Module 10 – Predictive Toxicology

This module provides an overview of computational methods to predict the toxicity of chemicals. Students will learn an updated overview of the latest methods that have been successfully applied to predict toxic effects of chemicals, in addition to understanding the outlook towards at the nexus of computational sciences and toxicology. Particular emphasis is placed on carbon-based toxicants. Multiple case studies and in-class discussions and assignments are provided in the lecture slides in addition to an extensive set of homework activities for students to do outside of the classroom. You will additionally gain access to multiple GAMESS activities and problem sets.

What’s included?

• Lectures:
  • “10A – Computational Chemistry in Toxicology” (2-3 hours)
  • “10B – Developing Descriptors by Model Size and Detail Level”
• Lesson Plans:
  • For all lectures
• Supplementary Information:
  • GAMESS tutorials
  • Four homework assignments
  • Installation files
  • Past problem sets
• Supplementary Videos: Recordings of these lectures being used in class. Coming soon!

Keywords: computational chemistry, predictive toxicology, organic chemistry, toxicant effects, modelling, datasets, energy levels, general chemistry.

File Size: 881 MB – this file is very large, please ensure you have good internet connectivity and time for the download to occur before downloading.

Download Lesson

TfC_M10_PredictiveToxicology.zip