Authors:
Durgadevi Perumal Department of Pharmaceutical Analysis, SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur – 603203, Tamil Nadu, India

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Manikandan Krishnan Department of Pharmaceutical Analysis, SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur – 603203, Tamil Nadu, India

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K.S. Lakshmi Department of Pharmaceutical Analysis, SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur – 603203, Tamil Nadu, India

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Abstract

The two chemical components Escitalopram (ESC) and Etizolam (ETZ) are beneficial for the health of individuals because it helps to treat anxiety. The study mainly illustrated that a green approach is essential in the medical sector with the help of “Green Analytical quality by design”. According to AQbD, the techniques of HPTLC have become eco-friendly, and decided to use “ESC” and “ETZ”. Hence, ethanol and phosphate buffer pH 3.5 adjusted with 1% “orthophosphoric acid”. After the retardation factor, the product ESC was found at 0.34 min and ETZ was found at 0.53 min. The linearity of ETZ the range varies from 300 to 1800 μg mL−1 and for ESC it varies from 100 to 600 μg mL−1. The validation parameter of R2 Values ranged from 0.9997 to 0.9994 for both ESC and ETZ. The study also demonstrated that different other methods were also useful for the medical sector to make it more convenient and eco-friendly. Some of those approaches are “GAPI”, “AGMS”, “NEMI”, and “AGREE”. The outcome of the study helped to find that the technique “HPTLC” is a green analytic design that helps to maintain the stability of the medicine and it was also approved as a quality design and also a novel approach in the pharmaceutical sector.

Abstract

The two chemical components Escitalopram (ESC) and Etizolam (ETZ) are beneficial for the health of individuals because it helps to treat anxiety. The study mainly illustrated that a green approach is essential in the medical sector with the help of “Green Analytical quality by design”. According to AQbD, the techniques of HPTLC have become eco-friendly, and decided to use “ESC” and “ETZ”. Hence, ethanol and phosphate buffer pH 3.5 adjusted with 1% “orthophosphoric acid”. After the retardation factor, the product ESC was found at 0.34 min and ETZ was found at 0.53 min. The linearity of ETZ the range varies from 300 to 1800 μg mL−1 and for ESC it varies from 100 to 600 μg mL−1. The validation parameter of R2 Values ranged from 0.9997 to 0.9994 for both ESC and ETZ. The study also demonstrated that different other methods were also useful for the medical sector to make it more convenient and eco-friendly. Some of those approaches are “GAPI”, “AGMS”, “NEMI”, and “AGREE”. The outcome of the study helped to find that the technique “HPTLC” is a green analytic design that helps to maintain the stability of the medicine and it was also approved as a quality design and also a novel approach in the pharmaceutical sector.

1 Introduction

There are mainly two medicines combined to form “ESC” and “ETZ” and both of them contains “Anti depression” and “anti-anxiety” characteristics. The chemical structure of “Escitalopram” is “C20H21FN2O”. There are different other chemical properties that can be observed in the structure of ETZ. Those components are “(1S)-1-[3-(Dimethyl amino) propyl]-1-(4-fluorophenyl)-1” and “3-dihydro-2-benzofuran-5-carbonitrile”. On the other hand the chemical structure for “Etizolam” is “C17H15ClN4S” and it can be observed that other essential chemical components are “4-(2-chlorophenyl)-2-ethyl-9-methyl-6H-thieno[3,2-f] [1,2,4] triazolo [4,3- a][1,4] diazepine” Fig. 1. In the pharmaceutical sector, ESC can be considered as a drug and the other name of “ESC” is SSR1. This particular medicine is effective for the treatment of brain issues and it can enhance the secretion of a hormone called serotonin. The term SSR1 mainly stands for “Selective serotonin reuptake inhibitor”. In addition, it can be observed that the chemical component Serotonin aids the activities inside the brain and it help to relieve depression [1, 2]. As a result, individuals can easily fall asleep and the particular combined drug has already been supported by the “US Food and Drug Administration” and permitted to apply to patients in Africa and America [3, 4].

Fig. 1.
Fig. 1.

“ESC and ETZ structure”

Citation: Acta Chromatographica 36, 2; 10.1556/1326.2023.01117

The strength of HPTLC is its capacity to examine several samples at once while only using a minimal amount of mobile phase. Thus, analysis takes less time and costs fewer expense. Additionally, it greatly decreases the difficulties associated with disposing of harmful organic effluents, minimising the danger of environmental damage. DOE is a composition parameter optimization tool. In this study, it can be observed that “a three-level factorial design” does not require in this method because CCD can make a “quadratic response” by itself. In the level of doing high-level experiments, it is required to develop chromatographic designs for better optimization. In this context, it can be observed that the “Central Composite Designs” are the most flexible design and it leads to the final optimization for “High-performance Thin Layer Chromatography” (HPTLC).15 experimental runs and 5 center points were used for performing “a three factorial experimental design”. Variables which were included are: Organic solvent content (A), Saturation time (B), travelling distance (C) and 15 optimized trial experimental runs. These three factors were studied for its robustness which showed insignificant effect on the retention.

The fundamental reason for developing “Green Chemistry” is to promote synthetic methods and its products. In this process, the utilisation of hazardous compound becomes decreases and the infrastructure of the pharmaceutical sector can alter in environment-friendly solutions. The study mainly promotes the “Green design” for the “chemical life cycle”, which includes manufacture, usage, and also disposal. The assessment helps to understand that after the “breakdown” of “Green products”, they convert into non-dangerous products. Those harmless components can easily use further after recycling it and for future generations, it can be considered as one of the innovative approaches. On the other hand, the study also compared these harmless substances with chemically hazardous products; hence it can be observed that animals and plants become affected due to the toxic materials entering our environment on a daily basis. As a result, the occurrence of “Ozone layer depletion”, “global climate change” and “Smog formation” can be observed [5, 6]. The concept of “Green Analytic Chemistry” (“CAG”) is an ideology that mainly pays attention to the formation of an “analytical process” that needs to be eco-friendly and also “analyst friendly” [7, 8]. There are lots of advantages that can be seen after using the GAC process, some of those benefits are “the reduction of usage of chemical products and reagents” and also “usage of requirements that require few energy”. As a result, these approaches can make good quality products after releasing minimal waste materials.

A study has been conducted on the “analytical procedures” used to determine “ESC and ETZ” as a single and multi-component. Single ESC UV-spectrophotometry [9], HPLC (High Performance Liquid Chromatography) [10–13], HPTLC [14]and single ETZ UV-spectrophotometry [15], HPLC [16, 17]The combined study of ESC and ETZ of UV-spectrophotometry [18], HPLC [19], UPLC [20]. Based on the review of the literature, clearly stated that the combination of ESC and ETZ by HPTLC does not make a method. This needs a systematic and quantitative approach to improving reaction parameters to obtain critical and accurate results with fewer experiments. One of the most frequent and beneficial chemometric optimization strategies is the experimental design, which is used to filter and optimize the impacts of selected parameters on the response by evaluating the influence of various factors on the response [21]. In this context, “RSM” has been used which is a mathematical and statistical tool for assessing and optimizing the development of various processes in design space [22–24]. RSM (“response surface methodology”) is used after factorial designs have been used to screen the experimental variables that significantly impact the response. The developed method was validated as per ICH Q2B guidelines [25].

