A Poster Session, Computational Toxicology and Data Integration II—Enhancing Our Abillity to Screen Hazards and Risks, was held on March 27, 2014 at the Phoenix Convention Center as part of the 53rd Annual Meeting of the Society of Toxicology. A summary of that session is below.
Are you hungry for fast, accurate, and cost-effective tools to assess hazards and risks associated with chemicals? Or perhaps learn whether High Throughput Screens (HTS) systems such as Tox21 can screen a wide variety of biological pathways associated with a disease? Or find out how you can screen for chemical hazards more reliably than a Restricted Substances List (RSL)? Then check out the posters from the Computational Toxicology and Data Integration II session to learn more!
For those of you relying only on RSLs to restrict hazardous chemicals from your products, a poster by Pat Beattie of SciVera (pictured at the left) will convince you to re-think your decision! OECD’s eChemPortal was used to identify 2,138 chemicals with developmental/reproductive (D-R) toxicity data. Of this, a subset of 440 chemicals was evaluated, with 113 chemicals were ranked as high hazard for D-R toxicity. When compared to over 60 RSLs in the Pharos database, their research indicates that more than 46% of chemicals with high D-R hazards were not on any RSL, and greater than 77% of chemicals with high D-R hazards are not only D-R lists reviewed, such as Prop 65 or EU’s SVHC list.
Ruthann Rudel and Janet 
Ackerman (pictured at the right) of the Silent Spring Institute presented results of their investigations of breast cancer-relevant biological pathways screened by the US Environmental Protection Agency ToxCast and US National Toxicology Program Tox21 Hazard Screening Programs, along with their collaborative research with Chris Vulpe from UC-Berkeley, relating to high-content screening of rodent mammary gland carcinogens in two breast cell lines. This research is a critical “reality check” to evaluate whether HTS effectively screens relevant biological pathways for breast cancer. They identified a number of HTS datagaps such as the ability to screen for perturbations in organism-level endocrine effects and affects on mammary gland development.
Chis Barber from Lhasa Ltd.(pictured at the left) in the UK presented his group’s work developing a QSAR tool called Sarah Nexus. Sarah Nexus is statistical software tool to predict mutagenicity, and when coupled with a second QSAR tool can help meet the draft ICH M7 guidelines that specifies the use of two complimentary (Q)SAR methods to predict the outcome of a bacterial mutagenicity assay.