Solubility of Tolbutamide and Chlorpropamide in ... - ACS Publications

Article Cite This: J. Chem. Eng. Data XXXX, XXX, XXX−XXX

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Solubility of Tolbutamide and Chlorpropamide in Supercritical Carbon Dioxide Luigi Manna and Mauro Banchero* Dipartimento Scienza Applicata e Tecnologia, Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy S Supporting Information *

ABSTRACT: Tolbutamide and chlorpropamide are oral hypoglycemic drugs that are used to treat diabetic patients. In the context of employing these drugs in green pharmaceutical applications that make use of supercritical fluids, the solubility of tolbutamide and chlorpropamide in supercritical CO2 has been measured at 313.15, 333.15, and 353.15 K and in the pressure range of 10−30 MPa. A semiflow apparatus equipped with a continuous solvent-dilution device of the depressurization line, which avoids the solubility data to be underestimated, was employed. The solubility of tolbutamide is in the range of 1.66 × 10−5 to 40.5 × 10−5 mole fraction while that of chlorpropamide is in the range of 2.29 × 10−6 to 72.2 × 10−6 mole fraction, which indicates that the first drug has higher solubility in the supercritical fluid than the latter, probably due to its higher hydrophobicity. The results were successfully correlated with the most popular empirical and semiempirical models reported in the literature. The Sparks model provided the best correlation for chlorpropamide with an adjusted absolute average percent deviation (AARD%) of 3.5%, while the Keshmiri model provided the best correlation for tolbutamide, with an AARD% of 4.8%. The self-consistency of the experimental data was checked through the Méndez-Santiago and Teja model.

1. INTRODUCTION Tolbutamide (TBD) and chlorpropamide (CPD) are oral hypoglycemic drugs that belong to the first generation of sulphonylureas. They are used to treat diabetic patients since they stimulate the release of insulin from pancreatic β-cells.1,2 TBD and CPD are easily absorbed in the gastrointestinal tract but their bioavailability is limited by their low water solubility; for these reasons, they can be classified as Class II drugs in the Biopharmaceutical Classification System (BCS).3−5 Several strategies can be adopted to enhance the aqueous solubility of this class of drugs such as the preparation of solid dispersions, which consists in the amorphous or molecular dispersion of the drug in a solid inert carrier (generally a biocompatible polymer),6 or the setup of many pharmaceutical particle technologies, which range from conventional mechanical micronization, cryogenic spray processes, crystal engineering up to the complexation with cyclodextrins, and the preparation of polymeric micelles or solid lipid nanoparticles.7 Supercritical carbon dioxide (scCO2) is a green solvent that is successfully employed in many research fields such as the biomedical,8 food,9 and textile10 area. The use of scCO2 to create pharmaceutical particles or prepare solid dispersions of the drug can be a good alternative to conventional processes because it offers many advantages.11,12 First, thanks to its relatively mild critical point (74 bar and 31 °C) it can process thermolabile compounds. If temperature and pressure are varied, then, the solvent power of scCO2 can be easily tuned. This allows particles with different morphologies or size distribution to be obtained by simply adjusting the process conditions.11 Further, pharmaceutical solid dispersions free of © XXXX American Chemical Society

any solvent residue can be obtained since, upon depressurization, the solubilized drug precipitates and is dispersed in the carrier matrix while the CO2 rapidly leaves the system.12 TBD and CPD have already been used in the literature to prepare micronic or submicronic drug particles by means of different techniques that employ scCO2.13−19 All the abovecited research works can be divided into two opposite approaches: in the first one13,15,17,19 the scCO2 acts as a solvent of the drug via the RESS (rapid expansion of supercritical solutions) process20 while in the second14,16,18 it acts as an antisolvent via the GAS (gas antisolvent) or the SAS (supercritical antisolvent).20 In both approaches, the size reduction leads to significant improvement in the dissolution behavior of the poorly water-soluble drug,17,18 which confirms the potentiality of these technologies. The knowledge of accurate and reliable solubility data of drugs in scCO2 at different temperatures and pressures is a key factor in the setup and optimization of the above-cited processes either the supercritical medium is employed as a solvent or an antisolvent. Even though the solubility of many drugs in scCO2 can be found in the literature,21,22 the information for TBD and CPD is practically missing despite the unquestionable interest toward these two drugs. To the authors’ knowledge, some nontabulated solubility data of TBD in scCO2 are displayed in a plot that is reported in a conference paper,23 while no information is available for CPD. Received: January 15, 2018 Accepted: March 2, 2018

