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Impact of Molecular Partitioning and Partial Equilibration on the Estimation of Diffusion Coefficients from Release
Reza Ghanbari1, Salvatore Assenza1, Patrick Zueblin1
1Food and Soft Materials Science, Department of Health Science & Technology, Institute of Food, Nutrition & Health , ETH Zurich , Schmelzbergstrasse 9 , CH-8092 Zurich , Switzerland.
Abstract:
The present work addresses the effect of partial equilibration and molecular partitioning on the interpretation of release experiments. In this regard, it is shown how release profiles and the values of extracted transport parameters are affected by the time protocol chosen for sample collection by considering a series of experiments where the latter is systematically varied. Caffeine is investigated as a main model drug because of its similar affinity for water and lipids, while monolinolein-based lipid cubic phases are chosen as host matrices because of their wide employment in release studies. Our findings point to a progressive decline in diffusion rate upon increasing the time step, that is, the gap in time between two consecutive pickups, which is a signature of increasing equilibration of caffeine concentration between the lipidic mesophase and the water phase. Furthermore, the amount of released molecules at the first pickup displays negligible changes for large time steps, indicating complete equilibration in such cases. A model is introduced based on Fick's diffusion which goes beyond the assumption of perfect-sink conditions, a common feature of the typical theoretical approaches hitherto developed. The model is shown to account quantitatively for the experimental data and is subsequently employed to clarify the interplay of the adopted release protocol with the various transport parameters in determining the final outcome of the release process. Particularly, two additional molecular drugs are considered, namely glucose and proflavine, which are, respectively, more hydrophilic and hydrophobic than caffeine, thus allowing elucidating the role of molecular partitioning.
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