The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractUncertainty analysis is the process of identifying limitations in scientific knowledge and evaluating their implications for scientific conclusions. It is therefore relevant in all EFSA's scientific assessments and also necessary, to ensure that the assessment conclusions provide reliable information for decisionmaking. The form and extent of uncertainty analysis, and how the conclusions should be reported, vary widely depending on the nature and context of each assessment and the degree of uncertainty that is present. This document provides concise guidance on how to identify which options for uncertainty analysis are appropriate in each assessment, and how to apply them. It is accompanied by a separate, supporting opinion that explains the key concepts and principles behind this Guidance, and describes the methods in more detail.

EFSA requested the Scientific Committee to develop a guidance document on the use of the weight of evidence approach in scientific assessments for use in all areas under EFSA's remit. The guidance document addresses the use of weight of evidence approaches in scientific assessments using both qualitative and quantitative approaches. Several case studies covering the various areas under EFSA's remit are annexed to the guidance document to illustrate the applicability of the proposed approach. Weight of evidence assessment is defined in this guidance as a process in which evidence is integrated to determine the relative support for possible answers to a question. This document considers the weight of evidence assessment as comprising three basic steps: (1) assembling the evidence into lines of evidence of similar type, (2) weighing the evidence, (3) integrating the evidence. The present document identifies reliability, relevance and consistency as three basic considerations for weighing evidence.

The Scientific Committee (SC) reconfirms that the benchmark dose (BMD) approach is a scientifically more advanced method compared to the NOAEL approach for deriving a Reference Point (RP). Most of the modifications made to the SC guidance of 2009 concern the section providing guidance on how to apply the BMD approach. Model averaging is recommended as the preferred method for calculating the BMD confidence interval, while acknowledging that the respective tools are still under development and may not be easily accessible to all. Therefore, selecting or rejecting models is still considered as a suboptimal alternative. The set of default models to be used for BMD analysis has been reviewed, and the Akaike information criterion (AIC) has been introduced instead of the log-likelihood to characterise the goodness of fit of different mathematical models to a dose-response data set. A flowchart has also been inserted in this update to guide the reader step-by-step when performing a BMD analysis, as well as a chapter on the distributional part of dose-response models and a template for reporting a BMD analysis in a complete and transparent manner. Finally, it is recommended to always report the BMD confidence interval rather than the value of the BMD. The lower bound (BMDL) is needed as a potential RP, and the upper bound (BMDU) is needed for establishing the BMDU/BMDL per ratio reflecting the uncertainty in the BMD estimate. This updated guidance does not call for a general re-evaluation of previous assessments where the NOAEL approach or the BMD approach as described in the 2009 SC guidance was used, in particular when the exposure is clearly smaller (e.g. more than one order of magnitude) than the health-based guidance value. Finally, the SC firmly reiterates to reconsider test guidelines given the expected wide application of the BMD approach.

Following a request from EFSA, the Panel on Plant Protection Products and their Residues (PPR) developed an opinion on the state of the art of Toxicokinetic/Toxicodynamic (TKTD) models and their use in prospective environmental risk assessment (ERA) for pesticides and aquatic organisms. TKTD models are species-and compound-specific and can be used to predict (sub)lethal effects of pesticides under untested (time-variable) exposure conditions. Three different types of TKTD models are described, viz., (i) the 'General Unified Threshold models of Survival' (GUTS), (ii) those based on the Dynamic Energy Budget theory (DEBtox models), and (iii) models for primary producers. All these TKTD models follow the principle that the processes influencing internal exposure of an organism, (TK), are separated from the processes that lead to damage and effects/mortality (TD). GUTS models can be used to predict survival rate under untested exposure conditions. DEBtox models explore the effects on growth and reproduction of toxicants over time, even over the entire life cycle. TKTD model for primary producers and pesticides have been developed for algae, Lemna and Myriophyllum. For all TKTD model calibration, both toxicity data on standard test species and/or additional species can be used. For validation, substance and species-specific data sets from independent refined-exposure experiments are required. Based on the current state of the art (e.g. lack of documented and evaluated examples), the DEBtox modelling approach is currently limited to research applications. However, its great potential for future use in prospective ERA for pesticides is recognised. The GUTS model and the Lemna model are considered ready to be used in risk assessment. This is an open access article under the terms of the Creative Commons Attribution-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited and no modifications or adaptations are made.The EFSA Journal is a publication of the European Food Safety Authority, an agency of the European Union. As a third deliverable of this mandate, the PPR Panel is asked to develop a Scientific Opinion describing the state of the art of Toxicokinetic/Toxicodynamic (TKTD) models for aquatic organisms and prospective environmental risk assessment (ERA) for pesticides with the main focus on: (i) regulatory questions that can be addressed by TKTD modelling, (ii) available TKTD models for aquatic organisms, (iii) model parameters that need to be included and checked in evaluating the acceptability of regulatory relevant TKTD models, and (iv) selection of the species to be modelled.Chapter 2 presents the underlying concepts, terminology, application domains and complexity levels of three different classes of TKTD models intended to be used in risk assessment, viz., (i) the 'General Unified Threshold models of Survival' (GUTS), (ii) toxicity models derived from the Dynamic Energy Budget theory (DEBtox models), and (iii) models for primary producers. All ...

To meet the general requirement for transparency in EFSA's work, all its scientific assessments must consider uncertainty. Assessments must say clearly and unambiguously what sources of uncertainty have been identified and what is their impact on the assessment conclusion. This applies to all EFSA's areas, all types of scientific assessment and all types of uncertainty affecting assessment. This current Opinion describes the principles and methods supporting a concise Guidance Document on Uncertainty in EFSA's Scientific Assessment, published separately. These documents do not prescribe specific methods for uncertainty analysis but rather provide a flexible framework within which different methods may be selected, according to the needs of each assessment. Assessors should systematically identify sources of uncertainty, checking each part of their assessment to minimise the risk of overlooking important uncertainties. Uncertainty may be expressed qualitatively or quantitatively. It is neither necessary nor possible to quantify separately every source of uncertainty affecting an assessment. However, assessors should express in quantitative terms the combined effect of as many as possible of identified sources of uncertainty. The guidance describes practical approaches. Uncertainty analysis should be conducted in a flexible, iterative manner, starting at a level appropriate to the assessment and refining the analysis as far as is needed or possible within the time available. The methods and results of the uncertainty analysis should be reported fully and transparently. Every EFSA Panel and Unit applied the draft Guidance to at least one assessment in their work area during a trial period of one year. Experience gained in this period resulted in improved guidance. The Scientific Committee considers that uncertainty analysis will be unconditional for EFSA Panels and staff and must be embedded into scientific assessment in all areas of EFSA's work.