Date of Award


Document Type


Degree Name

Master of Science (M.S.)


Pharmaceutical and Chemical Sciences

First Advisor

Bhaskara Jasti

First Committee Member

Raju Gadiraju

Second Committee Member

Xiaoling Li


Solubility of active pharmaceutical agents is a crucial process that determines drug absorption and ultimately its bioavailability. Many of the new therapeutically beneficial compounds discovered are lipophilic requiring various solubility enhancement strategies to improve their solubility. Among these strategies, solubility enhancement using solid dispersions is a leading method. To obtain a desirable increase in the solubility of a poorly-soluble compound, a good understanding of the molecular descriptors influencing the enhancement of solubility is essential. Therefore, the major research objective was to determine the descriptors which significantly influence the solubility enhancement by solid dispersions. After enhancing the solubility of selected poorly-soluble model compounds, a regression analysis was performed to determine the correlation of molecular descriptors of the active agent, polymer, and solvent with solubility enhancement. The partition co-efficient, hydrogen bonding and solubility parameters of polymer and water were found to influence the aqueous solubility of the poorly-soluble compounds. Aqueous solubility of a compound had an inverse relation with difference in solubility parameters of polymer and water. Similarly partition coefficient was found to be inversely related to aqueous solubility. However for an increase in hydrogen bond acceptors present in pharmaceutical agents increased their solubility, while the higher number hydrogen bond donors resulted in lower solubility. This complexity can be attributed to the contribution of hydrogen bonding in a crystal lattice and in aqueous environment. In conclusion, the contribution of partition co-efficient, solubility parameter and hydrogen bonding were found to be significant for a given set of poorly-soluble model compounds selected with a wide range of descriptors. Several models estimating aqueous solubility of compounds have been employed as screening tool in drug development process. However, all such models were developed to estimate aqueous solubility of pure active agents. Hence, the second research objective was to develop a model that could estimate aqueous solubility of Active Pharmaceutical Ingredient (API) in solubility-enhanced solid dispersions. Using multiple linear regression, a computational model was developed using the molecular descriptors of poorly-soluble compound, polymer and water. S=(2.02*HBA)-(3.37*??)-(11.56*log?P )-(0.9*HBD)+119.66 The model showed a regression (R2) value of 0.858. Upon validation, the model estimated the aqueous solubility of 79% of the compositions evaluated with within 20% variability.







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