U.S. flag

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

  • Publications
  • Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

  • Advanced Search
  • Journal List
  • Turk J Pharm Sci
  • v.18(3); 2021 Jun

Logo of tjps

Development and Validation of an HPLC Method Using an Experimental Design for Analysis of Amlodipine Besylate and Enalapril Maleate in a Fixed-dose Combination

Diren sarisaltik yasin.

1 Dicle University Faculty of Pharmacy, Department of Pharmaceutical Technology, Diyarbakır, Turkey

Alev ARSLANTÜRK BİNGÜL

2 Dicle University Faculty of Science, Department of Chemistry, Diyarbakır, Turkey

Alptuğ KARAKÜÇÜK

3 Gazi University Faculty of Pharmacy, Department of Pharmaceutical Technology, Ankara, Turkey

4 Ankara Medipol University Faculty of Pharmacy, Department of Pharmaceutical Technology, Ankara, Turkey

Zeynep Şafak TEKSİN

Objectives:.

The aim of this study was to develop and optimize a simple, cost-effective, and robust high-performance liquid chromatography (HPLC) method by taking an experimental design approach to the assay and dissolution analysis of amlodipine besylate and enalapril maleate from a fixed-dose combination tablet.

Materials and Methods:

The chromatographic analysis was performed on a C18 column (4.6x250 mm id., particle size of 5 μm). The injection volume was 5 μL, and the detection wavelength was 215 nm. A Box-Behnken design was used to test the robustness of the method. The flow rate (1, 1.2, and 1.4 mL/min), column temperature (25°C, 30°C, and 35°C), methanol ratio of the mobile phase (5, 10, and 15%), and pH of the mobile phase (2.8, 3, and 3.2) were selected as independent variables. The method was validated according to International Conference on Harmonization guidelines. Dissolution of the tablets was performed by using USP apparatus 2 and analyzed using the optimized HPLC method. Multivariate linear regression analysis and ANOVA were used in the statistical evaluation.

Linear models were fitted for all variables. The flow rate was the most significant factor affecting the APIs’ concentrations. The optimized method included the following parameters: Column temperature of 25°C, 10% methanol as the mobile phase, pH of 2.95, and flow rate of 1.205 mL/min. Retention times were 3.8 min and 7.9 min for enalapril and amlodipine, respectively. The method was found to be linear in the range of 0.8-24 μg/mL (R 2 >0.999) and 1.6-48 μg/mL (R 2 >0.999) for amlodipine and enalapril, respectively. Both APIs were dissolved more than 85% within 10 min.

Conclusion:

The experimental design was proved as a useful tool for the determination and separation of enalapril maleate and amlodipine besylate in dosage forms. The optimized method can be used for in vitro performance and quality control tests of fixed-dose tablet combinations containing enalapril maleate and amlodipine besylate.

INTRODUCTION

At the early stages of the treatment of hypertension, it can be useful to choose monotherapy to observe the effect and the side effects of the drug. However, monotherapy can be insufficient to reach the target blood pressure in a majority of patients. 1 , 2 , 3 A greater therapeutic benefit can be achieved with two or even more antihypertensive drugs. 4 Therefore, fixed-dose combinations (FDCs) are frequently used in cardiovascular diseases such as hypertension. In order to develop an FDC product including two drugs, certain conditions must be met. For instance, a synergistic effect can be observed using two drugs together, or a side effect related to a drug may be eliminated using the other drug concurrently. 5 In the treatment of hypertension, there is a synergistic effect between calcium channel blockers (CCBs) and angiotensin-converting enzyme inhibitors (ACEIs). In addition, ACEIs such as enalapril prevent peripheral edema caused by CCBs such as amlodipine. 6

Amlodipine is a long-acting CCB that inhibits the transmembrane influx of calcium ions into vascular smooth muscle and cardiac muscle. It is indicated for the treatment of hypertension and coronary artery disease when used alone or in combination with another antihypertensive agent. 7 Amlodipine is given orally as besylate in general, but doses are calculated in terms of amlodipine base. A dose of 6.94 mg of amlodipine besylate is equivalent to 5 mg of amlodipine base. The recommended dose of amlodipine is 5-10 mg once daily. 8 Since amlodipine is a weak base, it exhibits high solubility in physiological pH values. Although the bioavailability of amlodipine is approximately 60%-65%, it is defined as a highly permeable drug because of the 90%-95% excretion rate as an inactive metabolite in the urine Shohin et al. 9 Amlodipine is a class 1 drug according to the Biopharmaceutics Classification System (BCS). 9 , 10 , 11

Enalapril is the ethyl ester of enalaprilat, an ACEI indicated for the treatment of hypertension and heart failure. Enalapril is available as maleate salt in the drug market. Enalapril maleate is a white crystalline powder sparingly soluble in water. Although the solubility is 25 mg/mL at pH 3.5, it increases to 200 mg/mL at pH 7.0. It is defined as BCS class 3 with high solubility but low permeability properties. 12

There are high-performance liquid chromatography (HPLC) methods recommended in United States Pharmacopeia (USP42) for analysis of amlodipine besylate 13 and enalapril maleate, 14 separately and a few liquid chromatography methods are available in the literature for analyses of amlodipine, 15 and enalapril, 16 , 17 individually or in combination with other drugs. 18 , 19 , 20 , 21 , 22 , 23 However, these methods are not suitable for the separation of amlodipine and enalapril in the same dosage unit. Nevertheless, there are three published articles for HPLC analysis of amlodipine besylate and enalapril maleate together in dosage forms. 24 , 25 , 26 However these methods contain a high ratio of organic solvents in the mobile phase, which is environmentally inappropriate according to the green chemistry approach. An important principle of green chemistry is to reduce toxic organic solvents and to consume safer chemicals. 27 , 28 Relating to the green analytical chemistry approach, Korany et al. 27 recommended reducing the acetonitrile amount in the methods and using multiparameter methods such as design of experiment (DOE) instead of the one factor at a time (OFAT) approach. 28 In the method developed by Chaudhari 24 , the mobile phase contains 50% acetonitrile and 40% methanol and a higher injection volume (20 µL), which increases the consumption of mobile phase and the linearity range was comparatively narrow (0.5-6 µg/mL and 0.5-8 µg/mL for enalapril and amlodipine, respectively). In another method, the mobile phase includes 60% acetonitrile, the injection volume was 20 µL, and the linearity range was not suitable for lower concentrations (20-100 µg/mL), which might be essential for the initial points of the dissolution tests. 25 In the method developed by Masih et al. 26 , 50% 1N HCl and 50% methanol were included in the mobile phase, and the injection volume was 10 µL. Additionally, none of the studies include the application of DOE in robustness testing in validation for amlodipine besylate and enalapril maleate. Furthermore, there is no dissolution analysis of enalapril and amlodipine in the combined dosage form in the literature.

DOE is a well-defined mathematical methodology to demonstrate how to obtain maximum reliable and valuable scientific information by performing minimal experiments. 29 In this technique, the effects of multiple variations on one or more responses can be investigated at the same time, instead of changing OFAT. Although conventional developmental approaches are mainly empirical and are often conducted using the changing OFAT method, DOE provides the facility of performing systematic and multivariate experiments in order to entirely understand the process and to assess the statistical significance of the variables. 30 , 31 By creating experimental matrix, DOE allows faster visualization and determination of more factors at a time. 32 Besides, in OFAT approach factors are evaluated independently, so it is assumed that the factors do not influence each other. However, the potential interactions between the factors can be identified using the appropriate DOE model. 33 , 34 In the pharmaceutical field, DOE helps to understand the effects of the critical formulation and process variables on the final product. 35 , 36 DOE can be used for factor screening and characterization of a new system or optimization of a characterized system. Factors are independent variables that might affect the results of critical responses. For instance, in an analytical method development process, the flow rate can be an independent factor that has potential effects on the peak area of the analyte. In a screening design it is aimed to investigate numerous factors that might affect the response and to discover the factor which has the most significant influence on the responses. 37 On the other hand, in an optimization process, the main objective of which is to define the optimal conditions and settings for the factors. 38 In case more than one factor must be examined, the multivariate optimization designs can be reasonable in order to evaluate different factors at the same time and to determine if interactions exist between factors. 37 , 38

In analytical chemistry, DOE can be used for chromatographic analytical method development to optimize the sampling preparational, column, detector, instrumental, or environmental factors. 31 , 39 Similarly, analytical method validation parameters such as accuracy, linearity, precision, or robustness can be performed by experimental design approaches. 29 , 40 , 41 , 42 , 43 , 44 , 45 , 46 Using DOE in validation studies is recommended in the International Conference on Harmonization (ICH) guidelines. 27 , 47 There have been many studies in which DOE was applied to robustness. 31 , 32 , 43 , 48 , 49 Experimental design targeting robustness is a good approach to fully understand the factors with effects on the responses and provide maximum information about the method in a short time. Robustness should be built into methods in the pre-validation stages; otherwise, a robustness test performed too late has a risk of obtaining inappropriate results which can cause redevelopment and revalidation. 50 Therefore, a robustness test in the earlier stage of the method development process leads to a saving of effort, time, and money. Experimental data obtained from early stages can aid in performance method evaluation and can be used to guide further method development. 51

Optimization can be performed by using response surface methodology (RSM) designs such as the Box-Behnken design (BBD) and the central composite design (CCD). 49 , 52 The BBD is a second-order design that allows investigation of numerous factors with three levels. It is preferable to the CCD because it prevents an unrealistic extreme scenario by creating the experimental matrix without containing extreme points in the same experiment. 33 , 52 BBD is used in analytical method optimization in many studies. 6 , 48 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65

In this study, a simple, rapid and robust HPLC method with photodiode array (PDA) detection at 215 nm was developed for the determination and separation of amlodipine besylate and enalapril maleate in FDC tablets. This method, which is available for assay and dissolution studies, was fast, environmentally friendly, and more cost-effective than the earlier published methods. 24 , 25 , 26 In this study, DOE was adapted to the robustness parameter of the analytical method for determining amlodipine and enalapril together. DOE principles were used in the method development of amlodipine and enalapril for the first time. The validation of the method was performed according to the ICH Q2 (R1) guideline. 47 The BBD was used for the optimization of the method. The optimized HPLC method was applied to dissolution and assay analysis of an in-house FDC tablet including amlodipine and enalapril.

