Development of phospholipid mixed micelles and predictive models for solubilization of drugs

Low solubility in water is an intrinsic property of many drug candidates due to which a large number of potentially valuable bioactive molecules are dropped from further development as conventional methods of solubilization are inadequate. Traditional means to improve aqueous solubility for parenteral delivery is achieved by co-solvents, surfactants and extreme pH conditions. Dilution of these formulations on administration usually leads to aggregation of the drug in aqueous body fluids. To address this formulation problem, the focus of this study was to develop a safe lipid-based micellar nanosized drug delivery system for such water insoluble drugs. This micellar nanosystem, sterically stabilized mixed micelles (SSMM), is composed of FDA approved biocompatible phospholipids, phosphatidylcholine (PC) and distearoyl phosphatidyl ethanolamine grafted to polyethylene glycol (DSPE-PEG).; The overall goals of this thesis were to develop an optimized phospholipid mixed micellar carrier and generate computational models for rapid screening to predict improvement in aqueous solubility of water insoluble drugs using this lipid based micellar nanosystem. The specific aims of the study were to:{09} (1) Develop an optimized sterically stabilized mixed micellar system (2) Develop predictive models based on quantitative structure property relationship for SSMM solubilization: the hydrophobic effect model and the linear solvation free energy relationship (LSER) model. (3) Validate these models by determining prediction efficiency. Based on characterization studies, the optimized mixed micellar system was selected as DSPE-PEG 2000:PC 90:10 molar%. Hydrophobic effect model and LSER model were developed successfully correlating the octanol water partition coefficient (log P) and solvation factors, respectively to the enhancement in aqueous solubility of the drug on solubilizing in the optimized SSMM. Hydrophobic effect model (log P) described the improvement in aqueous solubility by 90%. The major parameters involved in the LSER model were dipolaritylpolarizability, hydrogen bond basicity and characteristic volume and this model described the solubilization by 95%. These models also predicted the solubilization of water insoluble drugs in SSMM in an accurate manner. This research not only predicts improvement in aqueous drug solubility but also provides a nanocarrier that can potentially target diseased organs, reduce systemic toxicity and increase in vivo stability of the drug.