Will collaborate on three main areas of kidney and liver toxicity and developmental toxicity
Singapore's Agency for Science, Technology and Research (A*STAR) and the US Environmental Protection Agency (EPA) are working together to develop new approaches to identify chemicals that could pose a risk to human health.
For almost a century, chemical safety testing has been performed mainly on laboratory animals. However, there is growing scientific agreement that animal testing, besides being costly and time consuming, may result in poor prediction of human toxicity due to inter-species differences.
Furthermore, animal testing for cosmetics products and ingredients has been banned in regions such as the European Union (EU) owing to ethical concerns.
The partners say it could be valuable for companies in the chemicals and pharmaceutical industries to develop innovative methods for assessing large numbers of chemicals, and their effects on human health, more accurately and efficiently.
If we can identify reliably and efficiently specific chemicals that pose a risk to human health, this should enable industry to predict the safety of their products in development
Scientists from A*STAR's Institute of Bioengineering and Nanotechnology (IBN), Bioinformatics Institute (BII), and Singapore Immunology Network (SIgN), and researchers from the EPA's National Centre for Computational Toxicology will collaborate on three areas of research: kidney toxicity; liver toxicity and developmental toxicity.
The kidney toxicity project will use predictive kidney technologies developed by IBN and BII to predict the effects of environmental toxicants on the human kidney efficiently and accurately. Their innovative technologies include stem cell-based models and a powerful high-throughput platform.
The liver toxicity project will use 3D liver models developed at IBN and computational tools at the NCCT to identify novel predictive biomarkers of human liver toxicity to overcome limitations in existing 2D model tests, which limit their sensitivity, especially over extended periods. Machine learning approaches will be used to analyse and improve existing predictive models of acute and sub-acute liver toxicity.
The developmental toxicity project aims to investigate the potential of certain chemicals to disrupt the development of blood vessels and the blood-brain-barrier during prenatal development.
Dr Kenneth Lee, Senior Director of A*STAR's Biomedical Research Council (BMRC) said: 'Chemicals are essential to modern life. If we can identify reliably and efficiently specific chemicals that pose a risk to human health, this should enable industry to predict the safety of their products in development, and ultimately benefit consumers and society.'
Dr Russell Thomas, Director of the EPA National Centre for Computational Toxicology, added: 'We are excited to combine our computational and toxicological expertise with the world-class biomedical research capabilities of A*STAR. Through this collaboration, we hope to develop more efficient and economical ways to evaluate the potential health effects of chemicals that can be used by both industry and governmental agencies.'
In all of the projects, A*STAR will draw on its multidisciplinary capabilities in stem cell research and tissue models, genomics, high throughput bioimaging, and computational sciences. The collaboration will build on EPA's ToxCast programme which has generated high-throughput screening data on more than 1,800 chemicals.