Solubility of caffeine in N-methyl-2-pyrrolidone + ethanol mixture at different temperatures

Journal Pre-proof Solubility of caffeine in N-methyl-2-pyrrolidone + ethanol mixture at different temperatures

Homa Rezaei, Elaheh Rahimpour, Taravat Ghafourian, Fleming Martinez, Mohammad Barzegar-Jalali, Abolghasem Jouyban PII:

S0167-7322(19)36679-6

DOI:

https://doi.org/10.1016/j.molliq.2019.112354

Reference:

MOLLIQ 112354

To appear in:

Journal of Molecular Liquids

Received date:

4 December 2019

Accepted date:

18 December 2019

Please cite this article as: H. Rezaei, E. Rahimpour, T. Ghafourian, et al., Solubility of caffeine in N-methyl-2-pyrrolidone + ethanol mixture at different temperatures, Journal of Molecular Liquids(2019), https://doi.org/10.1016/j.molliq.2019.112354

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© 2019 Published by Elsevier.

Journal Pre-proof

Solubility of caffeine in N-methyl-2-pyrrolidone + ethanol mixture at different temperatures

Homa Rezaei

a,b

, Elaheh Rahimpour

b,c,*

, Taravat Ghafourian d, Fleming Martinez e, Mohammad

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Barzegar-Jalali f, Abolghasem Jouyban b,g

a

Student Research Committee, Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran Pharmaceutical Analysis Research Center and Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran c Food and Drug Safety Research Center, Tabriz University of Medical Sciences, Tabriz, Iran d School of Life Sciences, University of Sussex, Brighton, BN1 9QG, UK e Grupo de Investigaciones Farmacéutico-Fisicoquímicas, Departamento de Farmacia, Facultad de Ciencias, Universidad Nacional de Colombia – Sede Bogotá, Cra. 30 No. 45-03, Bogotá, D.C., Colombia f Research Center for Pharmaceutical Nanotechnology and Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran g Digestive Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran.

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b

*

Corresponding author. E-mail: [email protected]

Journal Pre-proof ABSTRACT The solubility profile of caffeine in the binary non-aqueous mixtures of N-methyl-2-pyrrolidone (NMP) and ethanol at different temperatures is determined and the obtained data are fitted to some linear and non-linear cosolvency models including the van’t Hoff, the double log-log, the mixture response surface, Yalkowsky, Jouyban-Acree, Jouyban-Acree-van’t Hoff, and the modified Wilson models. The measured density data of caffeine saturated solutions as another

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physico-chemical property are also correlated with the Jouyban-Acree model and the results are

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discussed. In order to investigate the accuracy of the applied models, the mean relative

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deviations (MRD%) of the back-calculated solubility data is calculated. Furthermore, the

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apparent thermodynamic properties of caffeine dissolution process are also calculated by using

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van’t Hoff and Gibbs equations.

Keywords: Solubility; Caffeine; N-Methyl-2-pyrrolidone;Ethanol, Binary solvent mixtures; Cosolvency models.

Journal Pre-proof 1. Introduction Caffeine (3,7-dihydro-1,3,7-trimethyl-1H-purine-2,6-dione, Fig. 1) belonging to N-methyl derivatives of xanthine is commonly found in cocoa beans, coffee, tea leaves and cola nuts. It is also present in many antimigraine and painkiller pharmaceuticals [1, 2]. Some important physiological effects of caffeine are stimulation of the central nervous system, gastric acid secretion and diuresis and increasing blood pressure in the short term [3]. Extraction of caffeine

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is an important industrial process which is achieved by employing various aqueous or non-

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aqueous solvents or mixed solvents. Therefore, solubility data in aqueous and nonaqueous

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solvents provide useful information for the extraction and/or purification of this drug [4].

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Solubility is considered as an essential property for immiscible solvent mixtures used for

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extraction procedures and antisolvent/solvent systems used for purification because it helps the researchers to choose the optimized solvent medium for each purpose [5, 6]. So far, the solubility

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of caffeine has been studied in monosolvents of ethyl acetate, water, carbon tetrachloride, ethanol, chloroform, methanol, acetone and dichloromethane at temperature range of 298 – 323

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K by Shalmashi and Golmohammad [7], in binary solvent mixtures of water with methanol,