2 Materials and methods

2.1 Reagents, materials and instrumentation

For this study purpose, some chemical components such as ESC and ETZ were collected from the laboratory named “Chandra Labs” located in Hyderabad, Andhra Pradesh, India. Another drug “Etizola plus” (“ESC 10 mg and ETZ 0.5”) has been marketed or manufactured by “Macleods Pharmaceutical Pvt. Ltd” products were collected from the local market in Chennai, India. High-grade ethanol (100%) obtained from Hayman Group Ltd. in East Ways Park Witham, UK, that is acceptable for HPTLC and complies with British, European, and American pharmacopoeia monographs. Hydrogen peroxide, sodium hydroxide, hydrochloric acid, and potassium dihydrogen orthophosphate (KH2PO4) were all analytical reagent grade products from SRL Pvt. Ltd. Double distilled water was used throughout the study. The experiment was carried out with the quantitative HPTLC analysis On a Camag Linomat V automated sample applicator with a TLC Scanner III. Data collecting and processing software were included with the HPTLC system. CAMAG is a pharmaceutical manufacturing firm dealing in instrumental Thin-Layer chromatography CAMAG is located in Muttenz, Basel-Landschaft, Switzerland.

2.2 Software and statistical analysis

Using the Microsoft Excel 2013 programme, general statistical measures such as linear regression analysis, standard deviation, mean, and relative standard deviation were generated. Design Expert software version 11 was used to carry out the response surface optimization using analysis of variance (ANOVA), create perturbation plots, create 3D response surface plots, etc. In order to estimate homoscedasticity of variance and deviation from linearity, the Bartlett test was used to data of regions of linearity using the statistical process control trial edition for Excel. The Camag HPTLC system, which included a Camag Linnomate V automated sample applicator, a Hamilton syringe (100 l), a Camag TLC Scanner 3, Camag Win CATS software, and a Camag Twin-trough chamber (20 10 cm), was the equipment utilised in the current investigation. The extraction of the medicines from the tablets was done using an ultrasonicator.

2.3 Densitometric conditions

Different densitometric settings were used to establish an accurate HPTLC technique for ESC and ETZ analysis that is linear, specific, and has adequate stability. Among the several mobile phases tested, the ethanol: water with 1% orthophosphoric acid (5:5 v/v) mobile phase was determined to be suitable for the analysis of ESC and ETZ.

2.4 Method development

2.4.1 The formation of ESC and ETZ standard stock solution

After weighing the drugs ETZ and ESC (10 gm), a “stock solution” has been formed for the experiment process. Then the solution has transferred to the flask and started the dilution process with the help of ethanol. In the next step, 0.1 mL of both solutions has been taken and poured into 10 mL of ethanol solution. It has been maintained that the entire concentration of the solution was 10 μg mL−1 and its depicted in Fig. 2.

Fig. 2.
Fig. 2.

Standard chromatogram of “ESC and ETZ”

Citation: Acta Chromatographica 36, 2; 10.1556/1326.2023.01117

2.4.2 Preparation of an ESC and ETZ sample solution

In this experiment process, there were 20 tablets were taken and also weighed with the help of mortar. After that those tablets (“10 mg ESC and 0.5 mg ETZ”) were crushed into fine powder in that equipment mortar. The next phase contains the activity of dissolving weights of those ethanol tablets “10 mg of ESC” and “0.5 mg of ETZ”. After that those solutions were filtered in an innovative way to conduct the dilution process. For the filtration process “a 0.45-micron syringe filter” was utilised and for the dilution process “10 mL solvent was taken”.

2.5 Forced degradation studies

In this case, the solution of “ETZ and ESC” was included in the degradation process. This kind of stress-related study includes different components such as “alkali (1 M NaOH, room temperature for 12 h)”, “acid (1 M HCl, “room temperature” for 1 h)”, “photolytic degradation (“UV chamber at 27 °C for 48 h”), “oxidative (10% H2O2 at room temperature for 12 h)” and “thermal degradation (70 °C for 48 h)”.

Acid Degradation: In this case, “1 mL of the stock solution” is required to manufacture “10 mL acid solution” and with this “1 mL HCL” was mixed. In that phase, room temperature was maintained at least for one hour.

Alkali Degradation: In this process utilisation of a standard flask has been observed and with this “1 mL stock solution and 1 mL of NaOH” has been mixed and keep them at normal room temperature for at least 1 h. After that, the solution has placed in emulsifier to henearte 10 mL solution.

Oxidative Degradation: In order to conduct oxidative studies, it is required to prepare “10% of H2O2 after adding 10 mL of H2O2” into a 100 mL solution. Within the standard flask, then it is needed to add “1 mL stock solution and 1 mL of 10% H2O2 to produce a 10 mL standard solution, then it keep in a room temperature at least for twelve hours.

Photolytic Degradation: In this method, the new equipment has been used named the “UV chamber” and in that “1 mL of the stock solution” has been mixed and put for forty-eight hours at 27 °C in the “UV chamber”.

Thermal Degradation: In this process “1 mL of the stock solution” has prepared and mixed with “10 mL” of Stock solution and poured into a “standard flask” to heat at 70 °C at least forty-eight degrees C.

3 Results and discussion

Developing an analytical approach while adhering to stability-indicating principles was a new notion for a long-term method. The design of a stability-indicating assay method without applying the AQbD approach, on either side, may result in poor method performance and necessitate revalidation. The combining of AQbD and GAC ideas in the HPTLC process increases the system's stability and long-term viability. As a consequence, we've merged these three techniques to develop a useful and trustworthy approach. This is how the whole process of establishing this validation technique went. This is the novelty of the work and by literature survey that is proved there is no previous HPTLC method of ESC and ETZ by this concept.

3.1 Utilisation of CCD method for optimization of chromatographic condition

CCD provides versatility and may optimize separation utilizing numerous factors for HPTLC. A “triple factorial experimental design” was carried out using 15 experimental and “5 center points”. Variables included are ethanol content, Saturation time, traveling distance, and 15 optimized experimental runs. The responses were conducted and summarized in Table 1.

Table 1.

Model of central composite design

RunsFactorsResponses
A: Content of EthanolB: Saturation timeC: Developing travelledESCETZ
mlmincmRFRF
143590.370.59
26.683080.260.47
342590.360.58
453080.320.48
55306.310.30.5
653080.320.48
762590.270.48
853080.320.48
963570.280.49
103.313080.40.62
1162570.270.48
125309.680.310.52
1343570.360.58
14538.4080.330.55
1563590.280.49
1653080.320.48
1753080.320.48
1853080.320.48
19521.5980.30.52
2042570.350.57

Model selection for the RF Values of ESC and ETZ was determined. A quadratic and linear model was selected. It was based on the PRESS value. The R2 (Adjusted) value was found to be closer to 1. The model validation was performed with ANOVA, and the results are given in Table 2. Significance was found to be P < 0.05. The ratio obtained for the drugs showed an adequate signal.

Table 2.

