Session 4: Metabolism

Session 4: Metabolism

Session Chair: Carol Marchant (Lhasa Limited, Leeds)

Thursday, 1 October 2015
from 15:30 to 17:00

Speakers Title
Johannes Kirchmair, University of Hamburg Combining measurement and computation for the prediction of xenobiotic metabolism
Matthew Segall, Optibrium Predicting regioselectivity and lability of cytochrome P450 metabolism using quantum mechanical simulations
Carol Marchant, Lhasa Limited A hybrid expert system-machine learning approach to xenobiotic metabolite ranking
Session 4 Summary

The prediction of xenobiotic metabolites is of great importance across many chemical sectors and in silico systems play a key role across many industries and disciplines – including ‘where are the key sites of metabolism?’, ‘what are the likely metabolites (and will they be toxic)?’, ‘what metabolite may have been formed?’ and ‘can I expect my test system to produce relevant metabolites?’

Metabolite prediction is still an area that is being actively researched and in this session will cover a range of methodologies. These range from quantum mechanically–based, to machine-learnt (statistical) through to an approach centred around an expert rule-base and between then all, will provide an insight into the progress and potential that each of these approaches can offer.