Research infrastructures decrease the costs of research by concentrating skills, expertise, and costly facilities to deliver excellent services. EIRENE specifically aims to develop high-throughput services for multiresidual screening of biomarkers that can replace time-consuming and costly analytical methods targeting specific groups of chemicals. The same applies to innovative AI-driven tools for data processing, effective data mining, and modelling.

EIRENE also offers numerous options to support data-driven decision-making and policy-making. Better coordination of existing and future cohort studies, including parent-child, adult, occupational, and aging cohorts, is needed to capture exposures across the life course. Harmonized sample and data collection methods will generate comparable, data enabling meta-analyses and comparisons using different statistical approaches. This will improve knowledge and understanding of disease etiology, help identify factors affecting health and, enable more effective prevention. it will also significantly enhance the outcomes of national and European biomonitoring efforts. Integrating outputs from human health-relevant toxicological models with state-of-the-art exposure models will contribute to identifying major drivers of toxicity, thereby improving prevention and regulatory measures.

Improved data sharing and integration across human and environmental surveys represents another key impact on future infrastructure landscapes. This will enable joint interpretation of data across sectors, disciplines, and multiple stakeholders, as well as the development of new prediction models, and prevention and intervention strategies. The outcomes of these efforts will be accessible to both the scientific community and policymakers, supporting evidence-based decision-making for effective protection of human health and improved healthcare.