MATERIALS AND METHODS

Materials and reagents.

HPLC-grade methanol, o-phosphoric acid and hydrochloric acid 37% were obtained from Merck, Germany. Amlodipine besylate (Hetero Drugs, India) and enalapril maleate (Zheijiang Huahai, China) were kindly gifted by Nobel Pharma, Turkey.

The FDC tablet contains 6.94 mg of amlodipine besylate and 10 mg of enalapril maleate as APIs.

The HPLC system was a Shimadzu chromatographic system (Japan) with LC-20AD pump, SPD-M20A PDA detector at a wavelength of 215 nm, a reversed phase C18 column (4.6x250 mm id., particle size of 5 µm) from Waters ® (USA). The HPLC system was controlled by LC Solution Software. Design Expert ® Version 9 (Stat-Ease Inc, USA) was used for the experimental design and statistical analysis of data. A pH meter (PASS1 P11-BNC-Bante, England) was used to control the aqueous buffer. Dissolution test was performed with Pharmatest ® Dissolution System (Germany).

Chromatographic conditions

The mobile phase was a mixture of methanol and water (pH adjusted to 3.0 with o-phosphoric acid) in the proportion of 10:90 (v:v). The injection volume of the samples was 5 µL. The flow rate was 1.2 mL/min. The detector wavelength was 215 nm and the column temperature was 30°C.

Preparation of standard solutions

The standard solution was prepared according to the following process: 6.94 mg of amlodipine besylate (equivalent to 5 mg amlodipine base) and 10 mg of enalapril maleate were weighed and transferred to a 50 mL volumetric flask and diluted to the appropriate volume with 0.1N HCl. This solution included 0.1 mg/mL of amlodipine base and 0.2 mg/mL of enalapril maleate. The calculations were performed considering amlodipine base and enalapril as maleate salts because of the dose proportionality in market products .

Calibration procedure

Calibration series were prepared in volumetric flasks by the appropriate dilution of standard solution with 0.1N HCl. The calibration curve was plotted with eight concentrations in the range of 0.8-24 µg/mL for amlodipine and 1.6-48 µg/mL for enalapril (as maleate). The experiments were performed in three replicates for each level. The linearity of the calibration curve was evaluated by the linear regression statistics of concentrations against peak area.

Statistical analysis

Experimental design.

Experimental plan, data analysis and optimization process were executed in Design Expert ® Version 9 by using the BBD. The BBD is a three-level and multi-factor design which is a combination of 2K factorial and balanced incomplete block designs. In this study, four factors with three levels for each were determined as given in Table 1 .

An external file that holds a picture, illustration, etc.
Object name is TJPS-18-306-g8.jpg

The significant factors in the model were determined by multivariate linear regression analysis and ANOVA F-test and its lack of fit with a confidence interval of 95% for each response. Significant factors were determined by the probability level that the p value is less than 0.05 and one-factor graphs.

Assay in FDC tablets

The FDC tablet containing amlodipine besylate and enalapril maleate was prepared by using direct compression method. For assay of the tablets, 10 tablets for each product were selected at random and weighed. Then these tablets were powdered, and a quantity of the powder (equivalent to 5 mg of amlodipine and 10 mg of enalapril maleate) was accurately weighed and transferred to a 50 mL volumetric flask. A 30 mL volume of diluent solution (0.1N HCl) was added and mixed for 15 min in magnetic stirrer. Then, it was diluted with the same solution to the volume and mixed in an ultrasonic bath for 10 min. A 4 mL volume of this solution was transferred to a 25 mL volumetric flask and diluted to the volume using the same solvent and was held in an ultrasonic bath for 5 min. The samples were filtered through a syringe tip filter of 0.45-µm pore size and then analyzed using HPLC.

Dissolution studies

Dissolution studies were performed using USP apparatus II (paddle method) in 0.1N HCl (pH 1.2). The dissolution volume was 900 mL, and the temperature was 37°C±0.5°C. The paddle rotational speed was 75 rpm. Samples (2 mL) were withdrawn at 10, 20, 30, 45, and 60 min, and the same amount of fresh media was replaced. The samples were filtered through 0.45-µm membrane filters to vials and analyzed by the optimized HPLC method. The dissolution profiles were evaluated as the cumulative drug dissolved (%) over time. All experiments were performed in n=3 and the cumulative amounts were evaluated as the mean ± standard deviation (SD).

RESULTS AND DISCUSSION

The chromatograms of diluent (blank) and those obtained from the standard solutions of amlodipine and enalapril are given in Figure 1 , ​ ,2 2 respectively. The initial method provided good separation in a short time of 3.8 min for enalapril and 7.9 min for amlodipine. This level of separation is acceptable in a conventional method development process. A robustness study with DOE was also performed.

An external file that holds a picture, illustration, etc.
Object name is TJPS-18-306-g1.jpg

Chromatogram of the placebo (blank medium) for specificity testing

PDA: Photodiode array

An external file that holds a picture, illustration, etc.
Object name is TJPS-18-306-g2.jpg

Chromatogram of enalapril (8 μg/mL, as maleate) and amlodipine (4 μg/mL) in the initial method

Robustness with DOE principles

According to the ICH Q2 (R1), in a robust method, small variations in certain method parameters do not affect the reliability and results of the method. 47 These small variations are important for the pharmaceutical industry in terms of the transfer of the analytical method from research and development to the quality control laboratory or from one company to another. In other words, it is the indication of the strength of the method. 51 In order to assess the concurrent influences of the changes in factors on the defined responses, a multivariate analysis by DOE is recommended in robustness studies. 43 DOE is used in analytical method development for two main purposes: To determine the most significant factor influencing the response of the study and to discover the optimized value of the factors for best results for the response. 37

The DOE plan in a robustness test includes the following stages: 31

Selection of factors and their levels

Robustness studies are an excellent opportunity to apply statistical experimental design to provide data-based control of the method. 51 Since there are many factors that might affect the method, it is vital to choose the right factors. In robustness studies of liquid chromatography, the most frequently preferred factors are the pH of the mobile phase, analysis time, flow rate, column type, temperature, composition of the mobile phase, detection wavelength, chosen filters, or the variations in sample preparation such as dilution, shaking time, or heating temperature. 39 , 51 It should be noted that there are no absolute truths in selecting factors in a DOE process; the chosen factors should comply with the purpose. According to ICH Q2 (R1), the following variations were recommended for the robustness test of HPLC methods: 1) pH of the mobile phase, 2) composition of the mobile phase, 3) column type, 4) temperature, and 5) flow rate. Except for the column type, all recommended factors (mobile phase ratio, pH, flow rate, and column temperature) were investigated in this study. The chosen factors and their pre-defined levels have the potential to affect the method depending on the analyst, laboratory or equipment, and environmental conditions. 47

After selecting the factors, it is necessary to define their levels. In a two-level model such as Plackett-Burman Design (PBD) or two-level factorial designs, a maximum and a minimum limit are required for the factor values. In three-level designs, additional middle values, which generally represent the target or the expected value, are added to the design. Defining the levels is a critical step in experimental design. Particularly in two-level designs in which inappropriate levels were used, inaccurate and low-quality results can be obtained. 33 In order to avoid this problem, a three-level BBD design is preferred. The levels of the factors are usually defined symmetrically around the nominal level, which is the middle level in a three-level design. The interval chosen between the levels is generally decided according to the operator’s personal experiences or anticipated changes from one laboratory to another. For example, if the developed method will be transferred to another laboratory, the pH can be measured using a pH meter with a small deviation, so pH should be considered as critical. The pH of a solution varies with a deviation of 0.02 with a confidence limit of 95%. 50 Therefore, this limit is acceptable for the pH in a robustness test. The interval of pH was ±0.02 in this study. The levels of column temperature were decided ±5°C as recommended in the article by Vander-Heyden et al. 50 , which was aimed to guide a robustness parameter in method development. The levels of other factors, selected as 5% for mobile phase composition and 0.2 mL/min for flow rate, were in agreement with previous similar studies. 32 , 43 , 65

Defining responses to be investigated

In the HPLC studies where robustness was investigated by DOE, various responses such as peak area, peak height, determined concentration, retention time, tailing factor, theoretical plate number, and resolution were used. The most important selection criterion for a response to use in factor evaluation is ease of measurement. 39 Additionally, using a large number of responses can lead to confusion when interpreting the results. Therefore, API concentrations calculated from the peak areas were selected as responses in this study.

