A new strategy for development of eco-friendly RP-HPLC method using Corona Charged Aerosol Detector and its application for simultaneous analysis of risperidone and its related impurities

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A new strategy for development of eco-friendly RP-HPLC method using Corona Charged Aerosol Detector and its application for simultaneous analysis of risperidone and its related impurities Nevena Maljurić, Biljana Otašević, Jelena Golubović, Jovana Krmar, Mira Zečević, Ana Protić

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Department of Drug Analysis, University of Belgrade – Faculty of Pharmacy, Vojvode Stepe 450, Belgrade, 11152, Serbia

ARTICLE INFO

ABSTRACT

Keywords: Green analytical chemistry CAD Ethanol Acetone RP-HPLC GAPI

Green analytical chemistry is primarily directed towards minimization of the amount of waste associated with either the sample preparation or analysis. Among different chromatographic methods, liquid chromatography is considered the least green, allowing for various possibilities for greening. Using green solvents such as ethanol or acetone in RP-HPLC, as an alternative to acetonitrile, is recently attracting an attention. Both ethanol and acetone are characterized with low toxicity, with certain drawbacks limiting their regular use in RP-HPLC. Ethanol has low eluotropic strength and causes high backpressures, while acetone shows high UV cut-off, making it unsuitable for UV/Vis detection. To overcome the existing problems, Corona Charged Aerosol Detector was employed for development of RP-HPLC methods for separation of risperidone and its structurally related impurities with either ethanol or acetone as organic modifier. The methods were optimized by experimental design methodology, while optimal conditions for separation were determined using Derringer's desirability function. Detailed assessment of 3D surface plots of Derringer's desirability function enabled selection of 0.6 mL min−1 flow rate and 20% (v/v) organic modifier content as optimal when using ethanol, while in case of acetone mobile phase flow rate was 0.8 mL min−1 and organic modifier content 17% (v/v). Methods were validated and their eco-friendly character was confirmed through Green Analytical Procedure Index (GAPI). Although both methods are ecologically acceptable, the main drawback is reflected in the fact that no recycling or another waste treatment method exist. In the end, acetone was prioritized over ethanol, due to lower health hazard and decreased amount of generated waste.

Corona Charged Aerosol Detector – CAD Green Analytical Procedure Index – GAPI Reversed-Phase High-Performance Liquid Chromatography – RP-HPLC Risperidone – Ris National Fire Protection Association – NFPA International Conference on Harmonization – ICH 1. Introduction Liquid chromatography is considered, generally, less green than for example gas chromatography, as it requires solvents for separation [1, 2]. There are various strategies available for attaching an eco-friendly character to liquid chromatography method. It could be accomplished by using smaller particle size and shorter columns, leading to efficient and fast separations. Apart from stationary phase modifications, certain mobile phase additives could also lead to development of green liquid

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chromatography methods. In that respect, supercritical fluids are used as green mobile phases due to beneficial environmental impact and low toxicity [3]. Furthermore, additives such as cyclodextrin could reduce the consumption of organic solvents by inclusion complexation with various drugs and influence on their retention behaviour [4]. Contemporary strategy for developing green liquid chromatography methods is utilization of alternative solvents, characterized as „green“. Although the physicochemical characteristics of acetonitrile, as the most commonly used organic solvent in RP-HPLC, are labelling it as golden standard in pharmaceutical analysis, it could be successfully replaced with green alternatives. This research would be directed towards investigation of potential of ethanol and acetone as acetonitrile green alternatives, preferred over acetonitrile due to lower toxicity and costs. Further, acetone is characterized with higher eluotropic strength in comparison to methanol, ethanol and acetonitrile, which enables reduced solvent consumption in case of prolonged analyte retention

Corresponding author. E-mail address: [email protected] (A. Protić).

https://doi.org/10.1016/j.microc.2019.104394 Received 23 July 2019; Received in revised form 4 November 2019; Accepted 4 November 2019 0026-265X/ © 2019 Elsevier B.V. All rights reserved.