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ethanol, 1-propanol, ethyl acetate or acetone at temperature range of 288.15 – 328.15 K by Zhong et al. [8], in the aqueous mixture of polyethylene glycol 400 and propylene glycol at 298.2 K by Gould et al. [9], in the aqueous mixture of dioxane at 298.2 K by Adjei et al. [10], and in the aqueous N, N-dimethylformamide mixture at 298.2 K by Herrador et al. [11]. However, there is no report for caffeine solubility study in non-aqueous systems. In the present work, a non-aqueous mixture of N-methyl-2-pyrrolidone (NMP) and ethanol is selected for the study of caffeine solubility. NMP with a chemical formula of C5H9NO is an aprotic polar solvent with considerable solubilizing property. It is very commonly employed in pharmaceutical

Journal Pre-proof products manufacture [5]. In addition, ethanol with a chemical formula of C2H6O is considered as one of the most commonly used non-aqueous solvents in the pharmaceutical industry for drug purification or preformulation [12]. To the best of the authors’ knowledge, there is no report on the investigation of caffeine solubility in the binary non-aqueous mixture of NMP and ethanol. ***Fig. 1***

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In order to extend solubility database of caffeine in the binary cosolvency systems, the aims of current study are to (1) determine the solubility and density of caffeine saturated mixtures in the

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mixtures of NMP and ethanol at various temperatures; (2) correlate the data with some

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process in the mixtures of NMP and ethanol.

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cosolvency models; and (3) compute the thermodynamic parameters for caffeine dissolution

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2. Materials and method

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2.1. Materials

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Caffeine (mass fraction purity of 0.997, Dana Pharmaceutical Company, Iran), NMP (mass fraction purity of > 0.998, Chem_lab NV, Belgium,), ethanol with mass fraction purity of 0.999, (Scharlau Chemie, Spain), and ethanol with mass fraction purity of 0.935 (for dilution purposes prior to spectrophotometric analysis) (Jahan Alcohol Teb, Arak, Iran) are the materials employed in the current work.

2.2. Measurement of caffeine solubility

Journal Pre-proof A commonly used shake-flask method [13] was employed for the solid-liquid equilibrium of caffeine in the non-aqueous mixtures of NMP and ethanol. Excess caffeine was dispersed into the vials containing either 10 g of each mono solvent or solvent mixtures in various mass ratios. After sealing, the vials were placed in an incubator (Nabziran Industrial Group, Tabriz, Iran) at definite temperatures (± 0.2 K) on a shaker (Behdad, Tehran, Iran). After equilibrating for 48 h, the mixtures were centrifuged, diluted with water: ethanol mixture in volume fraction of 1:1, and

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their absorbance was determined at 273 nm by a spectrophotometer model UV-1800 (Shimadzu,

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Kyoto, Japan). The concentration of caffeine in the saturated solutions was obtained according to

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previously plotted calibration curve. Data reported for caffeine solubility are the average of three replicated solubility measurements. The density values for the saturated mixtures were measured

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2.3. Thermodynamic parameters

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by a 5 mL pycnometer with the uncertainty of 0.001 g∙cm-3.

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The van’t Hoff and Gibbs equations were used to study the dissolution behavior of caffeine in

 ln x 1 1    T Thm

  p

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the binary mixtures of NMP and ethanol. The modified van’t Hoff equation can be written as: 

H  R

(1)

x is caffeine solubility in the mole fraction unit, T is the absolute temperature (K) and R is the ideal gas constant (J.mol-1.K-1), respectively [14]. Thm defined as the mean harmonic temperature n

was computed according to: Thm  n /  (1/ T ) , in which n is the number of temperatures studies. i 1

Journal Pre-proof G and H of solutions were obtained from the intercept and the slope of the plot of ln x against 1/T − 1/Thm, respectively [15], and Gibbs equation was used to obtain S . The relative contributions of entropy ( TS) and enthalpy (H) to G of dissolution procedure were computed by Eq. (2) and (3) [15].

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TS  ( H   TS  )

(3)

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 TS 

(2)

( H   TS  )

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H 

H 

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2.4. Mathematical models

The mole fraction solubility measured for caffeine in the mixtures of NMP and ethanol were

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fitted to some linear models such as van’t Hoff equation, the double log-log model, the mixture

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response surface model, the Yalkowsky equation, the Jouyban-Acree model, the Jouyban-Acree-

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van’t Hoff model, and a non-linear model, the modified Wilson, which details of each mentioned model are given in the following sections.

2.4.1. van’t Hoff equation The van’t Hoff equation which relates the solubility value to the temperature is as [16]: ln x  A 

B T

here, A and B are the equation parameters.