Choosing an experimental design

A suitable experimental design should be selected based on the aim of the study. In case a large number of factors might affect the method, the aim can be to discard some factors that have no significant effect on the response. For this purpose, a screening design such as PBD can be used. On the other hand, if the main objective is to investigate the effects of the relatively lower number of factors deeply, or optimize the most effective factors, optimization designs should be preferred. 31 Generally, optimization is carried out following determination of the most significant factors by screening design. In case there is a factor known to be highly effective in the separation (such a flow rate or temperature), optimization designs can be preferred directly. 37 In this study, factors that may affect the results, such as the column temperature, flow rate, and composition of the mobile phase, were chosen with the purpose of performing an optimization. Another reason for choosing an RSM design is to observe any interaction between the factors.

The most used RSM designs are CCD and BBD. BBD requires the fewest experiments among the RSM designs because it does not contain values that are maximum or minimum values in the experimental matrix. 33 Since BBD requires fewer experiments, and the experimental matrix does not contain the highest or lowest level in the combination, this experimental design prevents an unrealistic extreme scenario. Therefore, the experiment number, time, and cost are reduced. BBD can evaluate the linear and non-linear effects of factors. 34 , 66 Thus, BBD was selected for the experimental plan, data analysis and optimization process using the Design Expert ® Version 9 software.

Execution of experiments

Experimental executions were computed by Design Expert Software. Robustness was assessed by using BBD with 29 runs. Experimental design and calculated concentrations of enalapril (as maleate) and amlodipine and the corresponding responses are given in Table 2 .

An external file that holds a picture, illustration, etc.
Object name is TJPS-18-306-g9.jpg

Statistical evaluation of responses and their interpretations

The best fit model was linear for all factors and their responses. In the literature, linear analysis is frequently indicated and recommended in robustness tests. 29 , 30 Therefore, our results were as expected. Linear models are used to show the main effects of factors.

The equation model for Y 1 (enalapril concentration) and Y 2 (amlodipine concentration) was as follows:

Y 1 =32.32+0.079X 1 -5.32X 2 +0.11X 3 +0.51X 4           (Equation 1)

Y 2 =16.19+0.12X 1 -2.72X 2 +0.020X 3 +0.021X 4         (Equation 2)

Where, X 1 is column temperature, X 2 is flow rate, X 3 is the methanol ratio in the mobile phase, and X 4 is the pH of the mobile phase.

The ANOVA results are given in Table 3 . The significant effects showed a p value less than 0.05, a low SD (CV %), and a high adjusted R-square (adj R 2 ) value indicating a good relationship between the experimental data and those of the fitted model. The predicted R-square (pred R 2 ) value was in agreement with the adj R 2 for all responses.

An external file that holds a picture, illustration, etc.
Object name is TJPS-18-306-g10.jpg

The one-factor graphs ( Figure 3 , ​ ,4) 4 ) demonstrated that the flow rate was the most significant factor on the responses; inverse proportionality was found (p<0.05). It was revealed that the most critical factor in robustness is the flow rate. The methanol ratio in mobile phase, temperature, and pH had no significant effect on the calculated concentrations of amlodipine and enalapril in defined levels. Kovacs et al. 30 have evaluated the same factors in their robustness test with different responses such as peak asymmetry and retention time. They found that the proportion of methanol in the mobile phase had a significant effect on the retention time of strontium ranelate. Similarly, Dhumal et al. 32 found that the proportion of methanol in the mobile phase and the flow rate had a negative effect, while the pH had a positive effect on the peak area and the determined tapentadol concentration. In another study, in which the same factors and different responses (tailing factor, retention time and theoretical plate) were used, the most effective factors were found to be the methanol composition and pH. 45 However, the significance of factors depends on the APIs and chromatographic conditions. If we had defined our levels more broadly for other factors (methanol ratio, temperature, and pH) or if we had assessed more responses such as tailing factor or resolution we might have observed a meaningful effect with other factors. However, this was not considered to be an error in the design because the DOE is specific to the purpose. In this study, we would like to see how possible rational changes would affect the analytical results, rather than creating a design space based on the extreme values of factors.

An external file that holds a picture, illustration, etc.
Object name is TJPS-18-306-g3.jpg

A-D) One-factor graphs of the main effects of the factors on amlodipine concentration

An external file that holds a picture, illustration, etc.
Object name is TJPS-18-306-g4.jpg

A-D) One-factor graphs of the main effects of the factors on enalapril concentration

Two-way interactions between independent variables were found to be insignificant (p>0.05). Therefore, a simple screening design, such as a PBD, which is the most popular design in robustness evaluation, might be used in this study. 37 However, since PBD is a two-level design, it can cause inaccurate statistical evaluations when unsuitable factor levels are selected or when there might be an interaction between the factors. If an experimental model is needed to determine tolerable variations, an optimization design is recommended by Sahu et al. 31 For this reason, as discussed before, we preferred a BBD that contained a third level (target middle level) and provided more information about the method. There have been similar studies with other drugs in which calculated drug concentrations were the only response and flow rate was the only significant factor in the response. 43 , 46

Optimization

Following linear model fitting, an optimization run was performed, and factor settings were defined using the prediction spreadsheet of the software ( Figure 5 ). The final optimized parameters were a flow rate of 1.205 mL/min, pH of 2.95, and column temperature of 25°C. The factors described in the optimization were very close to the nominal levels in the BBD design. Non-etheless, these minor changes caused a better peak shape for amlodipine and a lower tailing factor (from 1.417 to 1.164, p<0.05) ( Figure 6 ). Retention times were not changed in the method with 3.8 min and 7.9 min for enalapril and amlodipine, respectively.

An external file that holds a picture, illustration, etc.
Object name is TJPS-18-306-g5.jpg

Optimization conditions of independent variables according to the Design Expert ® Software

An external file that holds a picture, illustration, etc.
Object name is TJPS-18-306-g6.jpg

Chromatograms of enalapril (8 μg/mL, as maleate) and amlodipine (4 μg/mL) in the optimized method

The optimized method was validated based on international guidelines.

The linearity of the peak area versus concentration was shown in the range of 0.8-24 µg/mL for amlodipine and 1.6-48 µg/mL for enalapril (as maleate). Linearity results were given in Table 4 . The linearity range was kept wider than the previously published methods. 24 , 25 , 26 The lower concentrations are considered for the first minutes of the dissolution study, and higher values are for the assay.

An external file that holds a picture, illustration, etc.
Object name is TJPS-18-306-g11.jpg

Accuracy was demonstrated using six different solutions, containing 1.39, 2.78, 5.56, 12, 16, and 19.2 µg/mL of amlodipine and 2.78, 5.56, 11.12, 24, 32, and 38.4 µg/mL of enalapril maleate. Recovery values were obtained within the range of 98.6%-101.6%. The low value of relative standard deviation (RSD) less than 1% indicates that the proposed method is accurate. Results are presented in Table 5 .

An external file that holds a picture, illustration, etc.
Object name is TJPS-18-306-g12.jpg

Repeatability

Repeatability is also termed intraday precision and provides information about the precision under the same operating conditions in a short time interval. 47 Repeatability was assessed using 10 determinations of the solutions including 16 µg/mL of amlodipine and 32 µg/mL of enalapril maleate. The recovery values were 99.9±0.31% and 100±0.07% for amlodipine and enalapril maleate, respectively.

The RSDs were 0.307% and 0.0711% for amlodipine and enalapril maleate, respectively.

Intermediate precision

Intermediate precision was assessed using the interday variations. Two different concentrations (4 and 16 µg/mL for amlodipine and 8 and 32 µg/mL for enalapril maleate) were analyzed on three consecutive days. The RSD values of interday precision were less than 1%, confirming the method precision. The results are given in Table 6 .

An external file that holds a picture, illustration, etc.
Object name is TJPS-18-306-g13.jpg

The low RSD value for intermediate precision and repeatability of the method as well as within-day and day-to-day variation suggested that the method was precise within the range of measurement.

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

LOD and LOQ were calculated based on the SD of the response and the slope by using the equations below:

L O D = 3 . 3 × σ S ( Equation 3 )

L O Q = 10 × σ S ( Equation 4 )

where s is the SD of the response, and S is the slope of the calibration curve. According to the equations, LOD values were 0.0631 µg/mL and 0.0424 µg/mL and LOQ were 0.19 µg/mL and 0.129 µg/mL for amlodipine and enalapril maleate, respectively.

The LOD and LOQ results suggested that the method was highly sensitive.

The drugs dissolved in 0.1N HCl were stable when stored at 25°C for 72 hours. After 72 hours, drug recovery values were 99.7% for amlodipine and 99.4% for enalapril maleate.