Please cite this article as: Nevena Maljurić, et al., Microchemical Journal, https://doi.org/10.1016/j.microc.2019.104394

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Fig. 1. Chemical structures of risperidone and structurally related impurities.

the literature, such as National Environmental Methods Index (NEMI) as one of the firstly use [15], or Analytical Eco-Scale Score, as contemporary approach [16]. Eco-scale score assessment is semi-quantitative procedure, not providing comprehensive information about the analytical procedure. Therefore, to overcome the mentioned limitations, Green Analytical Procedure Index (GAPI) as more up-to-date approach was applied. GAPI uses pictograms to classify the ecological acceptability of every segment of analytical method. Symbol with five pentagrams representing sample preparation, sample storage and transport, instruments, reagents and method's quantitative potential is formed. Within each of five pentagrams, eco-friendly character is evaluated and marked with green, yellow and red pointing out small, medium and large toxic influence on the environment. Pentagram which refers to reagents assesses the amount, flammability and health hazard according to National Fire Protection Association (NFPA). NFPA classifies reagents as weakly (0 or 1 point), moderately (2 or 3 points) and highly (4 points) hazardous towards human health. The same classification is applied for the level of flammability. This approach provides qualitative information, while graphical presentation of pentagrams enables simple and fast comparison of the methods and consequent selection of desirable method [17]. Finally, the aim of the presented study was to develop and validate eco-friendly RP-HPLC method for separation of risperidone and its structurally related impurities (Fig. 1), using ethanol or acetone as mobile phase modifiers. Method development and optimization would be performed with an aid of experimental design methodology and Derringer's desirability function. Eco-friendly character of both methods, one with ethanol and the other with acetone, was evaluated using GAPI, as recently developed tool for assessment of analytical method “greenness”. Additionally, CAD responsiveness of investigated analytes would be discussed with respect to different experimental parameters and type of solvent.

[5]. However, low eluotropic strength and increased backpressure caused by high viscosity limit the applications of ethanol in HPLC [6, 7]. Moreover, the use of acetone is not widespread, because of high UV cut-off of 330 nm, making it unsuitable for UV detection [8]. To fulfil the presented gap, Corona Charged Aerosol Detector (CAD), compatible with solvents showing high UV cut-off values or analytes lacking chromophores, found its purpose. CAD is known as detector producing universal response, but certain principles of functioning should be taken into account when dealing with this detector. In order to be compatible with CAD mobile phase components need to meet the certain criteria in terms of high vapour pressure. Volatility of mobile phase components is a prerequisite since it is nebulized by nitrogen stream, forming droplets dried afterwards to remove the mobile phase and generate particles. For that reason, CAD responsiveness depends on non-volatility of investigated analytes on one hand and volatility of mobile phase components on the other hand, leading to efficient evaporation [9, 10]. Volatility of ethanol and acetone makes them compatible with CAD. On the other side, risperidone and its structurally related impurities are non-volatile analytes which makes them suitable for CAD. Risperidone is second-generation atypical antipsychotic, chemically 3[2-[4-(6-fluoro-1,2-benzisoxazol-3-yl)1-piperidinyl]ethyl]−6,7,8,9-tetrahydro-2-methyl-4H-pyrido[1,2-a]pyrimidin-4-one. Risperidone impurity 1 is its N-oxide, which is one of the most common degradation products. Further, its impurity 2 is synthetic impurity, while impurity 3 is bicyclorisperidone, specified by USP monographs of risperidone tablets and oral solutions [11]. Literature survey revealed that vast of methods, proposed for their determination, employed large volume of acetonitrile and/or methanol for elution purposes. For instance, Bharathi et al. for isolation and characterization of risperidone degradation products used gradient elution, within which final percentage of methanol-acetonitrile mixture in mobile phase was 70%, v/v [12]. Similarly, the highest proportion of methanol within the gradient program employed by Tomar et al. was 70%, v/v [13]. As an extreme, Dedania et al. achieved satisfactory separation between the active pharmaceutical ingredient and its degradation products with mobile phase consisting of methanol:acetonitrile (80% : 20%, v/v) [14]. This makes particular analytes challenging in the context of green analytical chemistry. So risperidone and its related impurities were selected as appropriate model mixture to test the proposed methodology. The development of green liquid chromatography methods should always be followed by the evaluation of their eco-friendly character. There are different approaches for “greenness” assessment available in

2. Theory Experimental design methodology is an efficient procedure of planning the experiments and defining the experimental space. Within the defined experimental space multiple linear regressions are used for fitting mathematical model to obtained experimental data. When the quality of mathematical models is confirmed through analysis of variance (ANOVA), they could be used in method optimization. Prior to optimization factors should be carefully chosen with respect to their 2