(4)

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2.4.2. The double log-log model The double log-log model is a cosolvency model for solubility data fitting according to below equations [17]:

ln[ln( xm / x2 )]  ln[ln(( xm ) 0.5 / x2 )]  B ln( w1 / w2 )

(5)

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for 0 < w1 ≤ 0.5

(6)

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for 0 < w2 ≤ 0.5

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ln[ln( x1 / xm )]  ln[ln( x1 /( xm ) 0.5 )]  b ln( w2 / 0.5)

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here, x1 and x2 are the mole fraction drug solubility in the solvents 1 and 2, ( xm ) 0.5 is the drug

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solubility in the mixtures with the cosolvent mass fraction of 0.5, w1 and w2 are the mass

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fractions of solvents 1 and 2 in the absence of solute. B and b are the equation factors.

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2.4.3. The mixture response surface (MRS) method MRS model can be written as:

 1   1  ln xm  1 w'1   2 w2   3     4     5 w'1 .w2  w1   w1 

(7)

1  5 are model’s parameters and w1' and w2' are computed by using w1'  0.96 w1  0.02 and w2'  0.96 w2  0.02 [18].

2.4.4. Yalkowsky model

Journal Pre-proof The natural logarithmic solubility value in the binary mixtures can be calculated by Yalkowsky model as [19]:

ln x m  w1 ln x1  w2 ln x 2

(8)

The terms have the same definition as those given in the previous equations.

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2.4.5. Jouyban-Acree model

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The Jouyban–Acree model is another linear model that can be employed to fit the experimental

where

Ji

terms

are

the

2

 J .(w i 0

i

 w2 ) i

model

1

parameters

obtained

by

linear

regression

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w1 .w2 w1 .w2 ( w1  w2 ) w .w ( w  w2 ) 2 , , and 1 2 1 [21]. T T T

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(ln x m,T  w1 ln x1,T  w2 ln x 2,T ) against

(9)

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w1 .w2 T

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ln xm,T  w1 ln x1,T  w2 ln x2,T 

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data at different temperatures. The general form of Jouyban–Acree model is as [20]:

The measured density values for caffeine in the binary mixture of NMP and ethanol can be also

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fitted and back-calculated by the modified Jouyban-Acree model, where the solubility factors in Eq. (9) are replaced by the density factors for the investigated mixtures.

2.4.6. Jouyban-Acree-van’t Hoff model The combination of the Jouyban-Acree model with the van’t Hoff model results in an accurate model for correlating/predicting drug solubility in the solvent mixtures. The Jouyban-Acree-van’t Hoff model [22] is written as:

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ln xm,T

B B w .w  w1 ( A1  1 )  w2 ( A2  2 )  1 2 T T T

2

 J .(w i 0

i

 w2 ) i

1

(10)

Here, A1, B1, A2, B2 and Ji parameters are the model parameters which can be calculated by a simple linear regression.

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2.4.7. The modified Wilson model

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In addition to mentioned linear models employed for fitting / prediction of drug solubility data, a non-linear model, the modified Wilson, can be also used for the correlation of the solubility data

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w1 1  ln x1  w2 1  ln x 2   w1  w2 12 w121  w2

(11)

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 ln x m  1 

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at a given temperature. The general form of the model is as [23]:

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2.4.8. Model accuracy

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λ12 and λ21 are the equation factors computed by a simple nonlinear analysis.

The measured solubility data were fitted into the defined models and the models were used to calculate the solubility data. Then mean relative deviation (MRD%) (Eq. (12) of the calculated solubility were obtained as a measure of the accuracy of the correlations.

% MRD 

100  Calculated Value  Observed Value    N Observed Value  

N is the number of data points.

(12)

Journal Pre-proof 3. Results and discussions 3.1. Solubility profile of caffeine in the binary mixtures of NMP and ethanol The measured caffeine solubility (in mole fraction) in the binary mixtures of NMP and ethanol at different temperatures, and the standard deviation of the three replicated measurements are listed in Table 1. The lowest solubility data for caffeine in the binary mixtures of NMP and ethanol is

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measured for neat ethanol at 293.2 K (C = 1.47 × 10-2 mol∙L-1), whereas the highest one is measured for neat NMP at 313.2 K (C = 1.95 × 10-1 mol∙L-1). The caffeine solubility values

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increase with increase in temperature and NMP mass fraction.

