Using Machine Learning and in vitro Methods To Assess Human Metabolism of Organophosphates Pesticides and Chemical Warfare Agents
Abstract
We propose to evaluate the metabolism of organophosphate (OP) compounds by human drug metabolizing enzymes using a hybrid computational and in vitro approach. Over the past 20 years, large quantities of in vitro data have accumulated on drug metabolism in humans, which has enabled the building of predictive computational models that can aid in predicting metabolism and drug-drug interactions from a molecular structure. Combined ligand and protein-based methods can help us predict a compound s likely sites of metabolism, rate of metabolism, and the degree of involvement of specific enzymes. Using both computational and in vitro approaches it will be possible to predict the likely metabolites for OPs and generate data to validate the predictions. This will enable us to improve models that can be used for predicting metabolism of OPs.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 01, 2019
- Source ID
- HDTRA11910020
Entities
People
- Sean Ekins
Organizations
- Defense Threat Reduction Agency