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influence on investigated response. In this study, when selecting the appropriate factors CAD principle of functioning should be taken into account. Bearing in mind the evaporation process, higher percentage of organic modifier in the mobile phase is favourable due to production of larger number of particles via lower viscosity, contributing to CAD response [18]. In that respect the percentage of either ethanol or acetone, as organic modifier, was investigated through experimental design. With respect to ecological aspect, polar mobile phases were preferable, so it was especially important to investigate the percentage of organic modifier which would not compromise CAD signal. Furthermore, CAD is considered mass-sensitive detector, so it is believed that higher flow rates bringing more analytes to the detector are producing higher responses [18]. For that reason, flow rate was another parameter to be investigated, and its interaction with the mobile phase composition in terms of proportions of organic and aqueous part should be assessed. Additional parameter included in experimental design was column temperature. Although the goal was to develop a method capable to adequately resolve the analytes, parameters were selected in the manner which does not compromise CAD signal. Influence of the aforementioned factors together with a few of CAD parameters was established through preliminary experiments. CAD's benefits are also reflected in easiness to use with only a few parameters to be optimized. Namely, evaporation temperature, filter setting and gain range are parameters with the largest influence on detector's sensitivity. Moreover, power function is applied to linearize the detector's response. It is well known that raw signal of CAD is mostly influenced by particle charge on the surface, and is not linear in the wide region of sample concentrations. Therefore, power function is used to improve the linearity for calibration purposes. The raw signal is mathematically transformed to chromatographic response according to the following equation:

Table 2 CAD parameters

Acetone

Ethanol

Domains −1 0

+1

Organic modifier content (%) Mobile phase flow rate (mL min−1) Column temperature ( °C)

15 0.50 25

25 1.00 50

20 0.75 37.5

50 ̊C 10.0 s 1.00 10 Hz

3.1. Instrument and chromatographic conditions Experiments were performed on Thermo Scientific, Dionex Ultimate 3000 equipped with Corona Veo Charged Aerosol Detector. Separation was achieved on Xterra C18 column (150 × 3.9 mm, 5 µm particle size), at temperatures varying from 25 to 50 °C. Injection volume was 10 µL. The mobile phase was prepared by mixing acetone or ethanol (15–25%, v/v) with HPLC water (pH 2.5 adjusted with formic acid). Mobile phase flow rate was varied from 0.5 to 1 mL min−1. Preliminary experiments served to decide which CAD parameters should be constant during the investigation. The defined optimal settings of CAD parameters are presented in Table 2. Data were analysed using Chromeleon 7.0.0. 3.2. Sample preparation Risperidone stock solution was prepared by dissolving 10 mg of reference standard substance in 10 mL of acetonitrile:water mixture (50:50, v/v) to obtain final concentration 1 mg mL−1. Stock solutions of three impurities were prepared following the same procedure, but to obtain final concentration of 0.25 mg mL−1. Working samples were prepared by taking 250 µL of risperidone, 50 µL of impurity 1, impurity 2 and impurity 3 stock solutions, respectively and mixing it with 600 µL of previously prepared mobile phase. Since mobile phase could be prepared with either ethanol or acetone, as organic modifier, there would be two working samples prepared. Before HPLC analysis, samples were mixed on Vortex mixer. Working samples were kept at room temperature for 48 h and remained stable. 3.3. Chemicals and reagents Risperidone and its structurally related impurities reference standard substances, as well as Rispolept® 4 mg tablets were obtained from Jannsen Pharmaceutical (Beerse, Belgium). For the purpose of mobile phase preparation, HPLC grade acetone was purchased from Sigma Aldrich Chemie GmbH (Taufkirchen, Germany), while absolute ethanol HPLC grade (>99.9% purity) from Baker (Deventer, the Netherlands). Deionized water was obtained from Simplicity 185 purification system Millipore (Billerica, USA). pH of the aqueous part of the mobile phase was set to 2.5 by adding the appropriate amount of formic acid (Sigma Aldrich Chemie GmbH, Taufkirchen, Germany) and using standard PHM210 pH-meter (Radiometer, Analytical SAS, France), equipped with glass electrode. The pH value equal to 2.5 was chosen in order to assure the presence of all the investigated analytes in their ionized forms. After preparation, mobile phase was vacuum filtered through membrane nylon filter 0.45 µm pore size (Agilent Technologies, Santa Clara, USA).