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3.2. Thermodynamic parameters

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***Table 1***

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Table 2 gives H , S , and G of caffeine dissolution process in the binary mixtures of NMP

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and ethanol, obtained according to van’t Hoff and Gibbs equations at Thm=303.0 K. The highest and lowest H for caffeine in the investigated solvent mixtures are 28.70 kJ.mol−1 and 13.01

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kJ.mol−1, in w1 = 0.0 and w1 = 1.0, respectively. S values in all mixtures are positive and the lowest and highest values are 8.68 and 39.58 J.K–1.mol−1, in w1 = 1.0 and w1 = 0.0, respectively. Furthermore, G values are within the range of 16.71 and 10.38 kJ.mol−1 with the lowest value

for w1 = 1.0 (solubility in neat NMP), demonstrating that caffeine dissolution process is more favorable in this solvent (hence the increased solubility). Table 2 shows that H for all solvents and solvent mixtures is positive, but it is decreasing with the increase in NMP composition of the solvent mixture. Hence, it is concluded that the dissolution of caffeine in the binary mixtures of NMP and ethanol is endothermic, and entropically favorable. H and TS are also reported in

Journal Pre-proof Table 2. The enthalpy is the main contributor of G of caffeine dissolution procedure (H > TS and H > 0.6 in all solvents). ***Table 2*** In order to study the co-solvency mechanism of caffeine in the binary mixtures of NMP and ethanol, the H vs G plot was used [24]. Fig. 2 demonstrates a non-linear behavior with two

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regions with positive slope (0.0 ≤ w1 ≤ 0.1, and 0.3 ≤ w1 ≤ 1.0) indicating that by increasing

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ethanol ratio in the mixed solvents (within the above ranges), enthalpy and free energy both increase. This indicates that the dissolution becomes more endothermic at ethanol increases,

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hence evidence for less favourable caffeine-solvent interaction at higher ethanol concentrations.

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Figure shows a very slight reduction in enthalpy change with increasing G , i.e. a negative

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slope, at (0.1 ≤ w1 ≤ 0.3), which indicates entropy becomes slightly more favaourable when

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ethanol concentration increases from 0.7 to 0.9.

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***Fig. 2***

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3.3. Computational modeling of caffeine solubility The caffeine mole fraction solubility data in the binary solutions of NMP and ethanol were fitted into some mathematical cosolvency models including the van’t Hoff, Yalkowsky, Jouyban– Acree, Jouyban-Acree–van’t Hoff, the modified Wilson and double log-log and MRS models. The parameters of each model along with MRD% of back-calculated solubility data are given in Tables 3-8. The comparison of the MRD% values between these models show a similar error level for all models. However, two models, Jouyban-Acree and Jouyban-Acree-van’t Hoff, stand-out in terms of capability to predict for different temperatures as well as different solvent

Journal Pre-proof compositions. On the other hand, van’t Hoff model predicts caffeine solubility at different temperatures (in the same solvent system), whereas Yalkowski model, modified Wilson model, the double log-log model and mixture response surface model predict caffeine solubility in different solvent compositions (measured at the same temperature). The prediction capability of Jouyban-Acree-van’t Hoff model was also investigated by employing the minimum number of fitting data i.e. solubility data in neat solvents 1 and 2 at

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293.2 and 313.2 K and in solvent mixtures with NMP mass fractions of 0.3, 0.5 and 0.7 at 298.2

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K. Eq. (10) is trained by using these minimum data and then the solubility values in other mass

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fractions of NMP was predicted by using the trained model. The MRDs% for predicted solubility

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respectively. The overall MRD is 2.2 %.

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data at 293.2, 298.2, 303.2, 308.2 and 313.2 K are 2.3%, 1.7%, 2.4%, 3.0% and 1.8%,

***Tables 3- 8***

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In another effort, caffeine solubility data in NMP and ethanol were correlated with a recently

w2 2,T

e

w1 . w2 2 J i ( w1  w2 )i T i 0



(13)

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xm,T  x  x w1 1,T

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modified version of Jouyban-Acree model in the arithmetic scale [25].

e is the Euler's number (e = 2.718). The trained model is as:

xm,T  x  x w1 1,T

w2 2 ,T

e

{87.946.

w1 . w2 w .w ( w  w ) w .w ( w  w )2 128.066. 1 2 1 2 83.638. 1 2 1 2 } T T T

(14).

