Computational Prediction of Drug Solubility in Lipid Based Formulation Excipients

Purpose To investigate if drug solubility in pharmaceutical excipients used in lipid based formulations (LBFs) can be predicted from physicochemical properties.

Methods Solubility was measured for 30 structurally diverse drug molecules in soybean oil (SBO, long-chain triglyceride; TGLC), Captex355 (medium-chain triglyceride; TGMC), polysorbate 80 (PS80; surfactant) and PEG400 co-solvent and used as responses during PLS model development. Melting point and calculated molecular descriptors were used as variables and the PLS models were validated with test sets and permutation tests.

Results Solvation capacity of SBO and Captex355 was equal on a mol per mol scale (R2=0.98). A strong correlation was also found between PS80 and PEG400 (R2=0.85), identifying the significant

contribution of the ethoxylation for the solvation capacity of PS80. In silico models based on calculated descriptors were successfully developed for drug solubility in SBO (R2=0.81, Q2=0.76) and Captex 355 (R2=0.84, Q2=0.80). However, solubility in PS80 and PEG400 were not possible to quantitatively predict from molecular structure.

Conclusion Solubility measured in one excipient can be used to predict solubility in another, herein exemplified with TGMC versus TGLC, and PS80 versus PEG400. We also show, for the first time, that solubility in TGMC and TGLC can be predicted from rapidly calculated molecular descriptors.