Solubility; still a challenging subject in pharmaceutical sciences

Abolghasem Jouyban
2010 Revista Vitae  
Solubility of a drug/drug candidate is one of the most important required physico-chemical properties in pharmaceutical area and nearly 40% of drug candidates fail to proceed to the higher trial phases of new drug development process because of their poor solubility. The commonly used method is to determine the experimental values of either thermodynamic or kinetic solubility. Numerous efforts were made to develop predictive tools for replacing the time consuming and costly experimental
more » ... The oldest rule in this area is "like dissolves like" which is translated as the Hildebrand solubility approach in which the maximum solubility of a solute is observed when the solubility parameters of the solvent ( 1 ) and solute ( 2 ) are the same or ( 1 -2 ) 2 =0. In 1916, Prof. Joel H. Hildebrand (1881-1983 wrote: "There is scarcely anything more important for a chemist than a knowledge of solubilities, but unfortunately he finds it more difficult to predict how soluble a substance will be in a given solvent than it is to predict almost any other important property." A simple search from databases like Scopus® shows that the first article including "solubility" in its title was published in 1831 and more than 21500 articles were reported during last 179 years, revealing the position of solubility investigations in the scientific community. The Hildebrand solubility approach is applicable only to the solubility of non-polar solutes in non-polar solvents and is not applicable to the pharmaceutical systems. Its extended versions were reported to provide better predictions for pharmaceutical systems including methods based on partial solubility parameters developed by Prof. Alfred N. Martin (1919Martin ( -2003 and his co-workers. The linear solvation energy relationship models proposed by Prof. Michael H. Abraham are the most accurate model to predict the solubility of a solute in monosolvent systems. The Abraham solvent coefficients which derived from experimental solubility data are available for a limited number of solvents, however, they are not available for some pharmaceutically relevant cosolvents like propylene glycol or polyethylene glycols. A trained version of Abraham solvation model was reported to predict the aqueous solubility of drug/drug like molecules using Abraham solute parameters computed by Pharma-Algorithm. The model provides solubility values with relatively high prediction error, however, it possesses an advantage of in silico prediction of aqueous solubility of drugs and no experimental data is required as input values. The Abraham model was also applied to other physico-chemical and biological properties of drugs. Another predictive model was developed by Prof. Samuel H. Yalkowsky is the general solubility equation which requires the melting point and logP of the drug as input data. The logP values could be computed using software such as ACD with reasonable accuracy. There is also a number of software which could be used to predict the aqueous solubility of drugs. "Handbook of Aqueous Solubility Data" reports the published data and provides a useful database for developing more accurate quantitative structure property relationships. When aqueous solubility of a drug/drug candidate is low, numerous methods could be used to enhance the solubility including mixing a permissible organic solvent (or cosolvency), using complexing agents such as cyclodextrins, addition of surface active agents etc. Among these methods, the cosolvency is the more common and effective method to increase the solubility of a low soluble drug. Addition of a pharmaceutical cosolvent possibly is associated with side effects, therefore the cosolvent concentration should be kept as low as possible. It also may affect the chemical stability of a drug in the liquid pharmaceutical formulation. In addition to the collected experimental solubility data of drug or drug related compounds in mixed solvents and also non-aqueous organic solvents in "Handbook of Solubility Data for Pharmaceuticals", a number of mathematical models were reported to simulate the solubility data in mixed solvent systems. Prof. Anthony N. Paruta and co-workers correlated the solubility of drugs to the dielectric constant of the mixed solvent system in 1964. The log-linear model of Prof. Yalkowsky was the next model providing a simple equation to calculate the solubility of drugs in water + cosolvent mixtures and the constants of this model were reported for most of pharmaceutically relevant cosolvents.
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