Assay in tablets

The optimized method was used for the assay of amlodipine and enalapril in FDC tablets. An additional peak from excipients was not observed. The results were in the range of the labeled amount ±5% for both drugs ( Table 7 ).

An external file that holds a picture, illustration, etc.
Object name is TJPS-18-306-g14.jpg

Dissolution

Dissolution was performed with the in-house FDC tablet by using USP apparatus II in 0.1N HCl. 0.1N HCl was selected as the model dissolution medium. The proposed HPLC method was available for dissolution of FDC tablets. Both amlodipine and enalapril were dissolved more than 85% within 10 min. Dissolution profiles of amlodipine and enalapril were given in Figure 7 . The dissolution media of 0.1N HCl replaces the artificial stomach medium that is frequently used with the purpose of formulation development and quality control. For using this analytical method for other dissolution media such as pH 4.5 or pH 6.8 there might be small modifications in chromatographic conditions.

An external file that holds a picture, illustration, etc.
Object name is TJPS-18-306-g7.jpg

Dissolution results of amlodipine and enalapril in an in-house FDC product (n=3)

FDC: Fixed-dose combination

In conclusion, an accurate, precise, specific, and environmentally appropriate HPLC method was developed and validated for amlodipine besylate and enalapril maleate in the typical dosage unit. The BBD, an optimization design, was used to evaluate the operational factors in a robustness test, and validation was performed according to international guidelines. The developed method was more economic and suitable for green chemistry with less solvent consumption, which improved column performance. The method was applied to assay and dissolution studies and was found suitable for quality control tests and in vitro performance of pharmaceutical dosage forms for a fixed-dose tablet combination containing amlodipine besylate and enalapril maleate for the treatment of hypertension.

Acknowledgments

The authors would like to thank Nobel Pharma (Turkey) for providing amlodipine besylate and enalapril maleate as gift samples.

Conflicts of interest: No conflict of interest was declared by the authors. The authors alone are responsible for the content and writing of the paper.

International Journal of Pharmaceutical Sciences

  • Review Paper | Open Access
  • Volume 02 | Issue 01 | Article Id IJPS/240201110

A Comprehensive Overview Of HPLC Method Development And Validation

Photo

Department of Pharmaceutical Quality Assurance, P. Wadhwani College of Pharmacy, Yavatmal, Maharashtra, India

  • View Article

HPLC has become the workhorse of analytical separations due to its versatility, sensitivity, and precision. However, optimizing and validating an HPLC method for specific analytes requires an intricate adjustment of parameters. This review provides a comprehensive overview of the key steps involved in developing and validating a robust HPLC method. Initially, we delve into the critical factors influencing method development, including analyte properties, sample preparation strategies, column selection, mobile phase optimization, and detector choice. We detail the importance of resolution, peak shape, and retention time control in achieving optimal separation. Next, we dissect the validation process, highlighting essential parameters like linearity, limit of detection (LOD), limit of quantification (LOQ), accuracy, precision, specificity, robustness, and system suitability. We discuss established protocols and regulatory guidelines for each parameter, emphasizing the principles behind their evaluation. Furthermore, we explore advanced method development approaches, such as hyphenation with mass spectrometry (MS) for enhanced analyte identification and quantitative analysis. We also briefly touch upon emerging trends in HPLC, including microfluidic chips and green chromatography practices. This review serves as a valuable resource for both novice and experienced analysts, offering a roadmap for navigating the intricacies of HPLC method development and validation, ultimately paving the way for reliable and reproducible analytical results.

  • Sharma BK. Instrumental Methods of Chemical Analysis, 24th Edition, Pg: 68-110.
  • Gurdeep R Chatwal, Sham Anand. Instrumental Methods of Chemical Analysis, pg:185-190.
  • Khan MC, Reddy NK, Ravindra G, Reddy KVSRK, Dubey PK. Development and validation of a stability indicating HPLC method for simultaneous determination of four novel fluoroquinolone dimers as potential antibacterial agents. J Pharmaceut Biomed Anal, 59, 2012, 162–166.
  • Blanchet B, Sabourea C, Benichou AS, Billemont B, Taieb SR, Alain D. Development and validation of an HPLC-UV- visible method for sunitinibquantifcation in human plasma. ClinChimActa, 404, 2009, 134–139.
  • FDA Guidance for Industry. Analytical Procedures and Method Validation, Chemistry, Manufacturing, and Controls Documentation, Center for Drug Evaluation and Research (CDER) and Center for Biologics Evaluation and Research (CBER), 2000.
  • Korany MA, Mahgoub H, Ossama TF, Hadir MM. Application of artificial neural networks for response surface modeling in HPLC method development. J Adv Res, 3, 2012, 53–63.
  • Ferrarini A, Huidobro AL, Pellati F, Barbas C. Development and validation of a HPLC method for the determination of sertraline and three non-chiral related impurities. J Pharmaceut Biomed Anal, 53, 2010, 122–129.
  • Collier JW, Shah RB, Bryant AR, Habib MJ, Khan MA, Faustino PJ. Development and application of a validated HPLC method for the analysis of dissolution samples of levothyroxine sodium drug products. J Pharmaceut Biomed Anal, 54, 2011, 433–438.
  • Singh S, Bakshi M. Guidance on conduct of stress tests to determine inherent stability of drugs. Phrama Tech, 24, 2000, 1- 14.
  • Swartz ME, Jone MD, Fowler P, Andrew MA. Automated HPLC method development and transfer. LcGc N. Am, 75, 2002, 49-50.
  • Synder LR, Kirkland JJ, Glajach JLX. In Practical HPLC Methods Development. John Wiley, New York, 295, 1997, 643- 712.
  • Swartz M, Murphy MB. New Fronties in Chromatography. Am Lab, 37, 2005, 22-27.
  • Debebe Z, Nekhai S, Ashenaf M, David BL, Kalinowski DS, RG Victor, Byrnes WM, Richardson DR, Karla PK. Development of a sensitive HPLC method to measure invitro permeability of E- and Z-isomeric forms of thiosemicarbazones in Caco-2 monolayers. J Chromatogram B, 906, 2012, 25–32.
  • www.agilent.com/chem/store (Accessed on 11/01/2024)
  • Dolan JW. Peak tailing and resolution. LcGc N. Am, 20, 2002, 430-436.
  • Qiang Fu, Shou M, Chien D, Markovich R, Rustum AM. Development and validation of a stability-indicating RP-HPLC method for assay of betamethasone and estimation of its related compounds. J Pharmaceut Biomed Anal, 51, 2010, 617– 625.
  • Nguyen AT, Aerts T, Dam DW, Deyn PPD. Biogenic amines and their metabolites in mouse brain tissue: Development, optimization and validation of an analytical HPLC method. J Chromatogra B, 878, 2010, 3003–3014.
  • International Conference on Harmonization of technical Requirements for Registration of Pharmaceuticals for Human use, ICH
  • Harmonized Tripartite guideline-Validation of Analytical procedures: Text and methodology Q2 (R1), Current step 4 version., London 2005.
  • Singh R. HPLC method development and validation-an overview. Journal of Pharmaceutical Education & Research. 2013 Jun 1;4(1).
  • Sonia K, Lakshmi KS. HPTLC method development and validation: An overview. Journal of Pharmaceutical Sciences and Research. 2017 May 1;9(5):652.
  • Ahuja S, Rasmussen H, editors. HPLC method development for pharmaceuticals. Elsevier; 2011 Sep 21

image

Sayali V. Ganjiwale

image

A. P. Dewani

A. v. chandewar.

Sayali V. Ganjiwale*, A. P. Dewani, A. V. Chandewar, A Comprehensive Overview of HPLC Method Development and Validation, Int. J. of Pharm. Sci., 2024, Vol 2, Issue 1, 802-811. https://doi.org/10.5281/zenodo.10581387

More related articles

Formulation and evaluation of orally dissolving ta..., a comprehensive review clinical trials phase iv..., research advance in clinical evaluation of antihyp..., a review on application and scopes for dosage forms of cissus quadrangularis ext..., formulation and in vitro evaluation of controlled release matrix tablets of anti..., herbal agent used in treatment of diabetes mellitus ....

analytical method development and validation by hplc thesis

  • Received 22 Jan, 2024
  • Accepted 26 Jan, 2024
  • Published 29 Jan, 2024

Related Articles

Artificial inteligence in drug discovery and development..., to study relationship between body mass index and hypercholesterolemia..., review a mucoadhesive drug delivery system..., comprehensive review: bioactive components, traditional uses and pharmacological..., formulation and evaluation of orally dissolving tablets of sodium valproate and ..., research advance in clinical evaluation of antihypertensive drug....

