Research infrastructures, in general, decrease the costs of research by concentrating the skills, expertise, and costly infrastructures to provide excellent services. EIRENE specifically aims at developing high-throughput services for multiresidual screening of biomarkers that can replace time-consuming and costly analytical methods looking for 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 policymaking. Better coordination of existing and future cohort studies, including parent-child, adult, occupational, and aging cohorts, is needed to capture exposures throughout the life course. Harmonized sample and data collection methods produce comparable data enabling meta-analyses and comparisons with different statistical approaches. This will improve knowledge and understanding of disease etiology, help to identify factors affecting health and enable better prevention. This will also significantly improve the outcomes of the national and European biomonitoring efforts. The integration of the outcomes of human health-relevant toxicological models and state-of-the-art exposure models will contribute to the identification of major drivers of toxicity to improve prevention and regulatory measures.

Improved data sharing and integration between various human and environmental surveys is another important impact on future infrastructural landscapes, enabling joint interpretation of data across sectors, disciplines, and multiple stakeholders and the development of new prediction models, prevention, and intervention strategies. The outcomes of such efforts will be available to both the scientific community and policymakers to inform evidence-based decision-making for the adequate protection of human health and better healthcare.