| Literature DB >> 33071399 |
Mahboubeh Pishnamazi1,2, Saber Hosseini3, Samyar Zabihi4, Fatemeh Borousan5,6,7, Ali Zeinolabedini Hezave6,7, Azam Marjani8,9, Saeed Shirazian10,11.
Abstract
Unfortunately, malaria still remains a major problem in tropical areas, and it takes thousands of lives each year and causes millions of infected cases. Besides, on December 2019, a new virus known as coronavirus appeared, that its rapid prevalence caused the World Health Organization (WHO) to consider it a pandemic. As a potential drug for controlling or treating these two undesired diseases at the cellular level, chloroquine and its derivatives are being investigated, although they possess side effects, which must be reduced for effective and safe treatments. With respect to the importance of this medicine, the current research aimed to calculate the solubility of chloroquine in supercritical carbon dioxide, and evaluated effect of pressure and temperature on the solubility. The pressure varied between 120 and 400 bar, and temperatures between 308 and 338 K were set for the measurements. The experimental results revealed that the solubility of chloroquine lies between 1.64 × 10-5 to 8.92 × 10-4 (mole fraction) with different functionality to temperature and pressure. Although the solubility was indicated to be strong function of pressure and temperature, the effect of temperature was more profound and complicated. A crossover pressure point was found in the solubility measurements, which indicated similar behaviour to an inflection point. For the pressures higher than the crossover point, the temperature indicated direct effect on the solubility of chloroquine. On the other hand, for pressures less than the crossover point, temperature enhancement led to a reduction in the solubility of chloroquine. Moreover, the obtained solubility results were correlated via semi-empirical density-based thermodynamic correlations. Five correlations were studied including: Kumar & Johnston, Mendez-Santiago-Teja, Chrastil, Bartle et al., and Garlapati & Madras. The best performance was obtained for Mendez-Santiago-Teja's correlation in terms of average absolute relative deviation percent (12.0%), while the other examined models showed almost the same performance for prediction of chloroquine solubility.Entities:
Keywords: Chloroquine; Crossover pressure; Pharmaceuticals; Solubility; Thermodynamics
Year: 2020 PMID: 33071399 PMCID: PMC7550982 DOI: 10.1016/j.molliq.2020.114539
Source DB: PubMed Journal: J Mol Liq ISSN: 0167-7322 Impact factor: 6.165
Fig. 1Malaria distribution worldwide [1].
Fig. 2Chemical structure of chloroquine [5].
Fig. 3The schematics of used machine for the solubility measurements [16].
Fig. 4Solubility of chloroquine as function of T & P.
Chloroquine solubility at different temperatures and pressures.a
| P/bar | T/K | |||||||
|---|---|---|---|---|---|---|---|---|
| 308 | 318 | 328 | 338 | |||||
| y | SD | y | SD | y | SD | y | SD | |
| 120 | 8.26 × 10−5 | 6.72 × 10−6 | 4.26 × 10−5 | 3.09 × 10−6 | 4.04 × 10−5 | 3.06 × 10−6 | 1.64 × 10−5 | 1.06 × 10−6 |
| 160 | 1.33 × 10−4 | 1.06 × 10−5 | 1.13 × 10−4 | 3.93 × 10−6 | 7.35 × 10−5 | 3.40 × 10−6 | 5.96 × 10−5 | 2.90 × 10−6 |
| 200 | 1.53 × 10−4 | 5.17 × 10−6 | 1.76 × 10−4 | 4.73 × 10−6 | 1.95 × 10−4 | 1.27 × 10−5 | 2.22 × 10−4 | 1.30 × 10−5 |
| 240 | 2.11 × 10−4 | 9.32 × 10−6 | 2.26 × 10−4 | 1.34 × 10−5 | 2.33 × 10−4 | 1.44 × 10−5 | 2.59 × 10−4 | 2.20 × 10−5 |
| 280 | 2.50 × 10−4 | 1.03 × 10−5 | 3.05 × 10−4 | 4.35 × 10−6 | 3.45 × 10−4 | 1.24 × 10−5 | 3.87 × 10−4 | 2.73 × 10−5 |
| 320 | 2.95 × 10−4 | 1.92 × 10−5 | 3.78 × 10−4 | 1.72 × 10−5 | 4.40 × 10−4 | 1.84 × 10−5 | 5.02 × 10−4 | 3.57 × 10−5 |
| 360 | 3.28 × 10−4 | 1.04 × 10−5 | 4.12 × 10−4 | 1.54 × 10−5 | 5.21 × 10−4 | 1.35 × 10−5 | 6.04 × 10−4 | 4.59 × 10−5 |
| 400 | 3.74 × 10−4 | 2.65 × 10−5 | 4.55 × 10−4 | 2.13 × 10−5 | 6.76 × 10−4 | 4.62 × 10−5 | 8.92 × 10−4 | 2.27 × 10−5 |
Standard uncertainty, u, are u (T) = 0.1 K and u (P) = 0.35 bar.
Fig. 5Effect of temperature on solubility of chloroquine.
Fitting parameters of the semi-empirical correlations.
| Model | AARD % |
|---|---|
| Bartle et al. | 13.0 |
| Mendez-Santiago-Teja | 12.0 |
| Kumar and Johnstone | 12.3 |
| Chrastil | 13.3 |
| Garlapati and Madras | 13.6 |
AARD % = 100 × ∑ ((ycalc − yexp.) / yexp.).
Fig. 6Chloroquine solubility results based on a) Bartle et al. model, b) Chrastil, c) MST and d) KJ model.
Fig. 7Self-consistency results using MST correlation.