Copyright © 2023 IJPS. All rights reserved

  • Open access
  • Published: 13 July 2021

QbD approach to HPLC method development and validation of ceftriaxone sodium

  • Krunal Y. Patel 1 ,
  • Zarna R. Dedania 1 ,
  • Ronak R. Dedania 1 &
  • Unnati Patel 2  

Future Journal of Pharmaceutical Sciences volume  7 , Article number:  141 ( 2021 ) Cite this article

18k Accesses

31 Citations

Metrics details

Quality by design (QbD) refers to the achievement of certain predictable quality with desired and predetermined specifications. A quality-by-design approach to method development can potentially lead to a more robust/rugged method due to emphasis on risk assessment and management than traditional or conventional approach. An important component of the QbD is the understanding of dependent variables, various factors, and their interaction effects by a desired set of experiments on the responses to be analyzed. The present study describes the risk based HPLC method development and validation of ceftriaxone sodium in pharmaceutical dosage form.

An efficient experimental design based on central composite design of two key components of the RP-HPLC method (mobile phase and pH) is presented. The chromatographic conditions were optimized with the Design Expert software 11.0 version, i.e., Phenomenex ODS column C18 (250 mm × 4.6 mm, 5.0 μ), mobile phase used acetonitrile to water (0.01% triethylamine with pH 6.5) (70:30, v/v), and the flow rate was 1 ml/min with retention time 4.15 min. The developed method was found to be linear with r 2 = 0.991 for range of 10–200 μg/ml at 270 nm detection wavelength. The system suitability test parameters, tailing factor and theoretical plates, were found to be 1.49 and 5236. The % RSD for intraday and inter day precision was found to be 0.70–0.94 and 0.55–0.95 respectively. The robustness values were less than 2%. The assay was found to be 99.73 ± 0.61%. The results of chromatographic peak purity indicate the absence of any coeluting peaks with the ceftriaxone sodium peak. The method validation parameters were in the prescribed limit as per ICH guidelines.

The central composite design experimental design describes the interrelationships of mobile phase and pH at three different level and responses to be observed were retention time, theoretical plates, and peak asymmetry with the help of the Design Expert 11.0 version. Here, a better understanding of the factors that influence chromatographic separation with greater confidence in the ability of the developed HPLC method to meet their intended purposes is done. The QbD approach to analytical method development was used for better understanding of method variables with different levels.

A QbD is defined as “A systemic approach to the method development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management [ 1 ].” The QbD approach emphasizes product and process understanding with quality risk management and controls, resulting in higher assurance of product quality, regulatory flexibility, and continual improvement. The QbD method was based on the understanding and implementation of guidelines ICH Q8 Pharmaceutical Development, ICH Q9 Quality Risk Management, and ICH Q10 Pharmaceutical Quality System [ 2 , 3 , 4 ]. Analytical science is considered to be an integral part of pharmaceutical product development and hence go simultaneously during the entire product life cycle. Analytical QbD defined as a science and risk-based paradigm for analytical method development, endeavoring for understanding the predefined objectives to control the critical method variables affecting the critical method attributes to achieve enhanced method performance, high robustness, ruggedness, and flexibility for continual improvement [ 5 , 6 ]. The result of analytical QbD is well known, fit for purpose, and robust method that reliably delivers the intended output over its lifecycle, similar to the process QbD [ 7 , 8 ]. For QbD, HPLC methods, robustness, and ruggedness should be tested earlier in the development stage of the method to ensure the efficiency of the method over the lifetime of the product [ 9 ]. Otherwise, it can take considerable time and energy to redevelop, revalidate, and retransfer analytical methods if a non-robust or non-rugged system is adapted. The major objective of AQbD has been to identify failure modes and establish robust method operable design region or design space within meaningful system suitability criteria and continuous life cycle management. Literature survey reveals QbD approaches for HPLC method were reported [ 10 , 11 , 12 , 13 ].

The current work intends to develop and optimize the HPLC method for ceftriaxone sodium in pharmaceutical dosage form by quality-by-design approach.

Ceftriaxone sodium was procured as gift sample Salvavidas Pharmaceutical Pvt. Ltd., Surat, Gujarat. All other reagents and chemicals used were of analytical grade, and solvents were used were of HPLC grade. The marketed formulations MONOCEF 250 mg by Aristo were used for assay.

Instruments and reference standards

The HPLC WATERS-2695 with Detector-UV VIS Dual Absorbance Detector WATERS-2487. C-18 column (150 mm × 4.6 mm × 5 μm particle size) was used at ambient temperature.

Chromatographic conditions

The Phenomenex C-18 column (250 mm × 4.6 mm having 5.0 μm particle size equilibrated with a mobile phase consisting of acetonitrile to water (70:30, v/v)) was used. The mobile phase pH 6.5 was adjusted with 0.01% triethylamine. The flow rate was kept at 1 ml/min, and column was set at ambient temperature. Eluents were supervised using a PDA detector at 270.0 nm. A satisfactory separation and peak symmetry for the drug were obtained with the above chromatographic condition. The HPLC method for ceftriaxone sodium was optimized for various parameters: mobile phase and pH as two variables at three different levels using central composite design.

Preparation of reference standard solution

The 1000 μg/ml standard stock solution was prepared by dissolving an accurately 25 mg of ceftriaxone sodium in 25 ml methanol. The stock solution was further diluted to a sub-stock 100 μg/ml. The 10 μg/ml solution was prepared by diluting 1 ml of sub-stock solution to 10 ml with methanol.

Selection of detection wavelength

Ten μg/ml ceftriaxone sodium was scanned in the range of 200–400 nm, and wavelength maxima 270 nm was selected as detection wavelength.

HPLC method development by QbD approach

HPLC method development by Analytical QbD was as follows.

Selection of quality target product profile

The QTPP plays an important role for identifying the variables that affect the QTPP parameters. The retention time, theoretical plates, and peak asymmetry were identified as QTPP for proposed HPLC method [ 14 , 15 ].

Determine critical quality attributes

The CQAs are the method parameters that are directly affect the QTPP. The mobile phase composition and pH of buffer were two critical method parameters required to be controlled to maintain the acceptable response range of QTPP [ 16 ].

Factorial design

After defining the QTPP and CQAs, the central composite experimental design was applied to optimization and selection of two key components: mobile phase and pH of HPLC method. The various interaction effects and quadratic effects of the mobile phase composition and pH of buffer solution on the retention time, theoretical plates, and peak asymmetry was studied using central composite statistical screening design.

A 2-factor, mobile phase composition and pH of buffer solution at 3 different levels, design was used with Design Expert® (Version 11.0, Stat-Ease Inc., and M M), the best suited response for second-order polynomial exploring quadratic response surfaces [ 15 ].

where A and B are independent variables coded for levels, Y is the measured response associated with each combination of factor level, β0 is an intercept, and β1 to β22 are regression coefficients derived from experimental runs of the observed experimental values of Y. Interaction and quadratic terms respectively represent the terms AB, A2, and B2.

Since multivariable interaction of variables and process parameter have been studied, the factors were selected based on preliminary analysis [ 17 ]. As independent variables, mobile phase composition and pH of buffer were chosen and shown in Table 1 . The dependent variables were retention time, peak area, and peak asymmetry as dependent variables for proposed independent variables [ 18 ].

Evaluation of experimental results and selection of final method conditions

Using the CCD approach, these method conditions were assessed. At the first step, the conditions for retention time, theoretical plates, and peak asymmetry were evaluated. For ceftriaxone sodium, this resulted in distinct chromatographic conditions. The proven acceptable ranges from robust regions where the deliberate variations in the method parameters do not affect the quality. This ensures that the method does not fail downstream during validation testing. If the modeling experiments do not have the desired response, the variable needs to be optimized at different levels until the responses were within the acceptable ranges [ 19 ]. The best suited chromatographic conditions shall be optimized using the Design Expert tools.

Risk assessment

The optimized final method is selected against the attributes of the method like that the developed method is efficient and will remain operational throughout the product’s lifetime. A risk-based approach based on the QbD principles set out in ICH Q8 and ICH Q9 guidelines was applied to the evaluation of method to study the robustness and ruggedness [ 20 ]. The parameters of the method or its performance under several circumstances, such as various laboratories, chemicals, analysts, instruments, reagents, and days, were evaluated for robustness and ruggedness studies [ 21 ].

Implement a control strategy

A control strategy should be implemented after the development of method. The analytical target profile was set for the development of the analytical control strategy. The analytical control strategy is the planned set of controls that was derived from the understanding of the various parameters, i.e., fitness for purpose, analytical procedure, and risk management. All these parameters ensure that both performance of the method and quality outputs are within the planned analytical target profile. Analytical control strategy was planned for sample preparation, measurement, and replicate control operations [ 22 ].

Continual improvement for managing analytical life cycle

The best way in the management of analysis lifecycle is doing a continual improvement that can be implemented by monitoring the quality consistency and periodic maintenance of HPLC instrument, computers, and updating of software and other related instrument and apparatus can be done within laboratory [ 23 ].

Analytical method validation

Method validation is a documented evidence which provides a high degree of assurance for a specific method that the process used to confirm the analytical process is suitable for its intended use. The developed HPLC method for estimation ceftriaxone sodium was validated as per ICH Q2 (R1) guidelines [ 24 ].

The linearity of ceftriaxone sodium was evaluated by analyzing 5 independent levels concentration range of 10–200 μg/ml. The calibration curve was constructed by plotting peak area on y axis versus concentration on x-axis. The regression line equation and correlation coefficient values were determined.