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DOI: 10.1021/acs.jced.8b00050 J. Chem. Eng. Data XXXX, XXX, XXX−XXX

Journal of Chemical & Engineering Data

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In this work the solubility of TBD and CPD has been measured at 313.15, 333.15, and 353.15 K and in the pressure range of 10−30 MPa. A semiflow apparatus equipped with a continuous solvent-dilution device of the depressurization line, which avoids the solubility data to be underestimated, was employed.24 The solubility data were fitted with the most popular empirical and semiempirical correlations reported in the literature. The Sparks25 and Keshmiri26 models resulted to be those with the highest correlation performance while the Méndez-Santiago and Teja27 approach allowed the selfconsistency of the experimental data to be checked.

2. EXPERIMENTAL SECTION 2.1. Materials. The characteristics of the materials employed in this work are listed in Table 1. IUPAC names, CAS number, and structures of CPD and TBD are reported in Table 2.

Figure 1. Scheme of the experimental apparatus employed for the solubility tests. P1, CO2 pump; HE, heat exchanger; FM, mass flow meter; SV, saturation vessel; O, oven; P2, auxiliary pump; BPR, backpressure regulator; ST, solvent trap; T and P, temperature and pressure indicators.

Table 1. Sample Description chemical name carbon dioxide CPDa TBDb ethanol a

source Siad S.p.A. (Italy) Sigma-Aldrich Sigma-Aldrich Sigma-Aldrich

initial mole fraction purity 0.99998 >0.97 >0.97 ≥0.998

purification method none none none none

solubility data to be underestimated. Further details as well as the comparison of the measurements with literature data are reported in a previous work.24 An excess amount of drug (1 g) was set inside the 50 ml cylindrical vessel SV (diameter = 14 mm, length = 33 cm). Preliminary tests at different contact times24 pointed out that the flow rate of P1 should be set at 1 g·min−1 and that a transient period of 30 min should elapse to make sure that the saturation of the scCO2 was reached. The flow rate of P2 was set at 2 mL·min−1 to guarantee the correct operation of BPR.24 After the transient period had elapsed a fresh amount of ethanol (10 g) was set in ST. The drug dissolved by the scCO2 and the auxiliary solvent were sampled in ST for 10 min. At the end of the sampling step the final amount of the solution in ST, m1 (g), was determined through an analytical scale while the drug mass fraction, w, was evaluated via an UV spectrophotometer (the maximum wavelengths for CPD and TBD were equal to 276 and 274 nm, respectively). The totalizer implemented in FC allowed the mass of scCO2, m2 (g), which had been flowing through SV and had dissolved the recovered drug, to be determined. The drug solubility, y2, was calculated as the mole fraction of the drug dissolved in scCO2 according to the following equation

Chlorpropamide. bTolbutamide.