The back-calculated MRD% for Jouyban-Acree model in logarithmic scale is 3.9% (Table 5) whereas %MRD for Eq. (14) in the arithmetic scale is 1.6 % (N=55).

Journal Pre-proof 3.4. Density data and statistical modeling The density values of caffeine saturated mixtures can also be mathematically correlated by the Jouyban-Acree model [26]. The obtained trained model in the binary mixtures of NMP and ethanol (Table 9) is as below: ln  m,T  w1 . ln 1,T  w2 . ln  2,T





(15)

w1 .w2  6.116  1.866 ( w1  w2 ) T

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

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Here, m,T is the density of caffeine saturated mixture of solvents and 1,T , and 2,T are the

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density of caffeine saturated solvents 1 and 2 at temperature T. The back-calculated MRD% for

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density prediction at various temperatures.

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density data is 0.1 % illustrating that the Jouyban-Acree model provides a good model for the

4. Conclusions

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***Table 9***

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The caffeine solubility data in the mixed solutions of NMP and ethanol at various temperatures

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were measured and fitted into some linear cosolvency models such as van’t Hoff, the double loglog, the MRS, the Yalkowsky, the Jouyban-Acree, the Jouyban-Acree-van’t Hoff models, and a non-linear modified Wilson model. The accuracy of used models was investigated by obtaining MRDs% of back-calculated data. Furthermore, the thermodynamic parameters of caffeine dissolution process were also computed and discussed. The results showed entropy driven, endothermic dissolution process, with decreasing enthalpy as NMP ratio in the solvent mixture increased. Solubility models could calculate caffeine solubility in the solvent mixtures at different temperature with a very low mean relative deviation. The Jouyban-Acree and the

Journal Pre-proof Jouyban-Acree-van’t Hoff models stand out as requiring minimum data with maximum prediction capabilities (extrapolations to various temperatures and various solvent compositions).

Acknowledgments Research reported in this publication was supported by Elite Researcher Grant Committee under

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grant number 977199 from the National Institutes for Medical Research Development (NIMAD),

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Tehran, Iran.

Journal Pre-proof References

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[1] E. Abourashed, U. Koetter, A. Brattström, In vitro binding experiments with a Valerian, hops and their fixed combination extract (Ze91019) to selected central nervous system receptors, Phytomedicine 11 (2004) 633-638. [2] M.A. Tarnopolsky, Caffeine and endurance performance, Sports Med. 18 (1994) 109-125. [3] H. Ashihara, A. Crozier, Caffeine: A well known but little mentioned compound in plant science, Trends Plant Sci. 6 (2001) 407-413. [4] L. Di, P.V. Fish, T. Mano, Bridging solubility between drug discovery and development, Drug Discov. Today 17 (2012) 486-495. [5] R.G. Strickley, Solubilizing excipients in oral and injectable formulations, Pharm. Res. 21 (2004) 201-230. [6] J. Alsenz, M. Kansy, High throughput solubility measurement in drug discovery and development, Adv. Drug Deliv. Rev. 59 (2007) 546-567. [7] A. Shalmashi, F. Golmohammad, Solubility of caffeine in water, ethyl acetate, ethanol, carbon tetrachloride, methanol, chloroform, dichloromethane, and acetone between 298 and 323 K, Lat. Am. Appl. Res. 40 (2010) 283. [8] J. Zhong, N. Tang, B. Asadzadeh, W. Yan, Measurement and correlation of solubility of theobromine, theophylline, and caffeine in water and organic solvents at various temperatures, J. Chem. Eng. Data 62 (2017) 2570-2577. [9] P.L. Gould, M. Goodman, P.A. Hanson, Investigation of the solubility relationships of polar, semi-polar and non-polar drugs in mixed co-solvent systems, Int. J. Pharm. 19 (1984) 149159. [10] A. Adjei, J. Newburger, A. Martin, Extended Hildebrand approach: solubility of caffeine in dioxane–water mixtures, J. Pharm. Sci. 69 (1980) 659-661. [11] M.A. Herrador, A.G. González, Solubility prediction of caffeine in aqueous N, Ndimethylformamide mixtures using the extended Hildebrand solubility approach, Int. J. Pharm. 156 (1997) 239-244. [12] D. Lewis, D. Ganderton, B. Meakin, P. Ventura, G. Brambilla, R. Garzia, Pharmaceutical aerosol composition, Google Patents, 2009. [13] A. Jouyban, M.A.A Fakhree, In: W.E. Acree Jr (Ed.) Toxicity and Drug Testing, Intech Co., New York, 2012, Chap. 9. [14] S. Vahdati, A. Shayanfar, J. Hanaee, F. Martínez, W.E. Acree Jr, A. Jouyban, Solubility of carvedilol in ethanol+ propylene glycol mixtures at various temperatures, Ind. Eng. Chem. Res. 52 (2013) 16630-16636. [15] G.L. Perlovich, S.V. Kurkov, A. Bauer-Brandl, Thermodynamics of solutions: II. Flurbiprofen and diflunisal as models for studying solvation of drug substances, ‎Eur. J. Pharm. Sci. 19 (2003) 423-432. [16] C. Zhou, X. Shi, H. Wang, N. An, Measurement and correlation of solubilities of transferulic acid in solvents, J. Chem. Ind. Eng. 58 (2007) 2705. [17] M. Barzegar-Jalali, J. Hanaee, Model for solubility estimation in mixed solvent systems, Int. J. Pharm. 109 (1994) 291-295. [18] A.B. Ochsner, R.J. Belloto Jr, T.D. Sokoloski, Prediction of xanthine solubilities using statistical techniques, J. Pharm. Sci. 74 (1985) 132-135.