Repeatability calculated by the measurement of six samples 100 μg/ml ceftriaxone sodium. The intraday and interday precision were determined by analyzing three different concentrations of ceftriaxone sodium 100, 150, and 200 μg/ml concentrations at three times, on the same day at an interval of 2 h and for three different days. The acceptance limit for % RSD was less than 2.

The accuracy of the method was determined by calculating by recovery study from marketed formulation by at three levels 80%, 100%, and 120% of standard addition. The % recovery of ceftriaxone sodium was calculated. The acceptance limit for % recovery as per ICH guidelines was 98–102% of standard addition.

LOD and LOQ

The lowest drug concentration that can be accurately identified and separated from the background is referred to as a detection limit (LOD) and that can be quantified at the lowest concentration is referred to as LOQ, i.e., the quantification limit. The following equation was used to measure LOD and LOQ according to ICH guidelines.

where σ is the standard deviation of the y-intercept of the regression line, and SD is the slope of the calibration curve.

Robustness and ruggedness studies

The method’s robustness was calculated by subjecting the method to a minor change in the state of the method, such as pump flow rate and pH of mobile phase composition. The ruggedness studies were determined by changing the analyst as extraneous influencing factor. The acceptance limit for calculated %RSD of peak area was less than 2.

System suitability studies

The system suitability was evaluated by six replicate analyses of ceftriaxone sodium. The retention time, column efficiency, peak asymmetry, and theoretical plates were calculated for standard solutions.

Twenty tablets were weighed and powdered. Weigh an accurately about powder equivalent to 100 mg of ceftriaxone sodium, and transfer to 100 ml of volumetric flask. Add 25 ml of methanol, and perform sonication for 15 min until the powder dissolves. Then, make up the volume up to the mark with mobile phase. Filter the resulting solution with 0.42 μ Whatman filter paper. From the filtrate, dilute 0.5 ml to 10 ml to have a concentration of 100 μg/ml. The solution was analyzed by HPLC with same chromatographic condition as linearity. The mean of 3 different assay were used for calculation.

Initially, a mobile phase acetonitrile to water, 50:50 v/v, was tried; the peak was observed at far retention time. No single peak was observed with mobile phase acetonitrile to water, 80:20 v/v. The further mobile phase tried was acetonitrile to water, 40:60 v/v. The improvement of peak shape and symmetry was done by adjusting the buffer pH. The system suitability test parameters were satisfied with optimized chromatographic condition. The optimized mobile phase consisting of acetonitrile to water, 70:30 v/v, and pH 6.5 adjusted with 0.01% triethylamine. The central composite design was used further for the optimization of various parameters within the design space.

HPLC method development by QbD approach [ 25 ]

Quality target product profile

The QTPP selected were retention time, theoretical plates, and peak asymmetry for optimization of HPLC chromatographic condition.

Critical quality attributes

The mobile phase composition acetonitrile to water, 70:30, and pH of buffer solution adjusted with 0.01% triethylamine were identified.

Factorial design [ 21 ]

The CCD central composite design was selected for proposed HPLC method development. The optimization of various parameters is shown in Table 2 .

Design space

The response surface study type, central composite design, and quadric design model with 11 runs were used. The proposed CCD experimental design was applied, and the evaluation of mobile phase composition and pH of buffer was done against the three responses, retention time, theoretical plates, and peak asymmetry, and the result was summarized.

From Fig. 1 and equation retention time (for actual values) = 56.75 + 0.028 × A − 19.01 × B − 0.010 × AB + 0.000343 × A 2 + 1.70458 × B 2 , it was concluded that as β 1 positive coefficient (0.028) suggests that as the amount of acetonitrile in the mobile phase (A) increases and β 2 negative coefficient (− 19.01) suggests that as pH of buffer (B) decreases, the value of retention time was increased.

figure 1

3D surface plot for effect of combination of factors on R1 retention time of ceftriaxone sodium by using central composite design

From Fig. 2 and equation theoretical plates (for actual values) = − 16774.36 − 4220.40 × A + 53225.20 × B + 56.05 × A × B + 26.83 × A 2 − 4380.60 × B 2 , it was concluded that as β 1 negative coefficient (− 4220.40) suggests that as the amount of acetonitrile in the mobile phase (A) decreases and β 2 positive coefficient (53225.20) suggests that as pH of buffer (B) increases, the value of theoretical plates was increased

figure 2

3D surface plot for effect of combination of factors on R2 theoretical plate ceftriaxone sodium by using central composite design

From Fig. 3 and equation peak asymmetry (for actual values) = 31.13 − 0.31 × A − 5.98 × B + 0.0055 × A × B + 0.0021 × A 2 + 0.429 × B 2 , it was concluded that as β 1 negative coefficient (− 0.31) suggests that as the amount of acetonitrile in the mobile phase (A) decreases and β 2 negative coefficient (− 5.98) suggests that as pH of buffer (B) decreases, the value of peak asymmetry was increased.

figure 3

3D surface plot for effect of combination of factors on R3 peak asymmetry of ceftriaxone sodium by using central composite design

Optimized condition obtained

It was obtained by studying all responses in different experimental conditions using the Design expert 11.0 software, and optimized HPLC conditions and predicted responses are shown in Table 3 .

The observed value for responses was calculated by running the HPLC chromatogram for given set of mobile phase and pH of buffer and then compared with the predicted values to evaluate for % prediction error.

Method validation

System suitability.

The system suitability test was applied to a representative chromatogram to check the various parameters such as the retention time which was found to be 4.15 min, theoretical plates were 5263, peak asymmetry was 1.49, and % RSD of six replicate injections was 0.82. The 3D surface plot of desirability for obtaining optimized formulation is shown Fig. 4 .

figure 4

3D surface plot of desirability for obtaining optimized formulation

The constructed calibration curve for ceftriaxone sodium was linear over the concentration range of 10–200 μg/ml shown in Fig. 2 and Table 4 . Typically, the regression equation for the calibration curve was found to be y = 35441x + 60368 with a 0.991 correlation coefficient when graph was plotted with peak area verses concentration (Fig. 5 ).

figure 5

Linearity of 10–200 μg/ml ceftriaxone sodium

The % RSD for repeatability for ceftriaxone sodium based on six times the measurement of the same concentration (100 μg/ml) was found to be less than 0.082. Interday and intraday precisions were shown in Table 5 . The % RSD value less than 2 indicated that the developed method was found to be precise.

The accuracy was done by recovery study. Sample solutions were prepared by spiking at 3 levels, i.e., 80%, 100%, and 120%. The % recovery data obtained by the proposed HPLC method are shown in Table 6 . The % of recovery within 98–102% justify the developed method was accurate as per the ICH Q2 (R1) guidelines.

For robustness and ruggedness studies 100 μg/ml solution of ceftriaxone sodium was used. The robustness was studied by the slight but deliberate change in intrinsic method parameters like pH of mobile phase and flow rate. The ruggedness was studied by change in analyst as extraneous influencing factor. The % RSD for peak area were found to be less than 2 by change in pH of mobile phase, flow rate, and analyst.

The LOD and LOQ for ceftriaxone sodium based on standard deviation of slope and intercept were found to be 0.22 μg/ml and 0.67 μg/ml respectively.

The optimized chromatogram ceftriaxone sodium showed a resolved peak at retention time 4.15 min when performed assay from tablets. The % assay of drug content was found to be 99.73 ± 0.61 (n = 3) for label claim of ceftriaxone sodium. The assay result indicated the method’s ability to measure accurately and specifically in presence of excipients presents in tablet powder.

The analytical quality-by-design HPLC method for the estimation of ceftriaxone sodium in pharmaceutical formulation has been developed. The analytical target product profile were retention time, theoretical plates, and peak asymmetry for the analysis of ceftriaxone sodium by HPLC. The two variables namely the mobile phase composition and pH of buffer solution were identified as the critical quality attributes that affect the analytical target product profile. The central composite design was applied for two factors at three different levels with the use of the Design Expert Software Version 11.0. The risk assessment study identified the critical variables that have impact on analytical target profile [ 26 , 27 , 28 ]. In chromatographic separation, the variability in column selection, instrument configuration, and injection volume was kept controlled while variables such as pH of mobile phase, flow rate, and column temperature were assigned to robustness study.

The quality-by-design approach successfully developed the HPLC method for ceftriaxone sodium. The optimized RP-HPLC method for determination of ceftriaxone sodium used Phenomenex C18 column (250 × 4.6 mm, 5 μm particle size) and mobile phase consist of acetonitrile to water, 70:30 v/v, pH adjusted to 6.5 with 0.01% triethylamine buffer. The retention time for ceftriaxone sodium was found to be 4.15 min. The method was linear in the range of 10–200 μg/ml with 0.991 correlation coefficient. The % RSD for repeatability, intraday, and inter day precision was found to be less that 2% indicating the optimized method was precise. The LOD and LOQ were 0.22 μg/ml and 0.67 μg/ml, respectively. The % recovery of spiked samples was found to be 99.57 ± 1.47 to 100.79 ± 1.73 as per the acceptance criteria of the ICH guidelines. The method was developed as per the ICH guidelines.