Table 2. IUPAC Name, CAS Number, and Structure of the Drugs

2.2. Apparatus and Analysis. The solubility of CPD and TBD was measured with the experimental semiflow apparatus sketched in Figure 1. The supercritical solvent flows at constant pressure and temperature through a saturation vessel (SV) that contains a fixed bed of glass spheres where the solute is dispersed. The scCO2 is then depressurized in an ethanol solvent trap (ST) where the solubilized drug is recovered. The achievement of the appropriate pressure, temperature, and flow rate conditions of the supercritical solvent is obtained thanks to a backpressure regulator (BPR), a heat exchanger (HE), and a pump (P1), respectively. Heating is provided by an oven (O) where both SV and HE are set. A Coriolis-type mass flow meter (FM), which is also equipped with a temperature sensor, provides both the instantaneous CO2 flow rate and the integral mass of solvent flowed during fixed time periods. An auxiliary pump (P2) provides continuous dilution of the depressurization line by pumping an auxiliary solvent (ethanol) that is mixed with the saturated CO2 just before BPR. This device avoids the BPR valve to be clogged by the precipitated solute and guarantees its complete recovery, which avoids the

y2 =

w × m1 Ma w × m1 m + M2 Ma b

(1)

where Ma and Mb are the molecular weights of the drug (CPD or TBD) and the CO2. The same procedure was repeated in triplicate at each experimental condition of temperature and pressure.

3. CORRELATION OF SOLUBILITY DATA Density-based models are the simplest and most popular approach to correlate the experimental solubility data of solids in scCO2. They consist in empirical or semiempirical equations where the solubility of the solid solute (y2) is correlated with the density of the supercritical fluid (ρ) by means of different mathematical relationships, which may also include the B



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equilibrium temperature and pressure, and different number of regression parameters. These models can be divided into two main groups: those where a linear relationship between ln y2 and ln ρ is assumed and those where a linear dependence of ln y2 on ρ is hypothesized. The Chrastil28 and Chrastil-modified25,26,29−37 models belong to the first group, which accounts for the largest number of correlations. The Chrastil model assumes that a solvate complex between solvent and solute molecules is formed at equilibrium and one of its regression parameters is proportional to the sum of the sublimation and solvation enthalpies of the solute. Among the Chrastil-modified approaches, Sparks and co-workers25 proposed two versions of their model, one with five and another one with six regression parameters. Similarly, Garlapati and Madras proposed both a three-regression-parameter33 and a fiveregression-parameter34 model. With respect to most of the other models of this group, which consider any explicit dependence of y2 only on the solvent density and equilibrium temperature, the Jouyban32 and Keshmiri26 models account also for an explicit dependence on the equilibrium pressure of the system. As far as the second group27,38−42 is concerned, only the Kumar and Johnston model38 does not account for an explicit dependence of the solute solubility on pressure. It must also be pointed out that in analogy to the Chrastil model, one of its regression parameters is proportional to the sum of the sublimation and solvation enthalpies of the solute. On the other hand, the Bartle model39 allows the sublimation enthalpy of the solute to be determined whereas the Méndez-Santiago and Teja27 approach allows the self-consistency of the experimental data to be checked. Eventually other correlations that do not belong to the above-cited groups can be found in the literature.43−45 Among these, the Yu43 and Gordillo44 approaches are not density-based models because they do not establish an explicit dependence of the solute solubility on the solvent density. The experimental data of this work were correlated with all the above cited models,25−45 which are among the most popular correlations available in the literature. The models were fitted to the experimental data through nonlinear regression by minimizing the average absolute relative deviation between the calculated and experimental values. The complete list of the model equations is reported in Tables S1 and S2 of Supporting Information as well as the regression parameters and adjusted absolute average percent deviations between experimental and calculated solubility of the two drugs.

