Objective: The objective of the study is to optimize the solubility of a drug or a drug-like molecule using Aspen Plus simulation platform. Aspirin (solute) was taken as the second case study. The following solvents were used in our dry (virtual) laboratory experiment: Water, acetone, ethanol, and ethylene-glycol-mono-propyl-ether (PROPGLYC).
Methods: A simplified process flow sheet made of a single mixing tank where it has five feed streams, representing the solute, the water, and the set of three organic solvents, and one product stream where aspirin is either solubilized (liquid solution) or remains as solid crystal. Minimization of the molar Gibbs free energy of mixing, ΔGmix, was used as an objective function from an optimization point of view. The Non-random Two-liquid property method was used to analyze the solution properties.
Results: Using the molar Gibbs free energy of mixing, ΔGmix, as a criterion of solution thermodynamic stability, it was found that the most stable solution is the quinary mixture made of 24.42% aspirin, 10.22% water, 21.08% acetone, 19.51% ethanol, and 24.77 mole % PROPGLYC.
Conclusions: Exploiting Aspen Plus can be extended to handle the solubility of a new drug-like molecule once it is defined within its molecular editor with a little knowledge such as density and/or melting point.