Experimental and Computational Methods Pertaining to Drug Solubility

Solubility of a drug is one of its important physico-chemical properties. More attention has been paid to the aqueous solubility since water is the unique solvent of biological systems. It is obvious that a drug should be reached to its receptors in the body through the aqueous and non-aqueous media. The chance of a low water soluble drug to be appeared in the market place is very low and nearly 40 % of the drug candidates fail to reach higher phases of the drug trials simply because of their low water solubility. The solubility in non-aqueous solvents is not too important from clinical viewpoint however these solubilities play curious roles in drug discovery and development investigations. Most of drugs are synthesized in non-aqueous media and/or extracted from natural sources using non-aqueous extracting solvents. Different polymorphs of some drugs could be produced from their crystallization using organic solvents. There are various methods for solubility determination of drugs which is discussed in this chapter. The experimental determination is tedious and time-consuming process and sometimes there is restrictions in the availability of enough amount of a drug candidate to be used in the solubility measurements, especially in the early stages of drug discovery investigations in which only small amount of a drug is synthesized/extracted and large number of preliminary biological tests should be carried out. To cover this limitation, and in order to provide a faster and easier tool, mathematical models have been developed to correlate/predict the solubility of drugs. These models are discussed in this chapter to provide an overall view for a pharmaceutical scientist who is working in the research and development department of a company and/or a research laboratory within academia. In addition to the accurate calculations which are expected from these models, the simplicity of the required computations is another parameter which should be taken into account, since more complex computations did not attract more attention in the pharmaceutical industry.