At CAAT, we are at the forefront of a paradigm shift in alternatives research. Our work, supported by the generosity of funders such as ARDF, Colgate Palmolive, DoD, European Commission, FDA, NCATS, NIH, and LUSH, challenges the status quo.

Our vision is to move away from current animal-based tests to pathway-based cell assays. Our projects combine 3D organotypic cell models with high-content and high-throughput approaches. This includes metabolomics, proteomics, transcriptomics, miRNA profiling, and imaging techniques. By combining different methods using bioinformatics tools we are aiming to identify pathways of toxicity (PoT) and defense (PoD) and mechanisms of xenobiotics. 

CAAT is at the forefront of research on organoid intelligence (OI). OI involves utilizing brain organoids, which are three-dimensional cultures of human brain cells, to harness the computing power of the human brain. These brain organoids, developed from induced pluripotent stem cells, exhibit spontaneous electrical activity and myelination of axons, making them more efficient than traditional models. By scaling up brain organoids to achieve relevant computational capacities, OI has the potential to revolutionize artificial intelligence (AI) and computational capabilities. It offers opportunities to study human cognitive functions, develop disease models for neurological disorders, and explore chemical safety and drug development. With its transformative potential, OI represents an emerging field that requires interdisciplinary collaboration between engineering, data science, neuroscience, and other domains.

In recent years, we have crafted three novel 3D brain models using rat primary cells, a human dopaminergic cell line, and human induced pluripotent stem cells (iPSCs). These models have spurred groundbreaking applications across diverse areas such as developmental neurotoxicity, neurotoxicity, Parkinson’s disease, resilience, autism, Down’s syndrome, inflammation, and various virus infections, including Zika. Our iPSC model, in particular, has drawn significant media attention, catalyzing an array of collaborations across the globe.

Our NIH-funded endeavor, “Mapping the Human Toxome by Systems Toxicology“, has employed omics technologies to establish a workflow, using endocrine disruption as a case study. Through the integration of data from our multi-omics approach using emerging tools like pathway analysis software and network databases, we are mapping uncharted territories in toxicology.

To harness the potential of the extensive data from our studies and external large toxicology databases like REACH, we’ve pioneered a computational toxicology program. This innovative venture leverages data science to enhance our research findings and predictions. We intend to continue spearheading efforts to improve the scientific rigor of read across, develop better chemical similarity metrics, to combine biological data with chemoinformatics, and develop novel algorithms to classify chemicals. We are collaborating with several teams and plan to make our data and software packages public

The Green Toxicology project seeks to work in tandem with the Green Chemistry movement in developing less toxic products, safer processes, and less waste and exposure. Green Toxicology provides a framework for integrating the principles of toxicology into the enterprise of designing safer chemicals to minimize the potential for toxicity as early in production as possible by leveraging 21st century toxicological tools—including in silico and in vitro—to allow toxicology to help chemists “design out” undesired human health and environmental effects.