Toxicology testing plays a key role in ensuring the safety of US Food and Drug Administration (US FDA)-regulated products. As new methods such as mathematical modeling are being developed for toxicity testing, they are producing unique opportunities to enhance our ability to quickly and more accurately predict potential toxicities and reduce associated risks. These breakthroughs could help us move products to market faster while preventing products with increased toxicological risk from ever reaching the market. In some cases, these technologies are reducing the need for animal testing—furthering US FDA’s long-held goal of refining, reducing, and replacing testing on animals.
During the past decade, US FDA scientists have taken major steps to upgrade their toxicology toolboxes. However, US FDA also has recognized the need for a comprehensive strategy to evaluate new methodologies and technologies for their potential to expand the Agency’s toxicology predictive capabilities and to potentially reduce the use of animal testing.
To this end, in early December 2017, US FDA launched its Predictive Toxicology Roadmap, a six-part framework for integrating predictive toxicology methods into safety and risk assessments. The roadmap was developed by senior US FDA toxicologists across the Agency with deep expertise in US FDA’s product areas and knowledge of the differing legal authorities for evaluating safety and toxicity in those product areas.
Among other recommendations, US FDA’s roadmap calls for US FDA research to determine data gaps and to support intramural and extramural research to make sure that the most promising technologies are developed, validated, and integrated into the product pipeline. The roadmap also identifies toxicology issues that need tackling for US FDA-regulated products and toxicology areas that could benefit from improved predictivity.