Abstract
The “cure” for the ever rising cost of in vitro ADME screening performed to support drug discovery may be readily at hand. Rationally putting into practice and real use existing in silico technology based on available ADME data can reduce costs in terms of volume of ADME screening and in some cases compound generation (potential compounds predicted to have poor attributes would not be synthesized). It is clear that in order for an in silico model to be successful; its development must require not only reliable and relevant data input, but also clarity and realistic expectations of its output. This work focuses on the development and application of an in silico passive apparent permeability (Papp) model, created with a specific purpose and end user in mind (i.e., medicinal chemist & pharmacokineticist working in early drug discovery). In addition, this work describes how this in silico model can be used in combination with experimental permeability screens such as PAMPA (Parallel Artificial Membrane Permeability Assay) & MDCK (Madin Darby Canine Kidney) cells to further guide drug discovery while enabling a resource sparing approach.
Keywords: ADME, Permeability, In silico, Caco-2, MDCK, Pampa, Computational
7