Table 3. Experimental and Calculated Solubility of CPD in scCO2a T (K)

P (MPa)

ρ (kg·m−3)

6 yexp 2 × 10

6 ycal 2 × 10 (Sparks)

313.15

10.0 15.0 20.0 25.0 30.0 15.0 20.0 25.0 30.0 15.0 17.5 20.0 25.0 30.0

628.61 780.23 839.81 879.49 909.89 604.09 723.68 786.55 829.71 427.15 523.02 593.89 686.22 745.60

2.36 8.70 13.9 17.8 21.7 5.38 18.1 29.8 38.8 2.29 7.11 17.5 39.1 72.2

2.34 8.91 13.8 17.9 21.5 5.78 17.9 29.7 40.8 2.27 7.63 16.8 41.5 69.4

333.15

353.15

a

Standard uncertainties for temperature, pressure, and solubility are u(T) = 0.1 K, u(P) = 0.1 MPa and u(y) = 0.18 × 10−6, respectively. The density values were obtained from NIST.46

Table 4. Experimental and Calculated Solubility of TBD in scCO2a T (K)

P (MPa)

ρ (kg·m−3)

5 yexp 2 × 10

5 ycal 2 × 10 (Keshmiri)

313.15

10.0 15.0 20.0 25.0 30.0 15.0 20.0 25.0 30.0 15.0 17.5 20.0 25.0 30.0

628.61 780.23 839.81 879.49 909.89 604.09 723.68 786.55 829.71 427.15 523.02 593.89 686.22 745.60

1.66 3.87 5.87 7.46 9.20 4.21 9.66 15.9 20.9 1.80 4.85 10.5 24.3 40.5

1.45 3.99 5.76 7.40 9.07 3.95 10.2 16.2 22.2 1.64 5.09 10.4 24.0 39.8

333.15

353.15

a

Standard uncertainties for temperature, pressure, and solubility are u(T) = 0.1 K, u(P) = 0.1 MPa, and u(y) = 0.06 × 10−5, respectively. The density values were obtained from NIST.46

4. RESULTS AND DISCUSSION 4.1. Experimental Results. Both experimental (yexp 2 ) and calculated (ycal ) solubility values of CPD and TBD in scCO 2 2 at 313.15, 333.15, and 353.15 K and in the pressure range of 10− 30 MPa are reported in Tables 3 and 4, respectively. The ycal 2 values were calculated with the correlations reported in Section 4.2. The density values (ρ) of scCO2 at different temperatures and pressures were obtained from the National Institute of Standards and Technology (NIST) database.46 The TBD solubility data at 313.15 and 333.15 K were compared with those reported by Suzuki and co-workers (Figure 2).23 While the data measured at 313.15 K show a good agreement with those reported by the Japanese research group, the data at 333.15 K are significantly higher. However, a

Figure 2. Solubility of tolbutamide versus pressure at 313.15 and 333.15 K; comparison of data obtained in this work with those reported by Suzuki and co-workers.23

C



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improve the solubility of a solute only under high pressure. When the solubility isotherms are plotted versus the solvent density instead of pressure (Figures 5 and 6), the “crossover point” disappears because the second effect is included in the independent variable.

quantification of the deviation is difficult to perform because the data reported by Suzuki and co-workers were not tabulated but were just displayed in the form of isotherms in a y2 versus P plot, which makes it difficult to accurately evaluate both the solubility data and the experimental pressures. A comparison between the data reported in Tables 3 and 4 points out that TBD is more soluble in scCO2 than CPD. This is related to the different structures of the two drugs (Table 2) and the fact that the solvent power of scCO2 is higher for nonpolar (lipophilic) compounds.47 CPD differs from TBP for the presence of a chlorine atom bonded to the aromatic ring and a shorter aliphatic chain attached to the sulfonamide group (Table 2), which makes CPD less lipophilic than TBD. The effect of temperature and pressure on the solubility of the drugs in scCO2 is shown in Figures 3 and 4. At constant

Figure 5. Solubility of chlorpropamide at different temperatures and solvent densities.

Figure 3. Solubility of chlorpropamide at different temperatures and pressures.

Figure 6. Solubility of tolbutamide at different temperatures and solvent densities.