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[19] S.H. Yalkowsky, T.J. Roseman, Solubilization of drugs by cosolvents, in: S.H. Yalkowsky (Ed.), Techniques of Solubilization of Drugs, Marcel Dekker Inc, New York, 1981, pp. 91– 134. [20] A. Jouyban, W.E. Acree Jr, Mathematical derivation of the Jouyban-Acree model to represent solute solubility data in mixed solvents at various temperatures, J. Mol. Liq. 256 (2018) 541-547. [21] A. Jouyban, M. Khoubnasabjafari, H.-K. Chan, W.E. Acree Jr, Mathematical representation of solubility of amino acids in binary aqueous-organic solvent mixtures at various temperatures using the Jouyban-Acree model, Pharmazie 61 (2006) 789-792. [22] A. Jouyban, M.A.A. Fakhree, W.E. Acree Jr, Comment on “measurement and correlation of solubilities of (z)-2-(2-aminothiazol-4-yl)-2-methoxyiminoacetic acid in different pure solvents and binary mixtures of water+(ethanol, methanol, or glycol)”, J. Chem. Eng. Data 57 (2012) 1344-1346. [23] A. Jouyban-Gharamaleki, The modified Wilson model and predicting drug solubility in water-cosolvent mixtures, Chem. Pharm. Bull. 46 (1998) 1058-1061. [24] M. Gantiva, F. Martínez, Thermodynamic analysis of the solubility of ketoprofen in some propylene glycol+ water cosolvent mixtures, Fluid Phase Equilibr. 293 (2010) 242-250. [25] S. Dadmand, F. Kamari, W.E. Acree Jr, A. Jouyban, A new computational method for drug solubility prediction in methanol+ water mixtures, J. Mol. Liq. 292 (2019) 111369. [26] A. Jouyban, A. Fathi-Azarbayjani, M. Khoubnasabjafari, W.E. Acree Jr, Mathematical representation of the density of liquid mixtures at various temperatures using Jouyban-Acree model, Indian J. Chem. 44A (2005) 1553–1560.

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Fig. 1. Molecular structure of caffeine

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Fig. 2. Enthalpy-entropy compensation plot for caffeine in the binary mixtures of NMP and ethanol at 303.0 K. The points represent the mass fraction of NMP in NMP and ethanol mixtures in the absence of solute.

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Table 1 Experimental mole fraction solubility ( x m ,T ) values as the mean of three experiments (± standard deviation) measured for caffeine in the binary mixtures of NMP and ethanol at different temperatures. w1a 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 a

293.2 K 8.56 (±0.73) × 10–4 1.14 (±0.13) × 10–3 1.40 (±0.30) × 10–3 1.76 (±0.05) × 10–3 2.46 (±0.39) × 10–3 3.26 (±0.51) × 10–3 4.29 (±0.73) × 10–3 5.92 (±0.54) × 10–3 7.92 (±0.02) × 10–3 1.04 (±0.07) × 10–2 1.36 (0.14) × 10–2