Table 1 Investigated factors and their domains. Numerical

Evaporation temperature Filter constant Power function Data collection rate

3. Experimental

where S0 is raw signal, S1 transformed signal, k the constant and PFV power function [19]. During the preliminary experiments values of evaporation temperature, filter setting, gain range and power function were analyzed and those providing the optimal signal to noise were selected and held constant during method optimization. Mobile phase flow rate, percentage of organic modifiers and column temperature, as statistically significant variables towards selectivity factors between critical pairs (impurity 2 and 3, risperidone and impurity 3), as a measure of separation were optimized by applying BoxBehnken response surface design. Domains of selected variables are presented in Table 1. Box Behnken design is approximately rotable type of response surface design with each factor studied at three levels (−1, 0, +1). Since it does not contain combinations where all factors are at limit levels, it would be chosen if responses under extreme conditions should be obtained [20-22]. Constructed 3D response surface plots enabled simple and rapid selection of optimal separation conditions. However, when dealing with more than one response it is advisable to employ multicriteria decision making approach, to simultaneously search for conditions providing optimal values of all investigated responses. In this study, Derringer's desirability function was applied. The desirable range depends on optimization criteria, which could be set differently. Desirability function ranges from 0 to 1, depending on

Factor Categorical

Values

whether the values fall within the desired range. If value of global desirability function is 1 all factors have the desirable values [23].

(1)

S1 = S0 PFV + k,

Parameter

3.4. Experimental design To properly define the experimental space and optimize the method, three factorial Box-Behnken design was employed. On the basis of 3

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preliminary experiments, the following continuous variables were selected and varied in the proposed ranges: the content of organic solvent in the mobile phase from 15% to 25% (v/v), mobile phase flow rate from 0.5 mL min−1 to 1 mL min−1, column temperature from 25 °C to 50 °C (Table 2). In addition, type of organic solvent (ethanol or acetone) was included as categorical variable.

analysis. However, another retention related characteristic is the analyte's ionization ability. With respect to basic character, most of the investigated analytes would be ionized with decreasing mobile phase pH. Therefore, lipophilicity of ionisable compounds should also be interpreted in terms of log D (risperidone pH=2.5 log D=−0.95). Risperidone and its related impurities have two pKa values. The first one, pKa1, corresponds to tertiary cyclic amine (piperidine ring) and its value ranged from 7.79 - 8.76 for all analytes except impurity 1 (pKa1 = 2.99, tertiary cyclic amine in a form of N-oxide). The second one, pKa2 corresponds to imine and for all analytes was in range of 0.41–1.16. In order to follow the concept of green chemistry, no other additives except formic acid were used. Formic acid was chosen for pH adjustment since met the certain volatility criteria needed for CAD. Moreover, mobile phase pH was set to 2.5 in order to have all the analytes in their ionized forms. If analytes are predominantly present in their ionized forms, interactions with C18 stationary phase would be diminished and retention times would be lower. Consequently, the percentage of organic solvent could be decreased with preserved ability to eluate apolar compounds. Mobile phase flow rate, percentage of organic modifiers and column temperature were identified through preliminary experiments as statistically significant variables towards selectivity factors between critical pairs (impurity 2 and 3, risperidone and impurity 3), which was chosen as a measure of separation. The selectivity (or separation) factor (α) is measured as a ratio of the retention factors (k) of the two adjacent peaks. Even though selectivity factor is not directly indicative of the baseline separation, it has the high impact on the resolution. Commonly, selectivity factor should be above 1, to provide separation of closely eluting peaks. Experimental plan, obtained by applying Box-Behnken design, together with calculated selectivity factors for two critical peak pairs is presented in Table 3. When discussing the selectivity factor between impurity 2 and impurity 3, two-factor interaction model was proposed explaining its relation with the examined variables. Response was transformed to the power of −2.56. It should be noted that solvent type (ethanol or acetone) was included in the model as categorical variable. The validity of the models was confirmed through high values of coefficient of determination and non-significant Lack of Fit test, whose values together with model's coefficients are presented in Table 4. For the second response, selectivity factor between impurity 3 and risperidone (transformed to the power of −2.61), software proposed quadratic model (Table 4). Proposed mathematical models enabled prediction of selectivity factors throughtout the whole previously defined experimental space. These transformations together with the data presented in Table 4, led to the generation of following equations:

