Partition Coefficients of Pharmaceuticals as Functions of Temperature and pH

Abstract

Liquid–liquid extraction is a potential separation process for the purification of active pharmaceutical ingredients (APIs). The design of an extraction step requires knowledge of the API partition coefficient, which strongly depends on the solvent system and process conditions. Usually, cost-intensive experiments have to be performed to select the most suitable solvent system and the best process conditions. The number of experiments can be reduced by predicting the partition coefficient using perturbed chain statistical associating theory (PC-SAFT). In this work, modeling results and experimental data were compared for the partition coefficients of the APIs nicotinamide and salicylamide in different solvent systems at temperatures from 293.15 to 328.15 K and at pH values varying between 5.2 and 10.3. The results show that PC-SAFT is able to predict the API partition coefficients for different solvent systems as functions of temperature and pH.