4.2. Data Correlation. The experimental data of this work were correlated with all the models briefly described in Section 3. The regression parameters and adjusted absolute average percent deviations between experimental and calculated solubility of the two drugs are reported in Tables S1 and S2 of Supporting Information. As it has already been mentioned (Section 3) Chrastil28 and Kumar and Johnston38 models allow the total enthalpy of the solute-solubilization process, which is the sum of the sublimation and solvation enthalpies, to be determined. Because the Bartle39 model can provide the calculation of the sublimation enthalpy, an estimate of the solvation enthalpy can also be obtained. The values of the total, solvating, and sublimation enthalpies of each drug−solute system are reported in Table S3 of Supporting Information. Among all the different tested equations, the Sparks model (version with six parameters)25 and the Keshmiri model26 resulted in the best correlation performances for CPD and TBD, respectively. Both Sparks and Keshmiri models belong to the large class of the Chrastil-modified semiempirical correlations, which are modifications of the original model proposed by Chrastil in 1982.28 The original model proposed by Chrastil had the following expression

Figure 4. Solubility of tolbutamide at different temperatures and pressures.

temperature, the solubility of the drug increases when pressure is increased. This occurs because as the pressure increases the density and, consequently, the solvating power of the fluid increase. The role of temperature is more complex as demonstrated by the presence of the well-known “crossover point”48 that occurs in the range of 17−20 MPa (Figures 3 and 4). In fact, temperature exhibits two competitive effects on the solubility of a solute in a supercritical fluid. On one hand, a temperature increase positively affects the vapor pressure of the solute resulting in solubility enhancement. On the other hand, high temperatures correspond to low densities, which involves a reduction in solubility. Below the “crossover point”, the second effect prevails on the first one while the opposite occurs above, which means that operating at high temperature is beneficial to

⎛ β⎞ y2 = ρα exp⎜β0 + 1 ⎟ ⎝ T⎠ D

(2) DOI: 10.1021/acs.jced.8b00050 J. Chem. Eng. Data XXXX, XXX, XXX−XXX


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Table 5. Regression Parameters, R2adj, and AARD% of the Density-Based Models Used To Fit the Experimental Solubility of CPD and TBD drug CPD TBD

model Sparks Keshmiri

parameters −3

−7

α0 = 2.6065, α1 = 1.654 × 10 , α2 = −7.4219 × 10 , β0 = 7.6313, β1 = −2.0862 × 10 , β2 = 2.3944 × 10 α0 = 12.692, α1 = −2.5352 × 103, β0 = −73.187, β1 = 1.0149 × 104, β2 = 1.7158 × 10−4 4

6

R2adj

AARD%

0.999995 0.999742

3.5% 4.8%

where α is the association number, which is related to the average number of solvent molecules in the complex with the solute, β0 is a function of the association number and molecular weights of the solute and solvent, β1 is a function of the enthalpy of solvation and that of vaporization of the solute. Chrastil-modified semiempirical models have been proposed to overcome the correlation limitations of the original model. In the Sparks model version with six parameters, the association number, α, is assumed to be a density function while an additional dependence of ln y2 on 1/T2 is included ⎛ β β ⎞ 2 y2 = ρ(α0 + α1ρ + α2ρ )exp⎜β0 + 1 + 22 ⎟ ⎝ T T ⎠

(3)

On the other hand, the Keshmiri model hypothesizes that α is a function of temperature and that the solubility is explicitly dependent also on pressure ⎛ ⎞ β y2 = ρ(α0 + α1/ T ) exp⎜β0 + 1 + β2P 2⎟ ⎝ ⎠ T

Figure 7. Experimental and calculated (Sparks model) ln y2 of chlorpropamide versus ln ρ at different temperatures.