ANOVA table for optimized model

DrugsModelY (Equation model)R2 (Adjusted)P-value% CVPrecision (Adequate)
ESCQuadratic0.32–0.042A+6.62B+2.69C–2.5AC+3.754A2–1.549B2–5.085C20.9957<0.00010.7583.504
ETZQuadratic0.48–0.046A+6.623B+3.92C–2.5AC+0.023A2+0.019B2+0.010C20.9947<0.00011.1263.810

The % CV < 10% the R2 (Adjusted) was found to be high. This shows an effective relationship between the obtained experimental data and the models. R2 values adjusted have the limit of R2 ≥ 0.80, which are within the acceptable limits showing that the obtained experimental data fits with the polynomial equations. The equations with components and factors are given in Table 2.

The perturbation plots and 3-D plots were done to evaluate the factors and their effects (A, B & C) on retention factor (RF) for the drugs. Figure 3, shows the perturbation plots for the predicted model. This is done to comprehend the 64 procedures under investigation. Figure 3, shows how changes in response concerning perturbations occur from a reference value. The factors are taken to be constant at the point of reference. The steepest curvature of the steepest curve shows the sensitivity to the definite factor. Figure 3, shows that C has a more significant effect on the RF of ESC and ETZ than the other factors. Figure 4, keeping the ethanol content constant, there has been a variation in the RF value of ESC and ETZ with the function of B and C. RF of ESC and ETZ has an inverse correlation with the traveling distance. Analysis was conducted on the model's response plots and perturbation plots, exposing that A and B affect responses more than C and the 3D plots were depicted in Figs 5 and 6.The developed conditions for the separated drug were estimated with the help of Derringer's desirability function. The maximum desirability function obtained for the response surface is presented in Fig. 7. The agreement between the predicted response and the experimental response was predicted and given in Table 3.

Fig. 3.
Fig. 3.

“Perturbation graph depicting the effect of all factors against RF value of ESC”

Citation: Acta Chromatographica 36, 2; 10.1556/1326.2023.01117

Fig. 4.
Fig. 4.

“Perturbation graph showing the effect of all factors against RF value of ETZ”

Citation: Acta Chromatographica 36, 2; 10.1556/1326.2023.01117

Fig. 5.
Fig. 5.

3D “plots of RF of ESC against B and C”

Citation: Acta Chromatographica 36, 2; 10.1556/1326.2023.01117

Fig. 6.
Fig. 6.

“3D plots of RF of ETZ against A and B”

Citation: Acta Chromatographica 36, 2; 10.1556/1326.2023.01117

Fig. 7.
Fig. 7.

“3D plots for Derringer's desirability function”

Citation: Acta Chromatographica 36, 2; 10.1556/1326.2023.01117

Table 3.

The experimental and predicted value

ConditionAcetonitrile contentSaturation timeDistance travelledESCETZ
mlmincmRFRF
14259
Predicted0.360.58
Experimental0.350.56
Predicted Error %12

The % predicted error showcased a desirability value (D = 1) at the optimum conditions, which furnished a set of coordinates. These coordinates obtained were a measure for selecting optimum experimental conditions for analysis of ESC and ETZ. The HPTLC analysis was finalized to contain Ethanol: Water with 0.1% orthophosphoric acid (5:5 v/v). The HPTLC densitogram had an RF value of 0.34 and 0.53 in the case of ESC and ETZ.

3.2 Validation of the methodology

According to the new guidelines from ICH, the process of utilisation of both drugs “ESC and ETZ” has been verified and as a revised technique the “HPTLC” has been introduced. The study has followed the criteria recommended by ICH for the validation procedures. The following process of the study will describe the comments and findings in a detailed way.

3.2.1 Linearity

In order to maintain accuracy and proportion, it is required to maintain the sample concentration within a minimum range. In this experiment process, the concentration of those samples varies from “range 100–600 μg mL−1 for ESC and 300–1800 μg mL−1 for the drug ETZ”. in that case the “correlation coefficients of ESC and ETZ were (r2 = 0.9997 for ESC, r2 = 0.9994 for ETZ)” is shown in Table 4 and 3D Densitogram depicted in Fig. 8.

Table 4.

Validation of analytical parameters

ParametersESCETZ
Linearity range (µg mL−1)100–600300–1800
Correlation coefficient0.99970.9994
Slope3.89275.2022
Intercept1.791623.0443
Limit of Detection (µg mL−1)8.8426.78
Limit of Quantification (µg mL−1)63.41195.26
System precision (% RSD)0.12260.1029
Assay of marketed formulation (Etizola plus)
Label claim10 mg0.5 mg
Amount found9.88 mg0.49 mg
% of Assay99.5599.94
% Recovery (w/w)98.9399.21
Fig. 8.
Fig. 8.

Linearity densitogram of ESC and ETZ

Citation: Acta Chromatographica 36, 2; 10.1556/1326.2023.01117

3.2.2 Precision

The study helped to know that precision is the method that has been performed at least “twice” within a single day. In the peak situation of the experiment the “ESC and ETZ”, it is required to calculate RSD is shown in Table 4.

3.2.3 Accuracy

The percentage for accuracy in the case of “ESC” was 101.48% and for another drug “ETZ” was 101.65%. The ranges for both drugs varied from 100 to 2% and the entire process was done after “spiking” and also with the help of three concentrations from the standard of “50%, 100%, and 150%” is shown in Table 4.

3.2.4 Quantification and detection and its limitation

In order to understand the sensitivity, it can be observed that the “limit of quantification” and “limit of detection” were found. With the help of ICH guidelines the “LOD and LOQ” were measured and a specific formula has also used is shown in Table 4.

LOD = 3.3 × σ/Sσ = “the standard deviation of the response”.

LOQ = 10 × σ/SS = “the slope of the calibration curve”.

3.3 Analysis of marketed dosage form

In that case, it can be observed that the dose gathered from the market has already recovered after including “10 mg ESC and 0.5 mg ETZ”. Then the percentage of recovery in the case of ESC was “99.55%” and ETZ was “99.94%”. With the help of “standard and sample peaks,” the commercial components were calculated. In this assay, the structural formulation of “ETIZOLA PLUS” was obtained within the limitation. In this way, the particular study help to demonstrate the standard of “pharmaceutically prescribed tablets” is shown in Table 4.

3.4 Forced degradation studies

The study depicts that the rate of ESC degradation occurred under the stress factor of photo degradation and within the “acidic environment” the degradation rate can be enhanced. On the other hand, it can be stated that within the alkaline medium the percentage recovery of ETZ becomes stopped. In the alkali medium, most of the degradation occur because of the “drug sensitivity” to alkali. In other stressful conditions such as “heat and oxidation”, the situation of those drugs becomes steady. Table 5 portrays the further summarization of the study.

