- Methods Avoided the Use of Between 115,000-150,000 Test Animals, with Associated Savings of $50-70 Million [US]
- Paper Authored by ACI Scientists
Research methods that used innovative non-animal techniques for filling hazard data gaps for 261 high production volume chemicals eliminated the need for over 1200 animal tests that would have sacrificed 115,000 to 150,000 animals, according to a newly published study.
A paper now available in the journal Regulatory Toxicology and Pharmacology describes how these non-animal methods employed within voluntary chemical programs helped avoid the use of animals for testing. The research also showed between $50 million and $70 million [US] in associated testing costs were avoided.
The paper, authored by scientists at the American Cleaning Institute, utilized techniques known as “read-across” and “in silico.”
Read-across is a well-established, scientifically-justified method of filling data gaps where data of one or more chemicals are used to predict the same outcome for a structurally similar chemical where there is predictability in physicochemical properties, environmental fate, or toxicological and ecotoxicological properties. In silico techniques include the use of computer models to predict, in this case, hazard characteristics.
The chemical assessments were performed under two voluntary high production volume chemical (chemicals produced or imported in volumes of over one million pounds per year) programs: the Environmental Protection Agency’s HPV Challenge program and the International Council of Chemical Associations HPV Chemical Initiative.
“ACI and the industry demonstrated its adherence to the principles of the 3Rs for the more ethical use of animals – replacement, reduction and refinement – in creating and making publicly available hazard datasets for 261 chemicals,” said lead author Kathleen Stanton, ACI Director, Technical & Regulatory Affairs. “By grouping chemicals into structurally similar, scientifically-justified categories, we were able to use well-researched substances to supplement data for similar substances with less data.”
Significant savings were also realized by using modeled data to fulfill physical-chemical data requirements.
“It is estimated that 3.7 million dollars were saved through the use of computer models to fill gaps in chemical data sets, such as for melting and boiling points,” according to co-author Dr. Francis Kruszewski, ACI Senior Director, Human Health & Safety.
“To our knowledge, this is the first study to quantify actual benefits using read-across and other non-animal testing techniques to fill data gaps for structurally similar substances for hazard assessment,” added Stanton.
“We hope the realized benefits in using these approaches resonate with regulators and industry safety experts whose job it is to assess the necessity for animal testing in situations where scientifically justified chemical categories exist. Hopefully, this will allow for reliable read-across to be performed, and non-animal testing methods can be used to predict hazard endpoints.”
The paper, “Quantifying the benefits of using read-across and in silico techniques to fulfill hazard data requirements for chemical categories,” is available online at http://www.sciencedirect.com/science/article/pii/S0273230016302525.