Solubility of Bosentan in Polyethylene Glycol 400 + Water Mixtures: Experimental and Mathematical Computations

Author:

Jafari Parisa12ORCID,Rahimpour Elahahe13,Jouyban Abolghasem14ORCID

Affiliation:

1. Pharmaceutical Analysis Research Center and Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran.

2. Drug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.

3. Food and Drug Safety Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.

4. Faculty of Pharmacy, Near East University, PO BOX: 99138 Nicosia, North Cyprus, Mersin 10, Turkey.

Abstract

Background: To discover the optimal solvent amounts for using in a particular application, it is vital to achieve some useful information in regard with suitable neat or mixed solvent and drugs equilibrium solubility in them. It is known that the low solubility of drugs such as bosentan (BST) in water negatively effects in vitro and in vivo kinetics of dissolution, affecting in turn its bioavailability along with making several difficulties around designing its liquid formulations. Methods: Solubility of BST in some mixtures of polyethylene glycol 400 (PEG 400) and water was experimentally determined at T = (293.15 to 313.15) K by using a common shake-flask technique followed by UV-visible spectroscopic method. The experimental solubility data in PEG 400 mass fraction (w1) of 0.0 to 1.0 at 298.15 K and in w1=0.0, 0.5 and 1.0 at other temperatures were then correlated by cosolvency models including the Jouyban-Acree, the Jouyban-Acree-van’t Hoff, and the double log-log models and some un-measured solubility data were predicted based on the obtained trained models. Results: The results presented that the aqueous solubility of BST is increased by increasing mass fraction of PEG 400 as well as increasing temperature and reached the maximum value in neat PEG 400 at 313.15 K. Conclusion: The BST solubility in water improved by addition of PEG 400 into it. According to the average relative deviations obtained from the back-computed data with trained models which were < 8.0%, it concluded that the selected models were able to predict the un-measured data with high reliability.

Publisher

Maad Rayan Publishing Company

Subject

General Pharmacology, Toxicology and Pharmaceutics,Pharmaceutical Science

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