Table 5

“ESC and ETZ and the study of force degradation”

“Description”“ESC Decomposed Percentage”“ESC Recovered Percentage”“RF“ETZ Decomposed Percentage”“ETZ Recovered Percentage”“RF
Std0.0899.920.320.5399.470.55
Acid (0.1 M HCL)12.3287.680.331.3198.690.54
Alkali (0.1 M NAOH)3.2396.770.313.4286.580.53
Hydrogen peroxide (10%)2.1897.820.331.5698.440.55
Photo Degradation (UV Light)18.4281.580.332.3197.690.51
Thermal Degradation1.6598.350.331.7298.280.52

4 An innovative approach for greenness

4.1 “A developed method for greenness”

In the case of experimenting with two drugs the “tri combination” approach is one of the most suitable approaches. It can be observed that all these three processes are also important to find out the solution. In this competitive market, the pharmaceutical sector needs to utilise these methods in an appropriate way. Hence the implementation of “greenness” was evaluated through four innovative tools. Those are “NEMI”, “AGMS”, “GAPI” and “AGREE”. Each of equipment has its own capability and working process, hence every tool impact differently to the entire technique. Lots of technologies have been implemented for this method, however main intention was to implement an “eco-friendly greenway”.

4.2 NEMI

The tool NEMI is one of the important “qualitative evaluation” process that any leads to the evolution of “green chemistry”. The term NEMI stands for “National Environmental Methods Index” and it was the primary tool that has been used to evaluate the CAG process. The tool NEMI has lots of advantages and the structure of NEMI is made up of “four quadrants circular symbol with different colors such as green and colorless. In order to conduct “bioaccumulation of Toxic chemical components, the quadrant needs to react with “EPA's TRI”. The color of the quadrant is tinted green until it has been used in “PBT”. In this case, the discharged unusual components were controlled with the help of “The Environment Protection Agency” (EPA) within the guidance of RCRA [26, 27]. Many other components were recognised in the list of RCRA, therefore the second quadrant is already marked as green. The “third quadrant” was also kept in green zone after maintaining the pH 3.5 of the analytical solution. The fourth quadrant of the equipment mainly focuses on waste materials. Because we employed ethanol and phosphate buffer as our research's mobile phase consumption in the analytical technique, NEMI's third quadrant turns green. The fourth quadrant is made up of waste materials. Since HPTLC uses a less quantity of mobile phase than HPLC does, there is relatively little waste to be observed and it shown in Fig. 9.

Fig. 9.
Fig. 9.

(A) “NEMI”, (B) “GAPI”, (C) “AMGS”, and (D) “AGREE with metric results” of the suggested “green assessment method”

Citation: Acta Chromatographica 36, 2; 10.1556/1326.2023.01117

4.3 GAPI

It is another important tool with the facility of 11 different color classification. The particular tool is the upgraded version of “NEMI” and the term “GAPI” stands for “Green Analytics Procedure Index”. The tool can portray “hazard tolerance” and “environmental friendliness” by using and indicating different colors such as green, yellow, and red. After developing a proper software, the tool “GAPI” can be used. The tool is modified in such a way, it can cover a total of 11 stages to get the proper result. It will clearly mention in the Fig. 9. [28, 29] The GAPI consists of 10 phases, the first of which includes solvents and reagents and the second of which includes instrument energy. We employed less energy-intensive equipment throughout those phases and our analytical process was dependable when switching from methanol to ethanol as a solvent to create a greener technique.

4.4 AMGS

The study also helps to know the alternative process of maintaining “health”, “safety” and also “environment” by using “HPLC environmental assessment”. In this context “SHE” (“Safety, Health, and Environment”) was also included in the procedures of AMGS. There were near about three stages that can be observed in AMGS, which include “equipment”, “solvent energy” and “solvent environment health and safety”. In the case of obtaining the final outcome of using this particular method, Fig. 9 helps to evaluate the positive impact of the AIMS model. In this context, the essential information has been gathered from “AES Green computing University for the green revolution”.[30, 31].

4.5 AGREE with metrics

The tool “Agree with Metrics” can be considered as the most upgraded tool that help in the assessment and it includes a total of 12 “green analytical concepts”. In this context, the entire result is denoted as 1 and also emphasised the role of single principals. The rating has been given to the greenness and it needs to be closer to 1. The overall inputting method will clearly be observed in Fig. 9 and it helps in the specification of the program. The fundamental objective of the study is to detect sustainability, and also evaluating “greenness” with the help of other five tools. Despite this, it can be recognised that these tech techniques are flexible for greenness and lead to the future development of “green assessment” in pharmaceuticals.[32–35]. There is a sample process for the 12 stages of AGREE, number. Samples, Analytical device positioning, reagent usage reduction, miniaturised processes, derivatization agents, waste management, and number. Analytes, energy used, reagent type, hazardous solvents, and operator safety. A minimum number of samples were required for each step of the analytical process, HPTLC required less energy, toxic reagents were replaced with ethanol and phosphate buffer, less solvent waste resulted, and the main reason for the method's greenness was that all samples were analysed using in-line analysis, which automatically analyses production samples to ensure quality.

5 Conclusion

The study helps to identify the usage of “ETZ and ESC” drugs in the pharmaceutical industry in the form of different dosages. In order to stabilise the indicators the development of “CAG” was required based on the HPLC method. For utilisation in the future, the technique AQbD was introduced for rapid usage without any rev validation. The study helps to understand the “flowrate of 1 mL min−1”, it is required to do an alternation of ethanol with the help of multiple mathematical models. In this context, different types of parameters have been used to evaluate the impact of techniques used in this study. The process of “forced degradation” resulted in the “degradation peaks” and also showed that isolation can occur due to this and leads to the formation of those two drugs (ETZ and ESC). An analytical technique has been developed to maintain “accuracy”, “specificity”, “repeatability” and “linearity” during the working process. Last, the evolution of the most suitable “environment friendly” approaches has been done with the help of multiple green assessment methods NEMI, AMGS, GAPI and AGREE. From this study, it can be concluded that “the commercial and industrial lab research and testing departments” have already agreed to use different dosages of tablets. Therefore, the “scientific community” has decided to adopt AQbD-based techniques to promote “greenness” in the pharmaceutical industries.

Acknowledgments

The authors are grateful to the Chancellor, SRM Institute of Science and Technology, and the management of SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur, for permitting to carry out this work in the university facility.

Abbreviations

AGREE metrics

Analytical Greenness metrics

AMGS

Analytical Method Greenness Score

AQBD

Analytical Quality by Design

BP

British Pharmacopoeia

CCD

Central Composite Design

CED

Cumulative Energy Demand

EHS

Environmental Risk Protection

ESC

Escitalopram

ETZ

Etizolam

GAC

Green Analytical Chemistry

GAPI

Green Analytical Procedure Index

HPTLC

High Performance Thin Layer Chromatography

IP

Indian Pharmacopoeia

IUPAC

International Union of Pure and Applied Chemistry

LOD

Limit of Detection

LOQ

Limit of Quantification

NED

Net accumulated energy demand

PBT

Persistent, Bio accumulative and Toxic

RSD

Relative Standard Deviation

RSM

Response Surface Methodology

SD

Standard Deviation

UPLC

Ultra performance liquid chromatography

UV

Ultra violet spectroscopy

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    • Export Citation
  • 2.

    Kirino, E. Escitalopram for the management of major depressive disorder: a review of its efficacy, safety, and patient acceptability. Patient Preference and Adherence 2012, 6, 853861. https://doi.org/10.2147/PPA.S22495.

    • Search Google Scholar
    • Export Citation
  • 3.