298.2 K 1.15 (±0.04) × 10–3 1.40 (±0.02) × 10-3 1.73 (±0.10) × 10–3 2.24 (±0.16) × 10–3 2.98 (±0.14) × 10–3 3.90 (±0.21) × 10–3 5.04 (±0.11) × 10–3 6.64 (±0.26) × 10–3 8.74 (±0.32) × 10–3 1.14 (±0.05) × 10–2 1.49 (±0.05) × 10–2

l a

303.2 K 1.36 (±0.07) × 10–3 1.65 (±0.07) × 10–3 2.05 (±0.12) × 10–3 2.63 (±0.15) × 10–3 3.38 (±0.10) × 10–3 4.26 (±0.06) × 10–3 5.65 (±0.28) × 10–3 7.55 (±0.21) × 10–3 9.55 (±0.20) × 10–3 1.32 (±0.02) × 10–2 1.65 (±0.14) × 10–2

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w1 is mass fraction of NMP in the NMP and ethanol mixtures in the absence of caffeine.

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308.2 K 1.63 (±0.05) × 10–3 2.02 (±0.01) × 10–3 2.50 (±0.30) × 10–3 3.05 (±0.10) × 10–3 3.87 (±0.03) × 10–3 4.97 (±0.26) × 10–3 6.49 (±0.26) × 10–3 8.53 (±0.34) × 10–3 1.14 (±0.05) × 10–2 1.44 (±0.10) × 10–2 1.79 (±0.05) × 10–2

313.2 K 1.83 (±0.15) × 10–3 2.23 (±0.13) × 10–3 2.77 (±0.30) × 10–3 3.58 (±0.33) × 10–3 4.46 (±0.41) × 10–3 5.61 (±0.24) × 10–3 7.34 (±0.11) × 10–3 9.40 (±0.42) × 10–3 1.25 (±0.50) × 10–2 1.58 (±0.08) × 10–2 1.90 (±0.13) × 10–2

Journal Pre-proof Table 2 Apparent thermodynamic parameters for dissolution behavior of caffeine in the binary mixtures of NMP and ethanol at Thm. ΔS° (J.K–1.mol–1) 39.58 32.48 35.88 37.96 25.91 21.68 23.79 18.54 20.63 17.45 8.68

TΔS° (kJ.mol–1) 11.99 9.84 10.87 11.50 7.85 6.57 7.21 5.62 6.25 5.29 2.63

H

TS

0.705 0.725 0.709 0.698 0.739 0.755 0.737 0.762 0.741 0.755 0.832

0.295 0.275 0.291 0.302 0.261 0.245 0.263 0.238 0.259 0.245 0.168

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ΔH° (kJ.mol–1) 28.70 26.00 26.49 26.52 22.20 20.29 20.24 17.94 17.89 16.25 13.01

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0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

ΔG° (kJ.mol–1) 16.71 16.16 15.62 15.02 14.35 13.72 13.04 12.33 11.64 10.96 10.38

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and the corresponding MRD% for caffeine in the binary mixtures of

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MRD% 3.6 1.7 1.9 1.8 1.0 1.1 0.5 0.3 1.3 0.7 0.4 1.3

of

B -3452.224 -3127.665 -3186.656 -3190.416 -2670.405 -2439.894 -2434.926 -2158.224 -2151.313 -1954.547 -1564.540

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A 4.761 3.907 4.316 4.565 3.116 2.608 2.861 2.230 2.481 2.098 1.044

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Table 3 The van’t Hoff model parameters NMP and ethanol w1 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 Overall

Journal Pre-proof Table 4

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Calculated ln x values of caffeine obtained by Yalkowsky model in the binary mixtures of NMP and ethanol at different temperatures. ln x w1 293.2 K 298.2 K 303.2 K 308.2 K 313.2 K 0.00 -7.06 -6.77 -6.6 -6.42 -6.3 0.10 -6.79 -6.51 -6.35 -6.18 -6.07 0.20 -6.51 -6.26 -6.1 -5.94 -5.83 0.30 -6.23 -6 -5.85 -5.7 -5.6 0.40 -5.96 -5.75 -5.6 -5.46 -5.37 0.50 -5.68 -5.49 -5.35 -5.22 -5.13 0.60 -5.4 -5.23 -5.1 -4.98 -4.9 0.70 -5.13 -4.98 -4.85 -4.74 -4.66 0.80 -4.85 -4.72 -4.6 -4.5 -4.43 0.90 -4.57 -4.46 -4.35 -4.26 -4.2 1.00 -4.3 -4.21 -4.1 -4.03 -3.96 MRD% 3.3 4.9 5.7 4.4 3.1 Overall MRD% 4.3

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Journal Pre-proof Table 5 Parameters calculated for the Jouyban-Acree, and Jouyban-Acree-van’t Hoff model for caffeine solubility in the binary mixtures of NMP and ethanol.

