Innovation in New Approach Methodologies at the 2024 Society of Toxicology Meeting

By Breanne Kincaid | April 18th, 2024 

Last month, I enjoyed the opportunity to attend the Society of Toxicology (SOT) conference in Salt Lake City, Utah. It was clear that New Approach Methodologies (NAMs) are taking a central role in the future of safer chemical and product development. Experts across academia, government, and private industry discussed their latest research and insights, revealing common themes and highlighting exciting developments which underscore the transformative potential of NAMs in reshaping toxicological assessments.

One new, cutting-edge application involves looking at RNA from individual cells in a tissue, and using it to identify tissue structures and predict chemical-induced changes happening to them.  While most people are familiar with DNA, the study of RNA in vitro is more recent.  This field of research is known as transcriptomics.  These RNA changes – called transcriptomic signatures – can help scientists better assess whether small changes might lead to disease or injury.  These small single-cell changes are often not picked up when larger tissue samples are evaluated in bulk. This application has the potential to be incorporated into organoid and tissue models that are currently being used. 

Within the computational toxicology perspective, machine learning (ML) emerged as a central theme in many presentations, offering a powerful tool for predictive modeling and data analysis. From predicting plasma half-life of drugs to imputing in vitro assay results, ML algorithms were showcased as versatile tools for streamlining drug development processes and elucidating complex biological mechanisms. One promising application was the use of deep learning quantitative structure activity relationship (QSAR) models to predict mechanisms of carcinogenicity from in vitro assay data and chemical structures across diverse data sources. Carcinogenicity can occur through numerous mechanisms, and in many cases involve codependency across mechanisms and molecular targets, which creates a challenge in predicting structure-based toxicity outcomes.

With diverse methodologies across in vitro and in silico applications, a common question emerged: how will these technologies be used to inform regulatory decision making? With more than 20 established frameworks for safe chemical alternatives assessments spanning across different industries, and no federal consensus on what alternative tests may be used to inform specific data needs, it is clear that a critical next step in NAM adoption must be harmonization.

As we navigate the complexities of modern toxicology, NAMs are paving the way for more efficient, ethical, and scientifically robust approaches to chemical safety assessment. By harnessing the power of technology, fostering collaboration, and prioritizing regulatory acceptance, we can chart a course towards a safer, more sustainable future.

The views expressed do not necessarily reflect the official policy or position of Johns Hopkins University or Johns Hopkins Bloomberg School of Public Health.