Lhasa Limited shared knowledge shared progress



20 September 2019

Webinar - An introduction to in silico toxicology

Webinar 2

The first joint webinar from the Computational Toxicology Speciality Section (CTSS) from the Society of Toxicology has been confirmed. Scheduled to take place at 11am EST, this webinar will be co-presented by Lhasa Principal Scientist, Donna Macmillan.


Abstract: In silico toxicology has a number of unique benefits compared to in vivo or in vitro methods: it is fast to run, it does not require any test material, and often provides an understanding of the structural (and mechanistic) basis for any toxicity prediction. In addition, it has been validated as fit-for-purpose for specific endpoints and there exist protocols and other documentation to support its adoption. As such, it is being successfully used in a variety of situations.

This webinar will outline the process of developing and using in silico methods to predict toxicity. The two commonly used in silico methodologies, expert rule-based (or structural alerts) and statistical-based (or QSAR models), will be described. In silico models are built from existing knowledge or automatically derived from training sets of historical toxicity data. The construction of these models will be described as well as how these models could be used to make a prediction and support an expert review. A series of case studies will be used to illustrate this process using first principles and commercial software.

• Introduction to different methodologies
• Expert rule-based methodologies
• Statistical-based methodologies
• Predicting toxicity
• Expert review

Registration is now open:

  • Headline Event (shown first above featured)

  • Featured Event

Back to events

© 2020 Lhasa Limited | Registered office: Granary Wharf House, 2 Canal Wharf, Leeds, LS11 5PS, UK Tel: +44 (0)113 394 6020
VAT number 396 8737 77 | Lhasa Limited is registered as a charity (290866)| Company Registration Number 01765239 (England and Wales).

Thanks to QuestionPro's generosity, we now have survey software that powers our data intelligence.