MRD%

1.6

1.7

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Not statistically significant (p-value >0.05)

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Jouyban-Acree-van’t Hoff A1 1.442 B1 -1682.789 A2 4.737 B2 -3443.157 J0 -83.702 J1 109.048 J2 0a

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Jouyban-Acree J0 -82.394 J1 109.578 J2 64.571

NMP + ethanol

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Journal Pre-proof Table 6 The modified Wilson model parameters at the investigated temperatures and the MRD% for backcalculated caffeine solubility in the binary mixtures of NMP and ethanol. λ12 2.133 0.526 0.582 0.550 0.500

T (K) 293.2 298.2 303.2 308.2 313.2 Overall

λ21 0.646 1.349 1.264 1.326 1.433

MRD% 1.4 0.6 1.1 1.8 1.4

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1.3

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Table 7 The double log-log model constants at investigated temperatures and the MRD% for back-calculated caffeine solubility in the binary mixtures of NMP and ethanol. B

b

for 0
MRD%

for 0
MRD%

0.703 0.806 0.770 0.727 0.754

2.1 3.6 4.3 2.3 4.4 3.3

1.042 1.002 1.076 1.114 1.152

0.9 0.5 1.7 0.9 1.1 1.0

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293.2 298.2 303.2 308.2 313.2 Overall MRD%

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Journal Pre-proof Table 8 The mixture response surface model constants at investigated temperatures and the MRD% for backcalculated caffeine solubility in the binary mixtures of NMP and ethanol. T (K)

β1

293.2 -4.200 298.2 -4.157 303.2 -3.951 308.2 -3.826 313.2 -3.775 Overall MRD%

β3

β4

β5

MRD%

-7.123 -6.952 -6.656 -6.452 -6.352

0a 0.003 0a 0a 0a

0a 0a -0.002 -0.003 -0.003

-0.281 0a -0.558 -0.615 -0.404

2.1 0.8 1.1 1.1 0.9 1.2

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Not statistically significant (p-value >0.05)

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β2

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caffeine saturated solutions in the binary mixtures of NMP and ethanol at 308.2 K 0.784 ± 0.001 0.803 ± 0.001 0.825 ± 0.001 0.847 ± 0.001 0.870 ± 0.001 0.894 ± 0.001 0.918 ± 0.001 0.946 ± 0.003 0.972 ± 0.001 1.001 ± 0.001 1.031 ± 0.001

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303.2 K 0.783 ± 0.001 0.804 ± 0.001 0.828 ± 0.003 0.849 ± 0.001 0.872 ± 0.001 0.896 ± 0.001 0.921 ± 0.001 0.946 ± 0.001 0.974 ± 0.003 1.001 ± 0.003 1.033± 0.001

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298.2 K 0.789 ± 0.001 0.809 ± 0.001 0.832 ± 0.001 0.852 ± 0.001 0.874 ± 0.001 0.899 ± 0.001 0.925 ± 0.001 0.951 ± 0.001 0.978 ± 0.001 1.008 ± 0.001 1.037 ± 0.003

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Table 9 Measured density (g.cm–3) of different temperatures. w1 293.2 K 0.00 0.792 ± 0.001 0.10 0.812 ±0.001 0.20 0.835 ± 0.001 0.30 0.856 ± 0.001 0.40 0.880 ± 0.001 0.50 0.903 ± 0.001 0.60 0.928 ± 0.001 0.70 0.956 ± 0.001 0.80 0.982 ± 0.001 0.90 1.013 ± 0.001 1.00 1.044 ± 0.001

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313.2 K 0.779 ± 0.001 0.801 ± 0.001 0.821 ± 0.005 0.845 ± 0.001 0.868 ± 0.001 0.892 ± 0.001 0.919 ± 0.003 0.942 ± 0.001 0.969 ± 0.001 0.998 ± 0.003 1.028 ± 0.002

Journal Pre-proof Disclosure statement

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No potential conflict of interest was reported by the authors.

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Journal Pre-proof Highlights

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 

Solubility of caffeine in N-methyl-2-pyrrolidone/ethanol mixtures at different temperatures. Correlation/back-calculation of the solubility data by some cosolvency models. Calculation of thermodynamic parameters by using the van’t Hoff and Gibbs equations.

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