Abstract
While the regulatory risk assessment of chemicals has largely relied on toxicity data from experimental animals, we are faced with the challenge of finding scientifically robust ways to utilize the available data from a growing number of cell-based or computational methods. As these data streams continue to mature, we need to successfully integrate them into risk assessment. In this context, the National Institute of Health Sciences has conducted the development and validation of in silico methods and Integrated Approaches to Testing and Assessment (IATA). With the support of the MHLW’s Chemicals Risk Research Project, Ames (Q)SAR models have been improved using large, high-quality data sets. Since the discrepancy between in vitro and in vivo genotoxicity studies is often related to metabolism, new models were developed to account for kinetic differences. In addition, mechanism-based categories for repeated-dose toxicity were created to extend the applicability of read-across. Moreover, the Adverse Outcome Pathways were developed to support the assessment of developmental and reproductive toxicity using IATA. Case studies are useful for understanding the strengths and limitations of new approaches and as educational opportunities to enhance the experience of stakeholders. We have shared IATA and (Q)SAR case studies with the OECD projects. In Japan, we have established a working group with industry and regulators to jointly evaluate case studies on read-across for systemic toxicity assessment of quasi-drugs and have been discussing challenges for the regulatory acceptance.
