While pesticide use is subject to strict regulatory oversight worldwide, it remains a main concern for environmental protection, including biodiversity conservation. This is partly due to the current regulatory approach that relies on separate assessments for each single pesticide, crop use, and non-target organism group at local scales. Such assessments tend to overlook the combined effects of overall pesticide usage at larger spatial scales. Integrative landscape-based approaches are emerging, enabling the consideration of agricultural management, the environmental characteristics, and the combined effects of pesticides applied in a same or in different crops within an area. These developments offer the opportunity to deliver informative risk predictions relevant for different decision contexts including their connection to larger spatial scales and to combine environmental risks of pesticides, with those from other environmental stressors. We discuss the needs, challenges, opportunities and available tools for implementing landscape-based approaches for prospective and retrospective pesticide Environmental Risk Assessments (ERA). A set of "building blocks" that emerged from the discussions have been integrated into a conceptual framework. The framework includes elements to facilitate its implementation, in particular: flexibility to address the needs of relevant users and stakeholders; means to address the inherent complexity of environmental systems; connections to make use of and integrate data derived from monitoring programs; and options for validation and approaches to facilitate future use in a regulatory context. The conceptual model can be applied to existing ERA methodologies, facilitating its comparability, and highlighting interoperability drivers at landscape level. The benefits of landscape-based pesticide ERA extend beyond regulation. Linking and validating risk predictions with relevant environmental impacts under a solid science-based approach will support the setting of protection goals and the formulation of sustainable agricultural strategies. Moreover, landscape ERA offers a communication tool on realistic pesticide impacts in a multistressors environment for stakeholders and citizens.

New Approach Methodologies (NAMs) in Next-Generation Risk Assessment (NGRA), integrating toxicokinetics (TK) with toxicodynamics (TD), provides an accurate evaluation of combined chemical exposures. This study assesses pyrethroids, which pose regulatory challenges due to their widespread use and cumulative exposure risks. A tiered NGRA framework was compared with conventional risk assessment (RA) to evaluate regulatory applicability. In Tier 1, ToxCast data established gene and tissue bioactivity indicators, facilitating hypothesis-driven hazard identification. Tier 2 examined combined risk assessments, rejecting the hypothesis of the same mode of action and highlighting inconsistencies in in vitro data and NOAEL/ADI correlations. Tier 3 applied Margin of Exposure (MoE) analysis and TK modeling to realistic exposure estimations for risk assessment screening based on internal doses, identifying tissue-specific pathways as critical risk drivers. Tier 4 refined bioactivity indicators using TK approaches to improve the NAM-based effect assessment, including an in vitro vs. in vivo comparison, with coherent results based on interstitial concentrations, though intracellular estimations remained uncertain. Tier 5 confirmed that dietary exposure in healthy adults is close to but below levels of concern, with bioactivity MoE values remaining below concern thresholds, and in vivo MoEs within the standard safety factors. Nevertheless, the MoEs are insufficient for addressing the additional non-dietary exposure expected from other pyrethroid uses such as biocides or pharmaceuticals. Results demonstrate that NGRA with TK-NAM-based TD offers a nuanced, regulatory-relevant framework for risk assessment. The proposed approach integrates the information on individual pyrethroids using bioactivity indicators; and the re-assessment of regulatory toxicity studies to select organ-relevant NOAELs allowed an improved in vitro-in vivo comparison, demonstrating the capacity of bioactivity-based MoEs for combined exposure assessments. This tiered approach provides key insights for regulatory decision-making, establishing a robust model for evaluating pyrethroids and similar chemical classes.