    Indian Pharmacopoeia Commission, Government of India, Ministry of Health and Family Welfare. National Formulary of India, 2011.

  • 4.

    Shiozaki, Y. Jp Xvii, the Japanese Pharmacopoeia, 2016. http://www.pmda.go.jp/english/pharmacopoeia/pdf/jpdata/JP16eng.pdf.

  • 5.

    Becker, J.; Manske, C.; Randl, S. Green chemistry and sustainability metrics in the pharmaceutical manufacturing sector. Curr. Opin. Green Sustain. Chem. 2022, 33, 2021. https://doi.org/10.1016/j.cogsc.2021.100562.

    • Search Google Scholar
    • Export Citation
  • 6.

    Constable, D. J. C. Green and sustainable chemistry – the case for a systems-based, interdisciplinary approach. IScience 2021, 24, 103489. https://doi.org/10.1016/j.isci.2021.103489.

    • Search Google Scholar
    • Export Citation
  • 7.

    Badami, B. V. Concept of green chemistry. Resonance 2008, 13, 10411048. https://doi.org/10.1007/s12045-008-0124-8.

  • 8.

    Armenta, S.; Esteve-Turrillas, F. A.; Garrigues, S.; de la Guardia, M. Green Analytical Chemistry; Comprehensive Foodomics, 2020; 483493. https://doi.org/10.1016/B978-0-08-100596-5.22800-X.

    • Search Google Scholar
    • Export Citation
  • 9.

    Korea, S. By ion association complex with methyl. Orange 2013, 25, 34103414.

  • 10.

    Samanta, T.; Dey, S.; Samal, H. B.; Kumar, D. B.; Mohanty, L.; Bhar, K. J. Chem. Res. RP - HPLC Method Estimation Escitalopram Bulk Dosage Forms 2011, 2.

    • Search Google Scholar
    • Export Citation
  • 11.

    Charde, M. S.; Bhavsar, N.; Chakole, R. D. Determination of escitalopram oxalate in pharmaceutical formulation by high performance liquid chromatography. Int. J. Pharm. Chem. 2012, 2. https://doi.org/10.7439/ijpc.v2i1.422.

    • Search Google Scholar
    • Export Citation
  • 12.

    Rajendra, V. B.; Deshmukh, O. J.; Rawat, P. K.; Gulecha, B. S.; Khushwaha, S.; Ghadlinge, S. V. World J. Pharm. Res. Spectrophotometric Method Estimation Clopidogrel Bisulphate Residue Swab Samples n.d., 1, 850858.

    • Search Google Scholar
    • Export Citation
  • 13.

    Ali, H.; Shah, S. N.; Zafar, F.; Israr, F.; Hanif, M.; Zaib-Un-Nisa; Naqvi, G. R.; Hanif, A. M.; Khan, S.; Maroof, K. Development and validation of HPLC method for escitalopram oxalate: application to raw material, pharmaceuticals and freeze thaw stability profile. Latin Am. J. Pharm. 2018, 37, 553560.

    • Search Google Scholar
    • Export Citation
  • 14.

    Mahadik, M. V.; Dhaneshwar, S. R.; Kulkarni, M. J. Application of stability indicating HPTLC method for quantitative determination of escitalopram oxalate in pharmaceutical dosage form. J. Anal. Chem. 2007, 2.

    • Search Google Scholar
    • Export Citation
  • 15.

    Mondal, P.; Reddy, A. R. N.; Swarnamanju, G.; Raparla, R. Novel extractive colorimetric and UV spectrophotometric estimation of etizolam in bulk and tablet by forming ion association complex with methyl orange and bromocresol green. Toxicol. Environ. Chem. 2015, 97, 515525. https://doi.org/10.1080/02772248.2015.1054608.

    • Search Google Scholar
    • Export Citation
  • 16.

    Avula, P.; Galla, R.; Adepu, G. S.; Vemanaboina, H. B.; Tyagarajan, S. Development and validation of stability indicating RP-HPLC method for estimation of roflumilast in tablet dosage form. Res. J. Pharm. Technol. 2021, 14, 863868. https://doi.org/10.5958/0974-360X.2021.00153.0.

    • Search Google Scholar
    • Export Citation
  • 17.

    Gummadi, S.; Seru, G.; Chittajallu, S. G. Development and validation of a stability indicating RP-HPLC method for estimation of etizolam in tablet dosage form. Res. J. Pharm. Technol. 2019, 12, 16371642. https://doi.org/10.5958/0974-360X.2019.00273.7.

    • Search Google Scholar
    • Export Citation
  • 18.

    Sivadas, A.; Sathi, A.; Sathi, K.; Rahate, K. P. Development and validation of spectrophotometric methods for simultaneous estimation of citicoline and piracetam in tablet dosage form. J. Pharm. Bioallied Sci. 2013, 5, 202207. https://doi.org/10.4103/0975-7406.116818.

    • Search Google Scholar
    • Export Citation
  • 19.

    Kalia, B.; Baghel, U. S. Method development and validation of stability indicating RP-HPLC method for simultaneous estimation of escitalopram oxalate and clonazepam in bulk and its pharmaceutical formulations. J. Drug Deliv. Ther. 2019, 9, 265274. https://doi.org/10.22270/jddt.v9i1-s.2347.

    • Search Google Scholar
    • Export Citation
  • 20.

    RP-HPLC, B.; Rao, Vu. Analytical method development and validation for simultaneous estimation of escitalopram oxalate and etizolam in a combined dosage form, n.d.. www.ijipsr.com.

    • Search Google Scholar
    • Export Citation
  • 21.

    Books, H. F.; References, D.; Windows, M. Des. – Expert 1996, 1012.

  • 22.

    Ferreira, S. L. C.; Bruns, R. E.; Ferreira, H. S.; Matos, G. D.; DavidJ. M.; Brandão, G. C.; da Silva, E. G. P.; Portugal, L. A.; dos Reis, P. S.; Souza, A. S.; dos Santos, W. N. L. Box-Behnken design: an alternative for the optimization of analytical methods. Analytica Chim. Acta 2007, 597, 179186. https://doi.org/10.1016/j.aca.2007.07.011.

    • Search Google Scholar
    • Export Citation
  • 23.

    Bezerra, M. A.; Santelli, R. E.; Oliveira, E. P.; Villar, L. S.; Escaleira, L. A. Response surface methodology (RSM) as a tool for optimization in analytical chemistry. Talanta 2008, 76, 965977. https://doi.org/10.1016/j.talanta.2008.05.019.

    • Search Google Scholar
    • Export Citation
  • 24.

    Gundala, A.; Kvsrg, P.; Koganti, B. Application of quality by design approach in RP-HPLC method development for simultaneous estimation of saxagliptin and dapagliflozin in tablet dosage form. Braz. J. Pharm. Sci. 2019, 55, 110. https://doi.org/10.1590/s2175-97902019000218129.

    • Search Google Scholar
    • Export Citation
  • 25.

    Harron, D. W. G. Technical requirements for registration of pharmaceuticals for human use: the ICH process. Textbook Pharm. Med. 2013, 1994, 447460. https://doi.org/10.1002/9781118532331.ch23.

    • Search Google Scholar
    • Export Citation
  • 26.