3.5. Linearity To assess the linearity of both method with acetone and ethanol, stock solution of risperidone (10 mg mL−1) was prepared and used for preparation of seven calibration solutions. Appropriate volumes of risperidone stock solution were taken and mixed with appropriate mobile phase to obtain the following concentration range: 1.5–4.5 mg mL−1. Stock solutions of impurity 1 (100 µg mL−1), impurity 2 (100 µg mL−1) and impurity 3 (100 µg mL−1) served for preparation of seven calibration solutions for each impurity by taking an appropriate volumes of the stock solutions and adding an appropriate volume of the mobile phase (either with ethanol or acetone) to obtain the following concentration ranges: impurity 1 3–10 µg mL−1, impurity 2 1.5–5 µg mL−1 and impurity 3 1–3 µg mL−1. Linearity was assessed by constructing calibration curves for each analyte, plotting peak areas against analyte's concentration. 3.6. Accuracy and precision Pharmaceutical dosage form (tablets) containing risperidone as active component was used to prepare solutions for the accuracy and precision estimation. Firstly, the average tablet mass was determined out of twenty tablets and powdered. The appropriate amount of powdered tablet mass to obtain final concentration of 5 mg mL−1 was weighted, dissolved in ACN:H2O (50:50, v/v) mixture and kept on the ultrasonic bath for 30 min. When filtered, it was used to prepare working solution of risperidone at 100% concentration level (3 mg mL−1). According to obtained calibration curves, the amount of risperidone and related compounds in tablets could be determined. Knowing the amount of risperidone and its impurities, solutions for precision and accuracy assessment were prepared. The accuracy of the methods was performed by taking appropriate volumes of the prepared tablet solutions (5 mg mL−1) and adding the reference standard of the active compound to obtain solutions corresponding to 80%, 100% and 120% of nominal concentration. Each level was prepared in triplicate. Recovery values of active compound reference standard were calculated using calibration curves and served as a measure of accuracy. To calculate the percentage of the reference standard recovered for impurities the same procedure was performed. However, when preparing the solutions for accuracy assessment added impurities reference standards should correspond to LOQ, 100% and 120% concentration levels. The precision of the methods was estimated within the same concentration levels as in case of accuracy. The same solutions could be used and analyzed in triplicate. Precision is demonstrated through relative standard deviation (RSD).

2/3

2.56

= 0.54 + 0.15 A 3 AB + 3.335 e 3 BD

0.017 B + 0.019 C + 0.20 D

3 AC + 0.037 AD 1.857 e

1.813 e

6.114 e

3 BC + 2.516 e

3 CD (2)

4. Results and discussion

3/ R

2.61

= 0.47

0.052 A + 4.45 e

4 B + 9.594 e

3C

0.05 D

+ 0.054 AB + 0.014 AC

4.1. Development of green RP-HPLC methods for separation of model substances

0.044 AD 4 CD

7.312 e

3 BC + 0.015 BD + 1.765 e

0.022 A2 + 0.028 B2 + 0.029 C 2. (3)

Retention in HPLC is a result of analyte's interaction with stationary and mobile phase. Therefore, retention behaviour is generally influenced by stationary phase characteristics, mobile phase components and analyte's physicochemical properties. Risperidone and its structurally related impurities are basic lipophilic compounds. Risperidone's log P value is 2.89, while impurities log P values are approximately the same due to structural similarities. Lipophilic character of all investigated analytes required RP-HPLC as a method of choice for the

Based on the obtained and aforementioned mathematical model 3D response surface plots could be obtained for both critical peak pairs, enabling the selection of optimal separation conditions (Supplementary material, Fig. 1a and 1b). When using ethanol, impurity 2 and impurity 3 could be adequatly resolved if solvent's content is in range from 18 – 25% (v/v), while mobile phase flow rate could be from 0.5 to 1 mL min −1 . Risperidone and impurity 3 could be properly resolved if mobile 4

