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Solubilization by cosolvents. Establishing useful constants for the log-linear model
Jeffrey Millard1, F Alvarez-Núñez, S Yalkowsky
1Department of Pharmacy Practice and Science, College of Pharmacy, The University of Arizona, 1703 E. Mabel St., P.O. Box 210207, Tucson, AZ 85721-0207, USA.
International Journal of Pharmaceutics
|September 25, 2002
Summary
This study developed a log-linear cosolvent model to predict drug solubility in common pharmaceutical solvents like propylene glycol and ethanol. Knowing a compound's hydrophobicity allows accurate solubility predictions, aiding formulation development.
Area of Science:
- Pharmaceutical Science
- Physical Chemistry
- Drug Delivery
Background:
- Accurate prediction of drug solubility is crucial for pharmaceutical formulation.
- Cosolvents are frequently used to enhance drug solubility.
- A quantitative model for cosolvent effects is needed.
Purpose of the Study:
- To develop constants for the log-linear cosolvent model.
- To enable accurate prediction of solubilization in common pharmaceutical cosolvents.
- To establish a predictive tool for drug solubility in propylene glycol, ethanol, polyethylene glycol 400, and glycerin.
Main Methods:
- Determined solubilization power (sigma) for various organic compounds.
- Analyzed log-solubility versus cosolvent volume fraction plots.
- Used linear regression to correlate solubilization power with solute hydrophobicity (logK(ow)).
Main Results:
- Established a nearly linear relationship between solubilization power and solute hydrophobicity for each cosolvent.
- Developed constants for the log-linear cosolvent model.
- Demonstrated that a compound's partition coefficient is sufficient for predicting solubilization.
Conclusions:
- The log-linear cosolvent model provides accurate predictions of drug solubilization.
- The model is applicable to common pharmaceutical cosolvents.
- This predictive capability simplifies and enhances pharmaceutical formulation design.