Big Data Session 6: Dec. 1, 2021

Big Data in Environmental Science and Toxicology is a 2021 seminar series from the Texas A&M Superfund Research Center (heading image with abstract networking graphic and hands on a laptop)
Ruchir Shah
Ruchir Shah
Alex Sedykh
Alex Sedykh
Vijay Gombar
Vijay Gombar
Austin Ross
Austin Ross

Wednesday, Dec. 1, 2021 | 1:00–3:00 p.m. (Central US Time) 
Ruchir Shah, Alex Sedykh, Vijay Gombar, and Austin Ross—Sciome LLC 

Zoom Details: Will be emailed to registrants on the morning of the session

EXPERIMENTS ARE TOO HARD: HOW TO USE ONLINE RESOURCES FOR PREDICTIVE TOXICOLOGY

Only a small fraction of compounds in the commerce (TSCA, US; ECHA, EU; DSL, CA) has been experimentally assayed for toxicity evaluation to support hazard and risk assessment. Given the large number of chemicals that lack experimental toxicity profile, coupled with the cost, time, and animal sacrifice it takes to generate those profiles, NAMs – New Approach Methodologies – are a prudent recourse. Predictive models have been recognized as a first go-to NAM and their importance has been highlighted in all four previous sessions of this series. 

In our workshop, we will discuss some publicly available tools for accessing data and/or predicting various properties relevant to hazard and exposure assessment, namely ICE (Integrated Chemical Environment), OPERA (OPEn (q)saR App), and OrbiTox – a newly designed tool for translational discovery through an interactive, concerted view of multi-domain data and predictive models that provide chemistry-backed reasoning based on our recently published set of structural features, Saagar.

Post about the series on social media and use this hashtag!
#TAMUSuperfundBigData2021