Detecting and Evaluating Contaminants of emerging concern: Optimizing Data-driven Exposure characterization

Post Date: July 31, 2026

Expiration Date: July 31, 2028

Background:

Humans are exposed throughout their lives to a wide range of environmental chemicals and biological agents through the air they breathe, the water they drink, the food they consume, and numerous daily activities. While many of these exposures are harmless and others are known health hazards, many chemicals remain poorly characterized, with insufficient data to determine whether they pose risks to human health.

Contaminants of Emerging Concerns (CECs) are a broad range of chemicals (man-made or naturally occurring) and biological agents that are newly identified in the environment or in humans and may adversely affect health.  Potential effects include endocrine disruption, neurotoxicity, immune dysregulation, reproductive and developmental toxicity, and  cancer. Examples of CECs include unregulated contaminants in food and drinking water, pharmaceuticals released through wastewater, compounds released following disasters/spills, and previously unrecognized industrial chemicals and byproducts increasingly detected in the environmental and biological samples. 

Significant knowledge gaps exist for CECs regarding the sources, exposure pathways, levels of exposure, and health effects.  Key challenges include: 

• Limited analytical methods and standardized technologies for detecting and monitoring CECs in the environment and in biological samples. 
• Poor understanding of how CECs are absorbed, metabolized, and interact with biological systems, and contribute to adverse health outcomes. 
• Complex, real-world exposures involving mixtures of contaminants and other environmental or social stressors that may modify toxicity and disease risk. 

These gaps hinder risk assessment and the development of effective prevention and intervention strategies to protect public health.

Purpose:

NIH is interested in research that advances the identification, characterization, and understanding of CECs, including the development of methods to detect CECs in  environmental and biological samples, elucidation of exposure pathways, and characterization of biological and health effects. 

Recent advances in chemical analytical techniques, new approach methodologies (NAMs), and artificial intelligence (AL)/machine learning (ML) present an opportunity to improve CEC detection and prioritization, accelerate hazard identification, and better characterize exposure-health relationships. The long-term goal is to expand our understanding of CECs and how the environment impacts human health across the life span.