPI method B White analytical chemistry-based assessment and comparison of developed and published RP-HPLC methods for estimation of PIO and THH using RGB model

Blue model-based assessment for cost and time efficiency

The Blue model-based assessment was used to compare the published and proposed approaches for the estimation of THH and PIO for cost, time, and user-friendliness. For each FDC of THH and PIO, distinct chromatographic applications as well as pricey organic solvents (acetonitrile and methanol) were required per the stated procedures. The proposed approach, in contrast, used a single chromatographic condition and a more cost-effective solvent to estimate both substances simultaneously. As a result, the suggested approach needed less money, time, and resources. Additionally, the reduced chromatographic conditions of the suggested approach were thought to make it more user-friendly. As a result, the Blue model-based assessment gave the proposed method a score of 100 (plus an extra 20 points) out of 100 for cost efficiency, time efficiency, and user-friendliness.

Principles of white analytical chemistry

The colors red, green, and blue are blended to generate the color white. Similarly to this, the published and suggested approaches' WAC (White Analytical Chemistry) scores were calculated by averaging the results from the Red, Green, and Blue models (see Table 6 for more information). In their FDC, the published RP-HPLC techniques simultaneously estimated THH and PIO, earning a WAC score of 70.33 out of 100. For the same analysis, the proposed RP-HPLC method, in contrast, received a remarkable WAC score of 93.33 out of 100. This suggests that the suggested procedure performed exceptionally well while analyzing the samples. Figure 6 compares the WAC scores and RGB models for the proposed and published RP-HPLC procedures.

Table 6 Assessment of published and proposed RP-HPLC methods for estimation of THH and PIO using principles of white analytical chemistry, RGB model, NEMI, ESA, AGREE and GAPI tools

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