HOME- Bryn Mawr Conference
- Workshops & Training
- 2010 Oxford (Discovery)
- 2010 Oxford (ADMET)
- 2009 Oxford (Discovery)
- 2009 Oxford (ADMET)
- Bassan, A
- Cronin, M
- Hardy, B
- Helma, C
- Hopfinger, T
- Judson, P
- Leahy, D
- Madden, J
- Michielan, L
- Narayanan, D
- Myatt, G
- Obrezanova, O
- Thomas, S
- Zamora, I
- Poster Session
- Bursary Award
- 2008 Oxford
- 2006 Oxford
- Exhibition
- Registration
- Jobs
- Contact
- Support
- Schedule
|
|
|
|
|
|
|
Glenn J. Myatt, Ph.D., is Chief Scientific Officer at Leadscope. Dr. Myatt has worked in this field for over 17 years. He has a B.Sc. in Computing, an M.Sc. in Knowledged Based Systems, and a Ph.D. in Chemoinformatics from the University of Leeds. He has completed several post-doc positions and was one of the founders of Leadscope in 1997, where he has worked in a variety of scientific and business positions. Dr. Myatt has published over 12 articles, has regularly spoken at international meetings, and has written two books.
|
|
Using Database look-ups, Read Across, and Predictive Models to assess the Toxicity of Compounds
Glenn Myatt (Leadscope)
In silico toxicology software programs are becoming increasingly useful throughout all stages of drug discovery, including lead identification, lead optimization, and preclinical. Tools such as database look-ups, read across, and predictive models can be used to assess the toxicity of compounds. The use of these tools at the various stages of the discovery process will be explored in this workshop. The Leadscope software and databases will be used to provide hands-on experience of these different approaches. The software provides a range of structure and toxicity searching options over a variety of toxicity databases, including data from the US FDA. The software will be used to find information on compounds, to perform read across, and make predictions. Issues concerning data mining toxicity information will be further examined including finding structural alerts, building predictive models, and the use of modeling where the training data can or cannot be examined.
|
|
|
|
|
|
|
|
|
