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Evaluation of existing guidelines for their adequacy for the food and feed risk assessment of genetically modified plants obtained through synthetic biology

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Wiley Online Library

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Abstract

Synthetic biology (SynBio) is an interdisciplinary field at the interface of molecular engineering and biology aiming to develop new biological systems and impart new functions to living cells, tissues and organisms. EFSA has been asked by the European Commission to evaluate SynBio developments in agri‐food with the aim of identifying the adequacy and sufficiency of existing guidelines for risk assessment and determine if updated guidance is needed. In this context, the GMO Panel has previously adopted an Opinion evaluating the SynBio developments in agri‐food/feed and the adequacy and sufficiency of existing guidelines for the molecular characterisation and environmental risk assessment of genetically modified plants (GMPs) obtained through SynBio and reaching the market in the next decade. Complementing the above, in this Opinion, the GMO Panel evaluated the adequacy and sufficiency of existing guidelines for the food and feed risk assessment of GMPs obtained through SynBio. Using selected hypothetical case studies, the GMO Panel did not identify novel potential hazards and risks that could be posed by food and feed from GMPs obtained through current and near future SynBio approaches; considers that the existing guidelines are adequate and sufficient in some Synbio applications; in other cases, existing guidelines may be just adequate and hence need updating; areas needing updating include those related to the safety assessment of new proteins and the comparative analysis. The GMO Panel recommends that future guidance documents provide indications on how to integrate the knowledge available from the SynBio design and modelling in the food and feed risk assessment and encourages due consideration to be given to food and feed safety aspects throughout the SynBio design process as a way to facilitate the risk assessment of SynBio GMPs and reduce the amount of data required.