Lidia Ceriani - Academia.edu (original) (raw)

Papers by Lidia Ceriani

Background: EFSA's remit and chemical risk assessment of regulated products and... more Background: EFSA's remit and chemical risk assessment of regulated products and contaminants The European Food Safety Authority (EFSA) has the remit to provide scientific advice to risk managers and decision makers through risk assessment and risk communication on issues related to "food and feed safety, animal health and welfare, plant health, nutrition, and environmental issues". Risk assessment has been defined as "a scientifically based process consisting of four steps: hazard identification, hazard characterisation, exposure assessment and risk characterisation" (EC, 2002). In the food and feed safety area, hazard identification and hazard characterisation aim to determine safe levels of exposure for regulated products or contaminants as "reference values1" to protect human health, animal health, environmental-relevant species or the whole ecosystem. Such reference values for a given species are most often derived by using a "reference point2" determined from the critical toxicological study on which an uncertainty factor3 is applied. Since its creation in 2002, the European Food safety Authority (EFSA) has produced risk assessments for more than 4,750 unique substances in over 1,800 Scientific Opinions, Statements and Conclusions through the work of its scientific Panels, Units and Scientific Committee. For regulated products, these risk assessments have been performed by five scientific panels and four supporting units. EFSA's chemical Hazards Database : OpenFoodTox OpenFoodTox is a structured database summarising the outcomes of hazard identification and characterisation for the human health (all regulated products and contaminants), the animal health (feed additives, pesticides and contaminants) and the environment (feed additives and pesticides). OpenFoodTox the substance characterisation, the links to EFSA's related output, background European legislation, and a summary of the critical t [...]

Computational Toxicology

Highlights • Chemical toxicity assessment depends on the quantification of kinetics and dynamics.... more Highlights • Chemical toxicity assessment depends on the quantification of kinetics and dynamics.• Quantitative AOPs (qAOPs) are toxicodynamic models based on Adverse Outcome Pathways.• Existing e-resources could form the basis of an e-infrastructure for qAOP modelling.• Best practices for qAOP development, assessment and application are needed.• Three qAOP case studies are presented to illustrate a modelling workflow.

EFSA Supporting Publications

The present document is a summary of the activities undertaken during the first year of the frame... more The present document is a summary of the activities undertaken during the first year of the framework contract (OC/EFSA/SCER/2018/01) undertaken for the maintenance, update and further development of EFSA's chemical Hazards database "OpenFodTox 2.0". OpenFoodTox has been developed over the last 7 years to map and collect hazards data published in EFSA outputs for the risk assessment of chemicals in food and feed (i.e opinions, statements and conclusions). More specifically, the database holds summary data on identification of chemicals, document descriptors, hazard identification, and hazard characterisation. Within OpenFoodTox 2.0, the collection and entry of all hazard data assessed by EFSA scientific panels was performed according to the existing data model with the inclusion of PARAM codes. In parallel, OpenFoodTox data model was further expanded to incorporate new properties in the database including physicochemical properties (OHT 1 to 23-5), degradation and bioaccumulation (OHT 32 and 33), toxicokinetic data (OHT 58), intermediate effects (OHT 201), "New Approach methodologies (NAM)" as proposed by the European Chemicals Agency use and exposure information (OHT 301 to 306), as well as any other properties deemed relevant. Data for new substance properties have been collected from recent EFSA documents published in 2018 and 2019 and will be integrated in OpenFoodTox 2.0 in the new data model. Furthermore, preliminary results on new QSAR models are here presented as part of the design of an in silico integrative tool allowing description and prediction of hazard properties of chemicals within "OpenFoodTox 2.0".

EFSA Supporting Publications

The present document is a summary of the update and maintenance of the EFSA's Chemical Hazards Da... more The present document is a summary of the update and maintenance of the EFSA's Chemical Hazards Database that has been established few years ago to map the hazard data as collected from the EFSA opinions, statements and conclusions; more specifically the repository holds summary data on chemical identification, document descriptors, hazard identification, and hazard characterisation/ risk characterisation. The repository includes data extracted from opinions and statements adopted by a number of EFSA panels including NDA (vitamins and minerals, novel foods, dietetic products), CONTAM (contaminants in the food chain, contaminants in the feed chain), FEEDAP (feed additivesapplication linked to 1381/2003, feed additives-application under to 1381/2003, feed additives-other), AFC (food additives, food contact materials, nutrient sources, processing aids, flavourings), CEF (food contact materials, food manufacturing processes, processing aids, flavourings), ANS (food additives, nutrient sources) and PPR (pesticides). Substances which do not fall within the category of chemicals (e.g., microorganisms and enzymes) are excluded from the EFSA's Chemical Hazards Database.

EFSA Supporting Publications

Environmental Toxicology and Chemistry, 2015

In the present study, Quantitative Structure Activity Relationships were developed for predicting... more In the present study, Quantitative Structure Activity Relationships were developed for predicting ready biodegradability of approximately 200 heterogeneous fragrance materials. Two classification methods, Classification And Regression Tree (CART) and k-Nearest Neighbors (k-NN), were applied to perform the modeling. The models were validated with multiple external prediction sets, and the structural applicability domain was verified by the leverage approach. The best models had good sensitivity (internal ≥ 80%; external ≥ 68%), specificity (internal ≥ 80%; external 73%), and overall accuracy (≥ 75%). Results from the comparison with BIOWIN global models, based on group contribution method, show that specific models developed in the present study perform better in prediction than BIOWIN6, in particular for the correct classification of not readily biodegradable fragrance materials. This article is protected by copyright. All rights reserved.

Molecular Informatics

Read‐across is a non‐testing data gap filling technique which provides information for toxicologi... more Read‐across is a non‐testing data gap filling technique which provides information for toxicological assessments by inferring from known toxicity data of compound(s) with a “similar” property or chemical profile. The increased usage of read‐across was driven by monetary, timing and ethical costs associated with in vivo testing, as well as promoted by regulatory frameworks to minimize new animal testing (e. g., EU‐REACH). Several guidance documents have been published by ECHA and OECD providing guidelines on how to perform, assess and document a read‐across study. In parallel, much effort was invested by the scientific community to provide good read‐across practices and structured frameworks to enhance validity of read‐across justifications. Nevertheless, read‐across is an evolving method with several open issues and opportunities. A brief review is here provided on key developments on the use of read‐across, regulatory and scientific expectations, practical hurdles and open challenges.

Computational Toxicology

EFSA Supporting Publications

Environmental Toxicology and Chemistry, 2015

Molecular Informatics