    Serebruany, V.; Malinin, A.; Dragan, V.; Atar, D.; Van Zyl, L.; Dragan, A. Fluorimetric quantitation of citalopram and escitalopram in plasma: developing an express method to monitor compliance in clinical trials. Clin. Chem. Lab. Med. 2007, 45, 513520. https://doi.org/10.1515/CCLM.2007.108.

    • Search Google Scholar
    • Export Citation
  • 27.

    Thompson, C. M.; Haws, L. C.; Harris, M. A.; Gatto, N. M.; Proctor, D. M. Application of the U.S. EPA mode of action framework for purposes of guiding future research: a case study involving the oral carcinogenicity of hexavalent chromium. Toxicol. Sci. 2011, 119, 2040. https://doi.org/10.1093/toxsci/kfq320.

    • Search Google Scholar
    • Export Citation
  • 28.

    Epa, M. Your hazardous waste. Mar. Pollut. Bull. 2001, 11, 31.

  • 29.

    Systems, B.; Occupancies, S.; Materials, H. Fire Code 2021, 1, 20212022.

  • 30.

    Płotka-Wasylka, J. A new tool for the evaluation of the analytical procedure: green Analytical Procedure Index. Talanta 2018, 181, 204209. https://doi.org/10.1016/j.talanta.2018.01.013.

    • Search Google Scholar
    • Export Citation
  • 31.

    Mohamed, H. M.; Lamie, N. T. Analytical eco-scale for assessing the greenness of a developed RP-HPLC method used for simultaneous analysis of combined antihypertensive medications. J. AOAC Int. 2016, 99, 12601265. https://doi.org/10.5740/jaoacint.16-0124.

    • Search Google Scholar
    • Export Citation
  • 32.

    Diorazio, L. J.; Richardson, P.; Sneddon, H. F.; Moores, A.; Briddell, C.; Martinez, I. Making sustainability assessment accessible: tools developed by the ACS green chemistry institute pharmaceutical roundtable. ACS Sustain. Chem. Eng. 2021, 9, 1686216864. https://doi.org/10.1021/acssuschemeng.1c07651.

    • Search Google Scholar
    • Export Citation
  • 33.

    Pena-Pereira, F.; Wojnowski, W.; Tobiszewski, M. Agree - analytical GREEnness metric approach and software. Anal. Chem. 2020, 92, 1007610082. https://doi.org/10.1021/acs.analchem.0c01887.

    • Search Google Scholar
    • Export Citation
  • 34.

    Kokilambigai, K. S.; Lakshmi, K. S. Utilization of green analytical chemistry principles for the simultaneous estimation of paracetamol, aceclofenac and thiocolchicoside by UV spectrophotometry. Green. Chem. Lett. Rev. 2021, 14, 97105. https://doi.org/10.1080/17518253.2020.1862311.

    • Search Google Scholar
    • Export Citation
  • 35.

    Perumal, D. D.; Krishnan, M.; Lakshmi, K. S. Green Chemistry Letters and Reviews Eco-friendly based stability-indicating RP-HPLC technique for the determination of escitalopram and etizolam by employing QbD approach, 2022. https://doi.org/10.1080/17518253.2022.2127334.

    • Search Google Scholar
    • Export Citation
  • 1.

    Sellappan, M.; Devakumar, D. Development and validation of RP-HPLC method for the estimation of escitalopram oxalate and flupentixol dihydrochloride in combined dosage form and plasma. Int. J. Pharm. Pharm. Sci. 2021, 13, 6166. https://doi.org/10.22159/ijpps.2021v13i2.30158.

    • Search Google Scholar
    • Export Citation
  • 2.

    Kirino, E. Escitalopram for the management of major depressive disorder: a review of its efficacy, safety, and patient acceptability. Patient Preference and Adherence 2012, 6, 853861. https://doi.org/10.2147/PPA.S22495.

    • Search Google Scholar
    • Export Citation
  • 3.

    Indian Pharmacopoeia Commission, Government of India, Ministry of Health and Family Welfare. National Formulary of India, 2011.

  • 4.

    Shiozaki, Y. Jp Xvii, the Japanese Pharmacopoeia, 2016. http://www.pmda.go.jp/english/pharmacopoeia/pdf/jpdata/JP16eng.pdf.

  • 5.

    Becker, J.; Manske, C.; Randl, S. Green chemistry and sustainability metrics in the pharmaceutical manufacturing sector. Curr. Opin. Green Sustain. Chem. 2022, 33, 2021. https://doi.org/10.1016/j.cogsc.2021.100562.

    • Search Google Scholar
    • Export Citation
  • 6.

    Constable, D. J. C. Green and sustainable chemistry – the case for a systems-based, interdisciplinary approach. IScience 2021, 24, 103489. https://doi.org/10.1016/j.isci.2021.103489.

    • Search Google Scholar
    • Export Citation
  • 7.

    Badami, B. V. Concept of green chemistry. Resonance 2008, 13, 10411048. https://doi.org/10.1007/s12045-008-0124-8.

  • 8.

    Armenta, S.; Esteve-Turrillas, F. A.; Garrigues, S.; de la Guardia, M. Green Analytical Chemistry; Comprehensive Foodomics, 2020; 483493. https://doi.org/10.1016/B978-0-08-100596-5.22800-X.

    • Search Google Scholar
    • Export Citation
  • 9.

    Korea, S. By ion association complex with methyl. Orange 2013, 25, 34103414.

  • 10.

    Samanta, T.; Dey, S.; Samal, H. B.; Kumar, D. B.; Mohanty, L.; Bhar, K. J. Chem. Res. RP - HPLC Method Estimation Escitalopram Bulk Dosage Forms 2011, 2.

    • Search Google Scholar
    • Export Citation
  • 11.

    Charde, M. S.; Bhavsar, N.; Chakole, R. D. Determination of escitalopram oxalate in pharmaceutical formulation by high performance liquid chromatography. Int. J. Pharm. Chem. 2012, 2. https://doi.org/10.7439/ijpc.v2i1.422.

    • Search Google Scholar
    • Export Citation
  • 12.

    Rajendra, V. B.; Deshmukh, O. J.; Rawat, P. K.; Gulecha, B. S.; Khushwaha, S.; Ghadlinge, S. V. World J. Pharm. Res. Spectrophotometric Method Estimation Clopidogrel Bisulphate Residue Swab Samples n.d., 1, 850858.

    • Search Google Scholar
    • Export Citation
  • 13.

    Ali, H.; Shah, S. N.; Zafar, F.; Israr, F.; Hanif, M.; Zaib-Un-Nisa; Naqvi, G. R.; Hanif, A. M.; Khan, S.; Maroof, K. Development and validation of HPLC method for escitalopram oxalate: application to raw material, pharmaceuticals and freeze thaw stability profile. Latin Am. J. Pharm. 2018, 37, 553560.

    • Search Google Scholar
    • Export Citation
  • 14.

    Mahadik, M. V.; Dhaneshwar, S. R.; Kulkarni, M. J. Application of stability indicating HPTLC method for quantitative determination of escitalopram oxalate in pharmaceutical dosage form. J. Anal. Chem. 2007, 2.

