Predicting pH-Dependent Solubility Enhancement and Precipitation Suppression in Drug-Cyclodextrin-Arginine...

Area of Science:

• Pharmaceutical Science
• Physical Chemistry
• Computational Chemistry

Background:

• Cyclodextrin-based ternary systems enhance solubility of poorly soluble drugs.
• Amino acids like L-arginine can further improve drug solubility and reduce precipitation.
• Drug ionization, complexation, and interactions influence solubility enhancement.

Purpose of the Study:

• Develop a physicochemical model for pH-dependent solubility and precipitation in drug-cyclodextrin-L-arginine systems.
• Analyze multicomponent interactions and solid-liquid equilibria.
• Predict formulation performance based on pH and excipient composition.

Main Methods:

• Unified mass-balance treatment combining acid-base equilibria, inclusion complexation, and solid-phase partitioning.
• Application to ternary systems with repaglinide, sulfadiazine, cefixime, and meloxicam.
• Model validation using published phase-solubility data for repaglinide-HPβCD-L-arginine.

Main Results:

• Model accurately predicted solubility and precipitation behavior for the repaglinide system.
• Enhanced solubilization and reduced precipitation observed within specific pH regions.
• Calculations for cefixime and meloxicam served as predictive applications.

Conclusions:

• pH and multicomponent interactions are critical for formulation performance in cyclodextrin systems.
• Specific pH ranges are necessary for optimal drug solubilization and precipitation reduction.
• Model can aid in preliminary optimization of formulation pH and excipient composition.