Supercritical carbon dioxide utilization in drug delivery: Experimental study and modeling of paracetamol solubility

based on mole fraction. The obtained experimental solubility data revealed the direct effect of pressure on the paracetamol experimental data, while the temperature has a dual effect of both increasing and decreasing effect considering the shifting point known as crossover pressure which was measured to be around 110 bar for paracetamol. Besides, two theoretical approaches were applied to predict the paracetamol experimental results. The experimental data were modeled with two various equations of state (EoSs) i.e. Peng-Robinson EoS and the simplified perturbed chain statistical associating fluid theory (sPC-SAFT) EoS, which their binary interaction parameters were optimized by using genetic algorithm. The obtained results demonstrated the sPC-SAFT EoS predicted the solubility of paracetamol with more accuracy (the average percent deviation was equal to 2.5215), especially at higher pressures. Furthermore, four well-known semi-empirical density-based correlations namely Mendez-Santiago and Teja (MST), Kumar-Johnston (KJ), Bartle et al., and Garlapati and Madras models were applied for modeling the solubility of paracetamol experimental data. According to self-consistency test, KJ model presented more accurate correlative capability with average percent deviation about 4.09%. As a final point, the rapid expansion of supercritical solution process was performed to reduce particle size of paracetamol and mean particle size of paracetamol was calculated based on EoSs and mathematical modeling.

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