    • Search Google Scholar
    • Export Citation
  • 15.

    Mondal, P.; Reddy, A. R. N.; Swarnamanju, G.; Raparla, R. Novel extractive colorimetric and UV spectrophotometric estimation of etizolam in bulk and tablet by forming ion association complex with methyl orange and bromocresol green. Toxicol. Environ. Chem. 2015, 97, 515525. https://doi.org/10.1080/02772248.2015.1054608.

    • Search Google Scholar
    • Export Citation
  • 16.

    Avula, P.; Galla, R.; Adepu, G. S.; Vemanaboina, H. B.; Tyagarajan, S. Development and validation of stability indicating RP-HPLC method for estimation of roflumilast in tablet dosage form. Res. J. Pharm. Technol. 2021, 14, 863868. https://doi.org/10.5958/0974-360X.2021.00153.0.

    • Search Google Scholar
    • Export Citation
  • 17.

    Gummadi, S.; Seru, G.; Chittajallu, S. G. Development and validation of a stability indicating RP-HPLC method for estimation of etizolam in tablet dosage form. Res. J. Pharm. Technol. 2019, 12, 16371642. https://doi.org/10.5958/0974-360X.2019.00273.7.

    • Search Google Scholar
    • Export Citation
  • 18.

    Sivadas, A.; Sathi, A.; Sathi, K.; Rahate, K. P. Development and validation of spectrophotometric methods for simultaneous estimation of citicoline and piracetam in tablet dosage form. J. Pharm. Bioallied Sci. 2013, 5, 202207. https://doi.org/10.4103/0975-7406.116818.

    • Search Google Scholar
    • Export Citation
  • 19.

    Kalia, B.; Baghel, U. S. Method development and validation of stability indicating RP-HPLC method for simultaneous estimation of escitalopram oxalate and clonazepam in bulk and its pharmaceutical formulations. J. Drug Deliv. Ther. 2019, 9, 265274. https://doi.org/10.22270/jddt.v9i1-s.2347.

    • Search Google Scholar
    • Export Citation
  • 20.

    RP-HPLC, B.; Rao, Vu. Analytical method development and validation for simultaneous estimation of escitalopram oxalate and etizolam in a combined dosage form, n.d.. www.ijipsr.com.

    • Search Google Scholar
    • Export Citation
  • 21.

    Books, H. F.; References, D.; Windows, M. Des. – Expert 1996, 1012.

  • 22.

    Ferreira, S. L. C.; Bruns, R. E.; Ferreira, H. S.; Matos, G. D.; DavidJ. M.; Brandão, G. C.; da Silva, E. G. P.; Portugal, L. A.; dos Reis, P. S.; Souza, A. S.; dos Santos, W. N. L. Box-Behnken design: an alternative for the optimization of analytical methods. Analytica Chim. Acta 2007, 597, 179186. https://doi.org/10.1016/j.aca.2007.07.011.

    • Search Google Scholar
    • Export Citation
  • 23.

    Bezerra, M. A.; Santelli, R. E.; Oliveira, E. P.; Villar, L. S.; Escaleira, L. A. Response surface methodology (RSM) as a tool for optimization in analytical chemistry. Talanta 2008, 76, 965977. https://doi.org/10.1016/j.talanta.2008.05.019.

    • Search Google Scholar
    • Export Citation
  • 24.

    Gundala, A.; Kvsrg, P.; Koganti, B. Application of quality by design approach in RP-HPLC method development for simultaneous estimation of saxagliptin and dapagliflozin in tablet dosage form. Braz. J. Pharm. Sci. 2019, 55, 110. https://doi.org/10.1590/s2175-97902019000218129.

    • Search Google Scholar
    • Export Citation
  • 25.

    Harron, D. W. G. Technical requirements for registration of pharmaceuticals for human use: the ICH process. Textbook Pharm. Med. 2013, 1994, 447460. https://doi.org/10.1002/9781118532331.ch23.

    • Search Google Scholar
    • Export Citation
  • 26.

    Serebruany, V.; Malinin, A.; Dragan, V.; Atar, D.; Van Zyl, L.; Dragan, A. Fluorimetric quantitation of citalopram and escitalopram in plasma: developing an express method to monitor compliance in clinical trials. Clin. Chem. Lab. Med. 2007, 45, 513520. https://doi.org/10.1515/CCLM.2007.108.

    • Search Google Scholar
    • Export Citation
  • 27.

    Thompson, C. M.; Haws, L. C.; Harris, M. A.; Gatto, N. M.; Proctor, D. M. Application of the U.S. EPA mode of action framework for purposes of guiding future research: a case study involving the oral carcinogenicity of hexavalent chromium. Toxicol. Sci. 2011, 119, 2040. https://doi.org/10.1093/toxsci/kfq320.

    • Search Google Scholar
    • Export Citation
  • 28.

    Epa, M. Your hazardous waste. Mar. Pollut. Bull. 2001, 11, 31.

  • 29.

    Systems, B.; Occupancies, S.; Materials, H. Fire Code 2021, 1, 20212022.

  • 30.

    Płotka-Wasylka, J. A new tool for the evaluation of the analytical procedure: green Analytical Procedure Index. Talanta 2018, 181, 204209. https://doi.org/10.1016/j.talanta.2018.01.013.

    • Search Google Scholar
    • Export Citation
  • 31.

    Mohamed, H. M.; Lamie, N. T. Analytical eco-scale for assessing the greenness of a developed RP-HPLC method used for simultaneous analysis of combined antihypertensive medications. J. AOAC Int. 2016, 99, 12601265. https://doi.org/10.5740/jaoacint.16-0124.

    • Search Google Scholar
    • Export Citation
  • 32.

    Diorazio, L. J.; Richardson, P.; Sneddon, H. F.; Moores, A.; Briddell, C.; Martinez, I. Making sustainability assessment accessible: tools developed by the ACS green chemistry institute pharmaceutical roundtable. ACS Sustain. Chem. Eng. 2021, 9, 1686216864. https://doi.org/10.1021/acssuschemeng.1c07651.

    • Search Google Scholar
    • Export Citation
  • 33.

    Pena-Pereira, F.; Wojnowski, W.; Tobiszewski, M. Agree - analytical GREEnness metric approach and software. Anal. Chem. 2020, 92, 1007610082. https://doi.org/10.1021/acs.analchem.0c01887.

    • Search Google Scholar
    • Export Citation
  • 34.

    Kokilambigai, K. S.; Lakshmi, K. S. Utilization of green analytical chemistry principles for the simultaneous estimation of paracetamol, aceclofenac and thiocolchicoside by UV spectrophotometry. Green. Chem. Lett. Rev. 2021, 14, 97105. https://doi.org/10.1080/17518253.2020.1862311.

    • Search Google Scholar
    • Export Citation
  • 35.

    Perumal, D. D.; Krishnan, M.; Lakshmi, K. S. Green Chemistry Letters and Reviews Eco-friendly based stability-indicating RP-HPLC technique for the determination of escitalopram and etizolam by employing QbD approach, 2022. https://doi.org/10.1080/17518253.2022.2127334.

