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Beyond Profiling: Using ADMET Models to Guide Decisions by Matthew Segall; Edmund Champness; Olga Obrezanova; Chris Leeding is a Agricultural and Biological Sciences article available to read on EtoBox.

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## Abstract ADMET Models, whether __in silico__ or __in vitro__, are commonly used to ‘profile’ molecules, to identify potential liabilities or filter out molecules expected to have undesirable properties. While useful, this is the most basic application of such models. Here, we will show how models may be used to go ‘beyond profiling’ to guide key decisions in drug discovery. For example, selection of chemical series to focus resources with confidence or design of improved molecules targeting structural modifications to improve key properties. To prioritise molecules and chemical series, the success criteria for properties and their relative importance to a project's objective must be defined. Data from models (experimental or predicted) may then be used to assess each molecule's balance of properties against those requirements. However, to make decisions with confidence, the uncertainties in all of the data must also be considered. __In silico__ models encode information regarding the relationship between molecular structure and properties. This is used to predict the property value of a novel molecule. However, further interpretation can yield information on the contributions of

Who reads Beyond Profiling: Using ADMET Models to Guide Decisions?

Author

Matthew Segall; Edmund Champness; Olga Obrezanova; Chris Leeding

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); Wiley-Blackwell; Wiley (ISSN 1612-1872)

Published

2009

Language

EN

Field

Agricultural and Biological Sciences (Life Sciences)