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The same stands for separation of investigated critical peak pairs with acetone. When dealing with separation of impurity 2 and 3, organic modifier's content should be above 17% (v/v), while adequate separation is achieved accross the whole investigated range of mobile phase flow rate. However, risperidone and impurity 3 could be resolved when acetone content is up to 18% (v/v), while mobile phase flow rate could be from 0.5 to 1 mL min −1, noting that better separation is achieved with mobile phase flow rate up to 0.8 mL min −1. Analysing 3D response surface graphs there were no unique conditions providing the optimal separation for both responses, so global desirability function with an ability of optimization of multiple responses was employed. The first step included establishment of optimization goals, which are to be fulfilled simultaneously for as many variables as tested. Desirability function enables determining the conditions under which all variables would have their optimal values. So, utilizing fitted models and establishing the criteria, individual desirability functions for each response were built. When variables are transformed into individual desirability functions, they are combined in global desirability function, enabling the simultaneous determination of optimal values. 3D plots of the global desirability function against two most influential factors, mobile phase flow rate and content of organic modifier were constructed based on obtained mathematical models, in order to find the best compromise for both critical pairs with either ethanol or acetone. The goals within Derringer's desirability function were target values of selectivity factor between impurity 2 and impurity 3 in range from 1.25 to 1.85, and selectivity factor between impurity 3 and risperidone from 1.25 to 1.78. Detailed assessment of constructed 3D plots (Fig. 2a and b) enabled the selection of optimal conditions for separation for both methods. In case of ethanol, the desirable separation would be achieved if mobile phase flow rate was set to 0.6 mL min−1 and organic modifier content to 20% (v/v), while in case of acetone mobile phase flow rate was 0.8 mL min−1 and organic modifier content 17% (v/v). Column temperature was kept constant at 37.5 °C during the analysis. When using ethanol, 3D plot of desirability function against temperature and flow rate (Supplementary material, Fig. 2a) and 3D plot of desirability function against temperature and organic modifier content (Supplmentary material, Fig. 2b) reveal that desirable separation could be achieved within the whole temperature range. However, if aceton is used, 3D plot of desirability function against temperature and flow rate shows no desirable separation among critical peak pairs (Supplementary material, Fig. 3a), while in a narrow range of optimal organic modifier content optimal desirable separation could be obtained within the whole temperature range (Supplementary material, Fig. 3b). Representative chromatograms obtained under selected optimal conditions are presented in Fig. 3. When comparing the obtained 3D plots of global desirability function against two most influential factors, mobile phase flow rate and content of organic modifier, it is noticable that in case of ethanol, the region of optimal separation conditions is wide, enabling the selection of optimal conditions from the centre of the region. Hence, providing the robustness of the method. On the other hand, if acetone is used the observed optimal region is narrow, mainly due to higher eluotropic strenght of acetone. The difference in optimal conditions region between ethanol and acetone is explained by different eluotropic strength of those solvents, since the goal was to achieve adequate separation of the investigated analytes. Nevertheless, application of experimental design methodology enabled drawing valid conslusions about CAD responsiveness for each of the investigated analytes within the defined experimental domains. Unlike the separation factor, CAD response of risperidone is mostly influenced by mobile phase flow rate and column temperature (Supplementary material, Fig. 4). Effect of organic modifier content or type of solvent is not significant. However, there is joint influence of organic modifier content and flow rate, as well as solvent type and flow

Table 3 Experimental plan. Exp No.

Organic modifier content (%)

Mobile phase flow rate (mL min−1)

Column temperature ( °C)

Solvent

α2/3

α3/R

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34

15.00 25.00 15.00 25.00 15.00 25.00 15.00 25.00 20.00 20.00 20.00 2000 20.00 20.00 20.00 20.00 20.00 15.00 25.00 15.00 25.00 15.00 25.00 15.00 25.00 20.00 20.00 20.00 20.00 20.00 20.00 20.00 20.00 20.00

0.50 0.50 1.00 1.00 0.75 0.75 0.75 0.75 0.50 1.00 0.50 1.00 0.75 0.75 0.75 0.75 0.75 0.50 0.50 1.00 1.00 0.75 0.75 0.75 0.75 0.50 1.00 0.50 1.00 0.75 0.75 0.75 0.75 0.75

37.50 37.50 37.50 37.50 25.00 25.00 50.00 50.00 25.00 25.00 50.00 50.00 37.50 37.50 37.50 37.50 37.50 37.50 37.50 37.50 37.50 25.00 25.00 50.00 50.00 25.00 25.00 50.00 50.00 37.50 37.50 37.50 37.50 37.50

Ethanol Ethanol Ethanol Ethanol Ethanol Ethanol Ethanol Ethanol Ethanol Ethanol Ethanol Ethanol Ethanol Ethanol Ethanol Ethanol Ethanol Acetone Acetone Acetone Acetone Acetone Acetone Acetone Acetone Acetone Acetone Acetone Acetone Acetone Acetone Acetone Acetone Acetone

1.66 1.32 1.72 1.45 1.80 1.36 1.85 1.32 1.59 1.59 1.44 1.48 1.52 1.54 1.52 1.52 1.48 1.26 1.03 1.29 1.03 1.24 1.03 1.22 1.03 1.13 1.16 1.10 1.12 1.12 1.14 1.14 1.14 1.11

1.19 1.32 1.35 1.25 1.31 1.35 1.35 1.33 1.31 1.31 1.26 1.27 1.29 1.30 1.29 1.29 1.26 1.29 1.68 1.31 1.40 1.34 1.78 1.31 1.58 1.39 1.37 1.38 1.42 1.46 1.38 1.36 1.35 1.40

α2/3 – selectivity factor between impurity 2 and 3; α3/R – selectivity factor between impurity 3 and risperidone. Table 4 Mathematical model's parameters Response Coefficients

α2/3 − 2.56

p-value

α3/R − 2.61

p-value

Intercept A B C D AB AC AD BC BD CD A2 B2 C2 Lack of fit test R2 R2 Adjusted R2 Predicted