A quality-by-design approach to HPLC method development has been described. The method goals are clarified based on the analytical target product profile. The experimental design describes the scouting of the key HPLC method components including mobile phase and pH. The analytical QbD concepts were extended to the HPLC method development for ceftriaxone sodium, and to determine the best performing system and the final design space, a multivariant study of several important process parameters such as the combination of 2 factors namely the mobile phase composition and pH of buffer at 3 different levels was performed. Their interrelationships were studied and optimized at different levels using central composite design. Here, a better understanding of the factors influencing chromatographic separation in the ability of the methods to meet their intended purposes is done. This approach offers a practical knowledge understanding that help for the development of a chromatographic optimization that can be used in the future. All the validated parameters were found within the acceptance criteria. The validated method was found to be linear, precise, accurate, specific, robust, and rugged for determination of ceftriaxone sodium. The QbD approach to method development has helped to better understand the method variables hence leading to less chance of failure during method validation and transfer. The automated QbD method development approach using the Design Expert software has provided a better performing more robust method in less time compared to manual method development. The statistical analysis of data indicates that the method is reproducible, selective, accurate, and robust. This method will be used further for routine analysis for quality control in pharmaceutical industry.

Availability of data and materials

All data and material are available upon request.

Abbreviations

  • Quality by design

Active pharmaceutical ingredient

Central composite design

Critical quality attribute

High-performance liquid chromatography

Reverse phase high-performance liquid chromatography

Limit of quantitation

Limit of detection

Relative standard deviation

Sandipan R (2012) Quality by design: A holistic concept of building quality in pharmaceuticals. Int J Pharm Biomed Res 3:100–108

Google Scholar  

The International Conference on Harmonisation ICH Technical Requirements for Registration of Pharmaceuticals for Human Use on Pharmaceutical Development Q8(R2) (2009) https://database.ich.org/sites/default/files/Q8%28R2%29%20Guideline.pdf

The International Conference on Harmonisation ICH Technical Requirements for Registration of Pharmaceuticals for Human Use on Quality Risk Management Q9 (2005) https://database.ich.org/sites/default/files/Q9%20Guideline.pdf

The International Conference on Harmonisation ICH Technical Requirements for Registration of Pharmaceuticals for Human Use on Pharmaceutical Quality System Q10 (2008) https://database.ich.org/sites/default/files/Q10%20Guideline.pdf

Borman P, Nethercote P, Chatfield M, Thompson D, Truman K (2007) The application of quality by design to analytical methods. Pharm Tech 31:142–152

Schweitzer M, Pohl M, Hanna BM, Nethercote P, Borman P, Hansen G, Smith K, Larew J (2010) Implications and opportunities of applying QbD principles to analytical measurements. Pharm Tech 34:52–59

CAS   Google Scholar  

Galen WE (2004) Analytical Instrumentation Handbook 2nd edn. Marcel Dekker Inc, New York

Snyder LR, Kirkland JJ, Glajch LJ (1997) Practical HPLC method development; 2nd edn. John Wiley & Sons Inc, New York. https://doi.org/10.1002/9781118592014

Book   Google Scholar  

Bhatt D, Rane S (2011) QbD approach to analytical RP-HPLC method development and its validation. Int J Pharm Pharm Sci 3:79–187

Rajkotwala A, Shaikh S, Dedania Z, Dedania R, Vijyendraswamy S (2016) QbD approach to analytical method development and validation of piracetam by HPLC. World J Pharmacy Pharmaceutical Sci 5:1771–1784

Singh P, Maurya J, Dedania Z, Dedania R (2017) QbD Approach for stability indicating HPLC method for determination of artemether and lumefantrine in combined dosage form. Int J Drug Reg Affairs 5:44–59

Article   CAS   Google Scholar  

Prajapati R, Dedania Z, Jain V, Sutariya V, Dedania R, Chisti Z (2019) QbD approach to HPLC method development and validation for estimation of fluoxetine hydrochloride and olanzapine in pharmaceutical dosage form. J Emerging Tech Innovative Res 6:179–195

Dhand V, Dedania Z, Dedania R, Nakarani K (2020) QbD approach to method development and validation of orciprenaline sulphate by HPLC. J Global Trends Pharm Sci 11:8634–8640

Krull I, Swartz M, Turpin J, Lukulay P, Verseput R (2008) A quality-by-design methodology for rapid LC method development, part I. Liq Chroma Gas Chroma N Am 26:1190–1197

Myers R, Montgomery D, Anderson-Cook C (2016) Response surface methodology: process and product optimization using designed experiments. 4th edn. New York: Wiley

Yubing T (2011) Quality by design approaches to analytical methods- FDA perspective. https://www.fda.gov/files/about%20fda/published/Quality-by-Design-Approaches-to-Analytical-Methods%2D%2D%2D%2DFDA-Perspective%2D%2DYubing-Tang%2D%2DPh.D.%2D%2DOctober%2D%2D2011%2D%2DAAPS-Annual-Meeting.pdf . Accessed 15 Dec 2018.

Krull I, Swartz M, Turpin J, Lukulay P, Verseput R (2009) A quality-by-design methodology for rapid LC method development part II. Liq Chroma Gas Chroma N Am 27:48–69

Reid G, Morgado J, Barnett K, Harrington B, Wang J, Harwood J, Fortin D (2013) Analytical QbD in pharmaceutical development. https://www.waters.com/nextgen/in/en/library/application-notes/2019/analytical-quality-by-design-based-method-development-for-the-analysis-of-formoterol-budesonide-and-related-compounds-using-uhplc-ms.html . Accessed 10 June 2018.

Molnar RH, Monks K (2010) Aspects of the “Design Space” in high pressure liquid chromatography method development. J Chromatogra A 1217(19):3193–3200. https://doi.org/10.1016/j.chroma.2010.02.001

Monks K, Molnar I, Rieger H, Bogati B, Szabo E (2012) Quality by design: multidimensional exploration of the design space in high performance liquid chromatography method development for better robustness before validation. J Chromatogra A 1232:218–230. https://doi.org/10.1016/j.chroma.2011.12.041

Ramalingam P, Kalva B, Reddy Y (2015) Analytical quality by design: a tool for regulatory flexibility and robust analytics. Int J Ana Chem. https://doi.org/10.1155/2015/868727

The International Conference on Harmonisation ICH Technical Requirements for Registration of Pharmaceuticals for Human Use on Development and Manufacture of Drug Substances (Chemical Entities and Biotechnological/Biological Entities) Q11 (2012) https://database.ich.org/sites/default/files/Q11%20Guideline.pdf

Orlandini S, Pinzauti S, Furlanetto S (2013) Application of quality by design to the development of analytical separation methods. Ana Bioana Chem 405(2-3):443–450. https://doi.org/10.1007/s00216-012-6302-2

The International Conference on Harmonisation ICH Technical Requirements for Registration of Pharmaceuticals for Human Use on Validation of Analytical Procedures: Text and Methodology Q2(R1) (2005) https://database.ich.org/sites/default/files/Q2%28R1%29%20Guideline.pdf

Reid G, Cheng G, Fortin D (2013) Reversed-phase liquid chromatographic method development in an analytical quality by design framework. J Liq Chrom Related Tech 36(18):2612–2638. https://doi.org/10.1080/10826076.2013.765457

Elder P, Borman P (2013) Improving analytical method reliability across the entire product lifecycle using QbD approaches. Pharmaceu Outsourcing, 14:14–19. http://www.pharmoutsourcing.com/Featured-Articles/142484-Improving-Analytical-Method-Reliability-Across-the-Entire-Product-Lifecycle-Using-QbD-Approaches/ . Accessed 2019.

Smith J, Jones M Jr, Houghton L (1999) Future of health insurance. N Engl J Med 965:325–329

Schweitzer M, Pohl M, Hanna-Brown M (2010) Implications and opportunities of applying QbD principles to analytical measurements. Pharmaceu Tech 34:52–59

Download references

Acknowledgements

All authors are very thankful to the Bhagwan Mahavir College of Pharmacy, Surat, for providing necessary facilities to carry out the research work.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Authors and affiliations.

Department of Quality Assurance, Bhagwan Mahavir College of Pharmacy, Vesu, Surat, Gujarat, India

Krunal Y. Patel, Zarna R. Dedania & Ronak R. Dedania

Department of Chemistry, The University of Alabama in Huntsville, 301 Sparkman Dr, Huntsville, AL-35899, USA

Unnati Patel

You can also search for this author in PubMed   Google Scholar

Contributions

All authors associated with this research work declared that there is no conflict of interest for publication of work. All authors have read and approved the manuscript. The contribution of each author is mentioned below. KP: He is a M Pharm (Quality Assurance) Research Student and the above work has been carried out by him as dissertation work. ZD: She is Research Guide and HOD, Department of Quality Assurance and under her noble guidance the QbD approach for HPLC method has been developed and validated as per ICH guidelines. She is also giving training for ease of operation sophisticated instrument and involved in interpretation of data. RD: He is a co-guide and under his noble guidance student can understand the Design Expert Software and interpretation of statistical data. UP: She is a graduate teaching assistant at University of Alabama at Huntsville, USA and she has contributed for preparing the manuscript.