(4)

In Tables 3 and 4, the experimental solubility data are compared with those calculated with the best-correlating model for each drug. Table 5 reports for each drug the regression parameters of the best-correlating model as well as the adjusted coefficient of determination (R2adj) and the adjusted absolute average percent deviation (AARD%) between experimental and calculated solubility, which is defined as AARD% =

100 n−z

n

∑ i=1

y2exp − y2cal i i y2exp i

(5)

where n is the number of experimental points and z is the number of parameters of the correlation. Both models produced an accurate fit of the experimental data with values of R2adj almost approaching unity. The Sparks model provided an AARD% of 3.5% for CPD whereas the Keshmiri model resulted in an AARD% of 4.8% for TBD, which demonstrates the reliability of the experimental results. In both cases, the AARD% value is lower than that obtained with the Chrastil model, which is equal to 4.4% and 6.6%, respectively. The improvement of the correlation performances of the Sparks and Keshimiri models with respect to the original Chrastil approach may be related to the hypothesis that the association number depends on the working conditions. However, the choice of the most appropriate dependence of the association number on temperature or solvent density as well as the other additional dependences in the exponential part of eqs 3 and 4 strongly depend on the drug-solvent system under investigation. Eventually, the experimental and calculated solubility values are compared in Figures 7 and 8. Even though the models were fitted to the experimental data through nonlinear regression, the correlation results for CPD and TBD are reported in terms of ln y2 versus ln ρ to point out the linear relationship between the logarithm of solubility and that of solvent density, which is typical of all the Chrastil-modified correlations as reported in Section 3.

Figure 8. Experimental and calculated (Keshmiri model) ln y2 of tolbutamide versus ln ρ at different temperatures.

4.3. Self-Consistency Test. The self-consistency of the experimental data was checked through the Méndez-Santiago and Teja model,27 which can be more conveniently written according to the following equation ⎛ Py ⎞ T ln⎜ 2 ⎟ − α2T = α0 + α1ρ ⎝ Pref ⎠

(6)

The self-consistency test consists in plotting the experimental data according to eq 6 and checking if all isotherms collapse into a single line. This is reported in Figures 9 and 10 for CPD and TBD, respectively. The figures point out that the experimental data of both drugs are satisfactorily consistent.

5. CONCLUSIONS The solubility of CPD and TBD in scCO2 has been determined at 313.15, 333.15, and 353.15 K and in the pressure range of 10−30 MPa. To the authors’ knowledge, this is the first time that the solubility of these two drugs in scCO2 is reported in an accurate tabulated form. The solubility of TBD is in the range of 1.66 × 10−5 to 40.5 × 10−5 mole fraction while that of CPD is in the range of 2.29 E



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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel: +39 011 0904703. ORCID

Mauro Banchero: 0000-0003-1508-3921 Notes

The authors declare no competing financial interest.

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Figure 9. Méndez-Santiago Teja self-consistency test for chlorpropamide.

Figure 10. Méndez-Santiago Teja self-consistency test for tolbutamide.

× 10−6 to 72.2 × 10−6 mole fraction, which indicates that the first drug has higher solubility in the supercritical fluid than the latter, probably due to its higher hydrophobicity. The results were successfully correlated with many empirical and semiempirical models. Among all the investigated equations, the two best-correlating ones were reported. The Sparks model proved to be the best one for CPD with an AARD% of 3.5% while the Keshmiri model provided the best fitting for TBA with an AARD% of 4.8%. Both models belong to the class of Chrastilmodified semiempirical correlations, which points out that the ln y2−ln ρ dependence is the most appropriate type of relationship for the drug-solvent systems and the working conditions here investigated. The low AARD% values obtained here and the positive response to the Méndez-Santiago and Teja self-consistency test confirm the reliability of the experimental results, which are expected to provide an effective tool for process design with scCO2, such as the RESS, GAS or SAS, in the frame of innovative green pharmaceutical applications of CPD and TBD.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jced.8b00050. Tables S1 and S2 reporting all the model equations, regression parameters, and AARD% between experimental and calculated solubility of the two drugs; Table S3 reporting the total (ΔHtot), solvation (ΔHsolv), and sublimation (ΔHsub) enthalpies for the drugs (PDF) F



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