0.54 0.15 −0.017 0.019 0.20 −6.114×10−3 3.335×10−3 0.037 −1.813×10−3 2.516×10−3 −1.857×10−3 – – – – – – –

< 0.0001 < 0.0001 0.0201 0.0085 < 0.0001 0.5292 0.7306 < 0.0001 0.8514 0.7134 0.7862 – – – 0.0933 0.9901 0.9858 0.9729

0.47 −0.052 4.45×10−4 9.594×10−3 −0.05 0.054 0.014 −0.044 −7.312×10−3 0.015 1.765×10−4 −0.022 0.028 0.029 – – – –

< 0.0001 < 0.0001 0.9509 0.1938 < 0.0001 < 0.0001 0.1955 < 0.0001 0.4770 0.0504 0.9805 0.0350 0.0111 0.0086 0.3631 0.9268 0.8792 0.7499

A – content of organic modifier in the mobile phase; B – mobile phase flow rate; C – column temperature; D – type of organic modifier (ethanol or acetone). p = 0.05 – significance threshold.

phase flow rate is less than 0.7 mL min −1, so the optimal separation conditions for all critical peak pairs would be a compromise of many different solution. 5

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Desirability

a

b Fig. 2. 3D plot of Derringer's desirability function when using ethanol (Fig. 2a) and acetone (Fig. 2b) at 37.5 °C column temperature.

of both methods [24]. Validation results for both methods are summarized in Table 5.

rate on CAD response of risperidone. When discussing CAD response of impurity 1, it can be concluded that it is greatly influenced by all investigated experimental parameters (Supplementary material, Fig. 5). The type of solvent appeared to be important when dealing with impurity 2 and 3. CAD responses of both impurity 2 and 3 are higher when using acetone as mobile phase organic modifier (Supplementary material, Fig. 6 and 7). One of the reasons could be higher volatility of acetone in comparison to ethanol, with vapour pressure of 24 kPa and 5.8 kPa at 20 °C, respectivelly. Effect of column temperature on CAD response is important for both impurity 2 and 3. On contrary, response of impurity 2 is influenced by flow rate, while impurity 3 by organic modifier content.

4.3. GAPI assessment of developed RP-HPLC methods The eco-friendly character of method developed with ethanol or acetone as organic modifier was evaluated and illustrated applying GAPI pentagrams (Fig. 4a and b). When analysing GAPI pentagram illustrating RP HPLC method with ethanol, it could be seen that green and yellow aspects are dominant labelling the method as eco-friendly. Pentagram referring to sample preparation shows that no extraction was performed and samples were prepared with green solvents. Moreover, there was no preservation, storage or transportation of the sample. Further, when discussing about the reagents used, the amount was less than 10 mL per analysis. In terms of health hazard ethanol was moderately toxic, while in terms of safety there were no significant hazards. When discussing the applied instruments, method could be considered “green”, since LC is labelled as technique with low energy consumption [25]. The main disadvantage of the method is reflected in lack of waste treatment, since there was no recycling or any other waste treatment. However, when analysing GAPI pentagram obtained for RP-HPLC method with acetone, similar conclusions could be drawn. In general, method could be considered eco-friendly, with the same main drawback regarding the waste treatment. Moreover, acetone is considered slightly toxic and irritant, so its health hazard is lower in comparison with ethanol, giving priority to acetone as green organic modifier in RPHPLC method development.

4.2. Validation of the developed methods Both methods for separation of risperidone and its related compounds were validated according to International Conference on Harmonization (ICH) Q2 (R1) guideline [24]. Excipients from Rispolept® tablets did not interfere, while the peak purity of the compounds was 99%, confirming the selectivity of the method. For all impurities, within both methods, limits of detection (LOD) and limits of quantification (LOQ) were determined, using signal to noise approach (Table 5). Each impurity sample at LOQ level was injected in 10 replicates and RSD values below 10% confirmed the validity of proposed LOQs. Linear correlations between concentration and detector response were found in ranges presented in Table 5. The amount of risperidone in Rispolept® tablets was 97.54% for method with ethanol and 99.30% for method with acetone. Concentrations of risperidone impurities were below LOD. Recovery values, confirming the accuracy of both methods, are within the acceptance criteria (98.0–102.0% for active compounds and 70.0–130.0% for impurities with the specification limit of 0.5%) [24]. Moreover, RSD values ≤ 2% for active compounds and ≤ 15% for impurities with the specification limit of 0.5% confirm the precision

