Jānis Ruško

Current work is organised around three connected problems: integrating heterogeneous chemical evidence, developing transparent risk-ranking and monitoring-prioritisation methods, and translating assessments into usable guidance and decisions.

1. Integrated evidence infrastructure

   Integrating monitoring and occurrence data, food-consumption information, toxicological reference values, scientific literature, and predictive toxicology evidence into structured and traceable assessment workflows. AI-assisted extraction from scientific literature is being explored as one method for expanding and structuring occurrence evidence.

2. Risk ranking, uncertainty and monitoring prioritisation

   Developing transparent methods for comparing chemical risks, representing uncertainty, identifying important evidence gaps, and directing limited assessment and monitoring resources.

3. Exposure assessment, risk-benefit analysis and guidance

   Conducting applied exposure, chemical-risk, and risk-benefit assessments, with outputs designed for interpretable conclusions, proportionate guidance, and policy-facing decisions.

The longer-term programme is to improve the interface between chemical evidence and decisions: from fragmented data to traceable prioritisation, interpretable assessments, and usable guidance.

1. Risk prioritisation

   How should limited assessment and monitoring resources be directed toward the most relevant chemical risks?

2. Evidence systems

   How can fragmented occurrence, exposure, and hazard evidence be structured into usable assessment workflows?

3. Assessment and guidance

   How can exposure data be translated into robust, interpretable conclusions and proportionate guidance?

4. Automation and data methods

   Where can automation, AI-assisted extraction, and modern data methods improve the quality and efficiency of risk assessment?