    • Search Google Scholar
    • Export Citation
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Senior editors

Editor(s)-in-Chief: Kowalska, Teresa (1946-2023)

Editor(s)-in-Chief: Sajewicz, Mieczyslaw

Editors(s)

  • Danica Agbaba (University of Belgrade, Belgrade, Serbia)
  • Łukasz Komsta (Medical University of Lublin, Lublin, Poland)
  • Ivana Stanimirova-Daszykowska (University of Silesia, Katowice, Poland)
  • Monika Waksmundzka-Hajnos (Medical University of Lublin, Lublin, Poland)

Editorial Board

  • R. Bhushan (The Indian Institute of Technology, Roorkee, India)
  • J. Bojarski (Jagiellonian University, Kraków, Poland)
  • B. Chankvetadze (State University of Tbilisi, Tbilisi, Georgia)
  • M. Daszykowski (University of Silesia, Katowice, Poland)
  • T.H. Dzido (Medical University of Lublin, Lublin, Poland)
  • A. Felinger (University of Pécs, Pécs, Hungary)
  • K. Glowniak (Medical University of Lublin, Lublin, Poland)
  • B. Glód (Siedlce University of Natural Sciences and Humanities, Siedlce, Poland)
  • A. Gumieniczek (Medical University of Lublin, Lublin, Poland)
  • U. Hubicka (Jagiellonian University, Kraków, Poland)
  • K. Kaczmarski (Rzeszow University of Technology, Rzeszów, Poland)
  • H. Kalász (Semmelweis University, Budapest, Hungary)
  • K. Karljiković Rajić (University of Belgrade, Belgrade, Serbia)
  • I. Klebovich (Semmelweis University, Budapest, Hungary)
  • A. Koch (Private Pharmacy, Hamburg, Germany)
  • P. Kus (Univerity of Silesia, Katowice, Poland)
  • D. Mangelings (Free University of Brussels, Brussels, Belgium)
  • E. Mincsovics (Corvinus University of Budapest, Budapest, Hungary)
  • Á. M. Móricz (Centre for Agricultural Research, Budapest, Hungary)
  • G. Morlock (Giessen University, Giessen, Germany)
  • A. Petruczynik (Medical University of Lublin, Lublin, Poland)
  • R. Skibiński (Medical University of Lublin, Lublin, Poland)
  • B. Spangenberg (Offenburg University of Applied Sciences, Germany)
  • T. Tuzimski (Medical University of Lublin, Lublin, Poland)
  • Y. Vander Heyden (Free University of Brussels, Brussels, Belgium)
  • A. Voelkel (Poznań University of Technology, Poznań, Poland)
  • B. Walczak (University of Silesia, Katowice, Poland)
  • W. Wasiak (Adam Mickiewicz University, Poznań, Poland)
  • I.G. Zenkevich (St. Petersburg State University, St. Petersburg, Russian Federation)

 

KOWALSKA, TERESA (1946-2023)
E-mail: kowalska@us.edu.pl

SAJEWICZ, MIECZYSLAW
E-mail:msajewic@us.edu.pl

Indexing and Abstracting Services:

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2022  
Web of Science  
Total Cites
WoS
647
Journal Impact Factor 1.9
Rank by Impact Factor

Chemistry, Analytical (Q3)

Impact Factor
without
Journal Self Cites
1.9
5 Year
Impact Factor
1.4
Journal Citation Indicator 0.41
Rank by Journal Citation Indicator

Chemistry, Analytical (Q3)

Scimago  
Scimago
H-index
29
Scimago
Journal Rank
0.28
Scimago Quartile Score

Chemistry (miscellaneous) (Q3)

Scopus  
Scopus
Cite Score
3.1
Scopus
CIte Score Rank
General Chemistry 211/407 (48th PCTL)
Scopus
SNIP
0.549

2021  
Web of Science  
Total Cites
WoS
652
Journal Impact Factor 2,011
Rank by Impact Factor Chemistry, Analytical 66/87
Impact Factor
without
Journal Self Cites
1,789
5 Year
Impact Factor
1,350
Journal Citation Indicator 0,40
Rank by Journal Citation Indicator Chemistry, Analytical 72/99
Scimago  
Scimago
H-index
29
Scimago
Journal Rank
0,27
Scimago Quartile Score Chemistry (miscellaneous) (Q3)
Scopus  
Scopus
Cite Score
2,8
Scopus
CIte Score Rank
General Chemistry 210/409 (Q3)
Scopus
SNIP
0,586

2020
 
Total Cites
650
WoS
Journal
Impact Factor
1,639
Rank by
Chemistry, Analytical 71/83 (Q4)
Impact Factor
 
Impact Factor
1,412
without
Journal Self Cites
5 Year
1,301
Impact Factor
Journal
0,34
Citation Indicator
 
Rank by Journal
Chemistry, Analytical 75/93 (Q4)
Citation Indicator
 
Citable
45
Items
Total
43
Articles
Total
2
Reviews
Scimago
28
H-index
Scimago
0,316
Journal Rank
Scimago
Chemistry (miscellaneous) Q3
Quartile Score
 
Scopus
393/181=2,2
Scite Score
 
Scopus
General Chemistry 215/398 (Q3)
Scite Score Rank
 
Scopus
0,560
SNIP
 
Days from
58
submission
 
to acceptance
 
Days from
68
acceptance
 
to publication
 
Acceptance
51%
Rate

2019  
Total Cites
WoS
495
Impact Factor 1,418
Impact Factor
without
Journal Self Cites
1,374
5 Year
Impact Factor
0,936
Immediacy
Index
0,460
Citable
Items
50
Total
Articles
50
Total
Reviews
0
Cited
Half-Life
6,2
Citing
Half-Life
8,3
Eigenfactor
Score
0,00048
Article Influence
Score
0,164
% Articles
in
Citable Items
100,00
Normalized
Eigenfactor
0,05895
Average
IF
Percentile
20,349
Scimago
H-index
26
Scimago
Journal Rank
0,255
Scopus
Scite Score
226/167=1,4
Scopus
Scite Score Rank
Chemistry (miscellaneous) 240/398 (Q3)
Scopus
SNIP
0,494
Acceptance
Rate
41%

 

Acta Chromatographica
Publication Model Online only
Gold Open Access
Submission Fee none
Article Processing Charge 400 EUR/article
Regional discounts on country of the funding agency World Bank Lower-middle-income economies: 50%
World Bank Low-income economies: 100%
Further Discounts Editorial Board / Advisory Board members: 50%
Corresponding authors, affiliated to an EISZ member institution subscribing to the journal package of Akadémiai Kiadó: 100%
Subscription Information Gold Open Access
Purchase per Title  

Acta Chromatographica
Language English
Size A4
Year of
Foundation
1988
Volumes
per Year
1
Issues
per Year
4
Founder Institute of Chemistry, University of Silesia
Founder's
Address
PL-40-007 Katowice, Poland, Bankowa 12
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 2083-5736 (Online)

Monthly Content Usage

Abstract Views Full Text Views PDF Downloads
Jan 2024 0 100 10
Feb 2024 0 176 22
Mar 2024 0 44 25
Apr 2024 0 23 27
May 2024 0 43 24
Jun 2024 0 32 15
Jul 2024 0 0 0