4.4. Study limitations and plan for future work This study gives a contribution to the field of green liquid chromatography enabling usage of solvent not compatible with the most 6

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Fig. 3. Representative chromatogram obtained under optimal separation conditions for ethanol (Fig. 3a) and acetone (Fig. 3b) as organic modifier.

frequently used UV detector. However, it also has certain limitations, which guide authors to future research. Firstly, methods were developed at one defined pH of 2.5 to provide the ionized form of all investigated analytes. Ionized form of analytes was important due to shorter retention times accompanied with reduced solvents consumption, contributing to overall green liquid chromatography concept. On the other hand, low percentage of organic modifier was challenging from the perspective of CAD principle of functions. However, introducing pH as one of the variable in experimental design would be one of the future steps. Secondly, CAD is recognized as easily operable detector with only a few parameters to be set. However, when dealing with CAD, the problem with baseline noise is an important issue, by virtue of aforementioned small number of parameters. Using CAD, the baseline noise is not easily eliminated, so its influence on detector signal cannot be neglected. It is thus important to search for conditions enabling the reduction of the baseline noise while simultaneously increasing the model substance response. Moreover, investigating an addition of different additives compliant with green chromatography concept would also add value in terms of improvement of peak shape and symmetry.

risperidone and structurally related impurities with either ethanol or acetone, as organic modifier. Optimal separation conditions for ethanol were mobile phase flow rate 0.6 mL min−1, organic modifier content 20% (v/v), and column temperature 37.5 °C, while in case of acetone mobile phase flow rate was 0.8 mL min−1, organic modifier content 17% (v/v) and column temperature 37.5 °C. 3D response surface plots of Derringer's desirability function against organic modifier content and mobile phase flow rate enabled the selection of optimal separation conditions as well as the comparison of different modifiers.. Both methods were validated and assigned with eco-friendly character according to constructed GAPI pentagrams. However, in terms of “greenness” acetone was favoured over ethanol due to lower health hazard, since the main limitation of both methods in terms of ecofriendly character was the lack of waste treatment. The study highlighted the potential of CAD in creating the environment for utilization of green solvents as acetonitrile alternatives in RP-HPLC. Moreover, among the examined modifiers acetone could be recommended due to shorter analysis time and lower health risk in comparison to ethanol. Declaration of Competing Interest

5. Conclusion

The authors declare that they have no conflict of interest.

Derringer's desirability function enabled simple and sped-up development and optimization of RP-HPLC methods for separation of 7

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Table 5 Validation parameters Substance

RP-HPLC method with ethanol

RP-HPLC method with acetone

LOD (µg mL−1)

Linearity Concentration range (µg mL−1)

a

b

R

Risperidone

–

1500–4500

10.954

10.402

0.997

Impurity 1

3.00

10.00–60.00

28.487

0.144

0.993

Impurity 2

1.5

5.00–30.00

51.798

−0.055

0.999

Impurity 3

1.00

3.00–18.00

48.297

−0.001

0.995

Risperidone

–

1500–4500

8.262

5.406

0.999

Impurity 1

3.00

10.00–60.00

20.736

−0.056

0.999

Impurity 2

1.5

5.00–30.00

26.447

0.014

0.998

Impurity 3

1.00

3.00–18.00

23.304

−0.044

0.996

Concentration level

Recovery (R, %)

Precision (RSD, %)

(80%) (100%) (120%) (LOQ) (100%) (120%) (LOQ) (100%) (120%) (LOQ) (100%) (120%) (80%) (100%) (120%) (LOQ) (100%) (120%) (LOQ) (100%) (120%) (LOQ) (100%) (120%)

100.96 101.58 101.92 112.78 72.70 72.65 103.68 71.58 71.62 86.82 70.14 81.11 101.48 101.89 100.83 70.25 71.51 76.51 91.02 100.83 99.39 127.78 10.15 93.74

0.76 0.56 0.61 9.16 8.97 9.88 6.47 1.74 8.32 4.74 5.38 1.19 1.71 1.06 0.12 0.79 5.65 1.53 4.63 3.54 1.72 9.63 1.01 0.55

a– slope, b– intercept, r– correlation coefficient (acceptance value >0.99 for active compounds, >0.98 for related compounds); Recovery: 98.0–102.0% for active compounds, 70–130% for impurities with the specification limit of 0.5%; RSD: ≤ 2% for active compounds, ≤ 15% for impurities with the specification limit of 0.5%.%

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Fig. 4. GAPI pentagrams. 4a: GAPI pentagram for RP-HPLC method with ethanol. 4b: GAPI pentagram for RP-HPLC method with acetone .

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