The Application of Gaussian Processes in the Prediction of Permeability Across a Polydimethlysiloxane Membrane

Polydimethylsiloxane (PDMS) silicone membranes, such as Silastic^®, have been used widely in place of mammalian tissue in the determination of percutaneous absorption. While many experiments have shown correlations between the permeability across both membranes, Moss et al. demonstrated in a systematic study that PDMS membranes tend to exhibit greater permeability than mammalian skin, and that the relationship between permeability across both membranes was not found when the lipophilicity of the penetrant was greater than 3. Further, it was shown previously that when five commonly used physicochemical descriptors were applied to human, pig and rodent membranes they cannot represent the main characteristics of the PDMS dataset when using Gaussian Process (GP) regression to predict skin permeability. However, the previous study in which this process was modelled employed a small dataset (n=19, as part of the wider aims of that work to investigate the effect of dataset construction on model quality).