A gap between scientific research and regulatory frameworks continues to challenge the effective translation of science into policy and regulation. This commentary explores the disconnection between scientific research, regulatory agencies, and policymakers, highlighting the distinct yet interdependent roles they play. Researchers generate data, which is used by regulatory agencies for risk assessment, and these outcomes serve as the basis for policy development by policymakers. However, misalignments between these key stakeholders hinder effective integration, with consequences for advancing technological development. Additionally, it proposes a set of practical and strategic solutions that span academia, regulatory science, and policymaking to aid the effective integration of science into policy and regulation. Regulatory frameworks that encourage data harmonization, new options for validation, and accessibility are needed. Funding mechanisms that incentivize responsible and relevant research practices are also emphasized. Finally, the importance of open communication and targeted training for researchers and regulators to bridge knowledge gaps and build trust is also discussed. By addressing these issues, this manuscript aims to strengthen the synergy between scientific developments and regulation, advancing evidence-based policymaking. Enhancing robust, reliable and relevant science would improve regulatory decision-making processes, while also guiding researchers on responsible methodologies and setting standards for future research recommendations. The paper advocates for a collaborative approach to enhance the relevance and reliability of published research in guiding evidence-based regulation and policy.

The use of plant protection products (PPPs) remains a major concern for biodiversity, ecosystem integrity, and human health, even under robust regulatory oversight. Current regulatory assessments are often fragmented: they typically examine single substances and single crops in isolation at local or simplified scales. As a result, they struggle to capture the cumulative and combined effects of multiple PPPs and the way exposure propagates and interacts across space and time (fields, crops, and seasons). Our previously proposed landscape-based Environmental Risk Assessment (ERA) framework offered an integrative solution. By jointly representing agricultural practices, environmental characteristics, species movement among habitats, and the combined impacts of multiple PPPs, the current framework delivers predictions that are more adapted to the field reality. These insights are valuable both for regulatory decision-making and for understanding how PPP risks contribute to the overall environmental stress. In this manuscript, we explore the needs, challenges, opportunities, and modelling tools for implementing a landscape-based ERA in both prospective (ex-ante) and retrospective (ex-post) contexts. Drawing on expert discussions and collaborative initiatives, we propose a conceptual framework with four pillars: (1) flexibility to meet diverse user and stakeholder needs, different decision contexts, and varying data availability; (2) ecological realism, the capacity to represent multiple stressors, cumulative effects, exposure pathways driven by species movement, and recovery dynamics; (3) data integration and transparency, combining monitoring and regulatory datasets for calibration, validation, uncertainty analysis, and reproducibility; and (4) regulatory uptake and interoperability, ensuring compatibility with existing ERA methodologies and producing outputs that can be interpreted and used at the landscape level across jurisdictions and tools. Beyond regulatory compliance, landscape-based ERA is a dynamic and adaptative system that provides a robust scientific basis for setting protection goals, designing targeted risk mitigation measures, shaping sustainable agricultural strategies, and communicating realistic, multi-stressor risk trade-offs to stakeholders and the public.

Human health is continuously challenged by exposure to complex mixtures of chemicals present in food, products, and the environment. Traditional risk assessment (TRA), rooted in mid-20th-century paradigms, relies on deterministic thresholds and animal testing to define safe exposure levels. This approach, while useful for regulatory simplicity, fails to represent real-world variability, mixture effects, and lifelong events, limiting its relevance for public health protection. Here we show that a probabilistic Next-Generation Risk Assessment (NGRA) framework integrating quantitative modelling, mechanistic biology, and New Approach Methodologies (NAMs), can transform toxicological evidence into probability distributions, estimating the likelihood of adverse outcomes under realistic exposure scenarios. Central to this approach are Health Impact Pathways (HIPs), which connect molecular perturbations to population-level health indicators, bridging toxicology and epidemiology. The framework explicitly distinguishes susceptible groups, such as individuals in physiologically sensitive stages like pregnancy, from vulnerable groups, including those with pre-existing diseases or higher exposure burdens, poorly covered in TRA. By covering these groups, probabilistic NGRA enables more inclusive, relevant, and informative evaluations that align with FAIR (Findable, Accessible, Interoperable, Reusable) data principles and minimize animal testing, offering a scientifically grounded framework for improving chemical safety evaluations and public health protection.