Corresponding author

Correspondence to Zarna R. Dedania .

Ethics declarations

Ethics approval and consent to participate.

Not applicable

Consent for publication

Competing interests.

No competing interests to declare.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Patel, K.Y., Dedania, Z.R., Dedania, R.R. et al. QbD approach to HPLC method development and validation of ceftriaxone sodium. Futur J Pharm Sci 7 , 141 (2021). https://doi.org/10.1186/s43094-021-00286-4

Download citation

Received : 04 December 2020

Accepted : 18 June 2021

Published : 13 July 2021

DOI : https://doi.org/10.1186/s43094-021-00286-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Ceftriaxone sodium
  • Design approach

analytical method development and validation by hplc thesis

IMAGES

  1. Development and Validation of RP-HPLC Methods / 978-620-3-19888-1

    analytical method development and validation by hplc thesis

  2. RP-HPLC Method Development and Validation for the Analyisis of

    analytical method development and validation by hplc thesis

  3. (PDF) A Review: HPLC Method Development and Validation

    analytical method development and validation by hplc thesis

  4. Development and Validation of Stability Indicating RP-HPLC Method / 978

    analytical method development and validation by hplc thesis

  5. (PDF) Validation of Novel Analytical RP-HPLC Method for determination

    analytical method development and validation by hplc thesis

  6. Novel Spectrophotometric and HPLC Method Development and Validation

    analytical method development and validation by hplc thesis

VIDEO

  1. Analytical Method Development & Validation

  2. HPLC GC Validation IQOQ Service

  3. Development & Validation of Cell-based Assays

  4. hplc integration tips and tricks

  5. M-12. HPLC- Method Development and Validation

  6. End-to-end solution for your lab's analytical validation project

COMMENTS

  1. Development and Validation of an HPLC Method Using an Experimental Design for Analysis of Amlodipine Besylate and Enalapril Maleate in a Fixed-dose Combination

    For instance, in an analytical method development process, the flow rate can be an independent factor that has potential effects on the peak area of the analyte. ... Masih M, Mittal A, Nandy BC. Development and validation of HPLC method for simultaneous estimation of amlodipine besylate and enalapril maleate in solid dosage form. World J Pharm ...

  2. PDF Analytical Method Development and Validation of Assay for Carvedilol

    CERTIFICATE This is to certify that the dissertation work entitled "ANALYTICAL METHOD DEVELOPMENT AND VALIDATION OF ASSAY FOR CARVEDILOL TABLETS BY RP-HPLC, HPTLC AND UV SPECTROSCOPY" is a bonafide research work done in ORCHID HEALTHCARE, CHENNAI by Ms. NISHA.P.J in partial fulfillment of the requirement for the award of Master of Pharmacy in Pharmaceutical Analysis, R V S college

  3. PDF Development & Validation of Analytical Methods for The Estimation of

    It is certified that PhD Thesis titled "Development and Validation of Analytical Methods for Estimation of Anti-Diabetic Drugs" by Ms. Nidhi Chhabilkumar Kotecha has been examined by us. We undertake the following: a. Thesis has significant new work / knowledge as compared already published or are under consideration to be published elsewhere.

  4. PDF Development and Validation of HPLC Methods for Analytical and

    II. Guidelines for analytical method development and validation of biotechnological synthesis of drugs. Production of a chiral steroid as model. Johan Lindholm, Monika Johansson and Torgny Fornstedt. Journal of Chromatography B, 791 (2003), 323-336. III. Investigation of the adsorption behaviour of a chiral model com-pound on Kromasil CHI-TBB.

  5. PDF A Review: Development and validation of HPLC method

    HPLC methods development and validation play important roles in new discovery, development, manufacture of pharmaceutical drugs and various other studies related to humans and animals. It involves the understanding of chemistry of drug substance and facilitates the development of analytical method.

  6. Development and validation of a new HPLC analytical method for the

    The chromatographic runtime is also short. Therefore, the developed analytical method can be reliably employed as an assay method for pharmaceutical study of any dosage form containing DS. 5. Conclusions. A simple, rapid and sensitive analytical method was developed and validated for the analysis for DS. The chromatographic runtime was also short.

  7. PDF Analytical Method Development and Validation: A Review

    know the analytical method validation of HPLC as per USP and ICH guidelines. Keywords Validation, HPLC, USP, ICH, Regulatory, QC Lab Introduction Method validation is defined as the process which proves that an implied analytical method is acceptable for its intended purpose, determined by means of well- documented experimental studies.

  8. A Review: HPLC Method Development and Validation

    Received 04 Novem ber 2015; accep ted 20 November 2015. Abstract. HPLC is the dominant separ ation tech nique in modern pharmaceutical and bio medical anal ysis because it r esults in hi ghly ...

  9. Development and Validation of HPLC Methods for Analytical and

    This review describes a strategy for the systematic development of High performance liquid chromatographic methods, an analytical tool which is able to detect, separate and quantify the drug, its various impurities and drug related degradants that can form on synthesis or storage.

  10. A Comprehensive Overview Of HPLC Method Development And Validation

    HPLC has become the workhorse of analytical separations due to its versatility, sensitivity, and precision. However, optimizing and validating an HPLC method for specific analytes requires an intricate adjustment of parameters. This review provides a comprehensive overview of the key steps involved in developing and validating a robust HPLC method. Initially, we delve into the critical factors ...

  11. HPLC METHOD DEVELOPMENT AND VALIDATION: A REVIEW

    High performance liquid chromatography (HPLC) is an essential analytical tool in assessing drug product. HPLC methods should be able to separate, detect, and quantify the various drugs and drug ...

  12. PDF Updated Review on Analytical Method Development and Validation by Hplc

    pharmacopoeial method so we can develop the analytical method by own to set the specifications. The article focuses on HPLC method development, optimization of developed method and validation of developed analytical method as per ICH guideline Q2 (R1). KEYWORDS: HPLC, method development, related substances, validation, stability study.

  13. QbD approach to HPLC method development and validation of ceftriaxone

    Quality by design (QbD) refers to the achievement of certain predictable quality with desired and predetermined specifications. A quality-by-design approach to method development can potentially lead to a more robust/rugged method due to emphasis on risk assessment and management than traditional or conventional approach. An important component of the QbD is the understanding of dependent ...

  14. Hplc Method Development and Validation: a Review

    The issues pertinent to designing HPLC method development and validation and identification of the influences which may change these characteristics and to what extent are discussed. High performance liquid chromatography (HPLC) is an essential analytical tool in assessing drug product. HPLC methods should be able to separate, detect, and quantify the various drugs and drug related degradants ...

  15. PDF Analytical Method Development and Validation: a Review

    integral part of any sensible analytical practice. Validation of analytical strategies is also needed by most rules and quality standards that impact laboratories [6]. Analytical method development When there are no definitive techniques are present, new methodologies are being progressed for evaluation of the novel product.

  16. A Practical Approach to Rp Hplc Analytical Method Development

    This art icle focuses on the process o f developing a r obust and stability indicative. RP HPLC a ssay method for a pharmaceutical formulation by HPLC. A lab notebook or any. other means to record ...

  17. New HPLC-UV analytical method for quantification of metronidazole

    Method development and validation have tremendous importance in the QC of the drug. In recent years because of its importance, the development of new testing methods for drug determination has received considerable attention in determining potency of active ingredients in eye drops. ... Hence, HPLC is the analytical method of choice for ...

  18. PDF Development and The Validation of Hplc Method

    In the development and manufacturing of new pharmaceutical product the analytical method play an important role. The word validation means simply Validity or action of providing effectiveness. Validation is an analytical method that provides information about various parameters such as accuracy, precision, linearity, Limit if Detection, Limit of

  19. PDF HPLC Method Development and Validation

    The development and approval of a demonstration strategy are key elements of any drug development program [13]. The HPLC investigation method is developed to detect, measure or purify premium compounds. This special topic will focus on the development and approval of exercise as it is associated with medical equipment.

  20. PDF "QbD APPROACH TO ANALYTICAL METHOD DEVELOPMENT AND VALIDATION OF

    Otherwise, if a non‐robust or non‐rugged method is adapted, significant time and resource may be required to redevelop, revalidate and retransfer analytical methods. The present work is aimed to develop QbD approach to analytical method development and validation based of Piracetam by HPLC.

  21. RP-HPLC Analytical Method Development and Validation for ...

    Developing a single analytical method for estimation of individual drug from a multidrug composition is a very challenging task. A simple, rapid, precise, and reliable reverse phase HPLC method was developed for the separation and estimation of three drugs glimepiride, pioglitazone and metformin in bulk drug mix and pharmaceutical dosage forms. The estimation was carried out using Inertsil ODS ...

  22. Analytical Method Development and Validation of Teriflunomide by RP- HPLC

    The validation of the proposed method was verified by system precision and method precision by RP-HPLC. The %RSD of system suitability for Teriflunomide tablets was found to be 0.25. The validation of the proposed method was verified by recovery studies. The percentage recovery range was found to be satisfied which represent in results.