Computational prediction of drug solubility in water-based systems: Qualitative and quantitative approaches used in the current drug discovery and development setting

Int J Pharm. 2018 Apr 5;540(1-2):185-193. doi: 10.1016/j.ijpharm.2018.01.044. Epub 2018 Feb 6.

Abstract

In this review we will discuss recent advances in computational prediction of solubility in water-based solvents. Our focus is set on recent advances in predictions of biorelevant solubility in media mimicking the human intestinal fluids and on new methods to predict the thermodynamic cycle rather than prediction of solubility in pure water through quantitative structure property relationships (QSPR). While the literature is rich in QSPR models for both solubility and melting point, a physicochemical property strongly linked to the solubility, recent advances in the modelling of these properties make use of theory and computational simulations to better predict these properties or processes involved therein (e.g. solid state crystal lattice packing, dissociation of molecules from the lattice and solvation). This review serves to provide an update on these new approaches and how they can be used to more accurately predict solubility, and also importantly, inform us on molecular interactions and processes occurring during drug dissolution and solubilisation.

Keywords: Computational prediction; Intestinal fluid; Molecular dynamics simulations; Quantitative structure property relationships; Solid state; Solubility.

Publication types

  • Review

MeSH terms

  • Drug Compounding
  • Drug Discovery / methods*
  • Drug Liberation
  • Models, Chemical
  • Molecular Dynamics Simulation*
  • Molecular Structure
  • Pharmaceutical Preparations / chemistry*
  • Quantitative Structure-Activity Relationship
  • Solubility
  • Solvents / chemistry*
  • Technology, Pharmaceutical / methods*
  • Thermodynamics
  • Water / chemistry*

Substances

  • Pharmaceutical Preparations
  • Solvents
  • Water