The aim of this call is to seek support for the development of a novel strategy for allergenicity risk assessment (RA) of proteins in food and feed. For both clinically-relevant cross-reactivity and de novo sensitisation, the project foresees the development of open source in silico prediction/appraisal tools to be validated with experimental data; assessment of future prospects for in silico tools; estimation of thresholds of allergological concern, and the development of a systematic tiered approach with a decision-making framework. This novel strategy will enhance the reliability and speed of allergenicity RA and support process simplification and harmonisation, ultimately enabling better-informed risk management decision-making.
See the official notice for the place of performance.
The tenderer must have generated an overall annual turnover of at least 600.000 € in each of the last 3 closed financial years (2022, 2023 and 2024).
Overall at Organisational Level: The tenderer must have the technical and professional capacity to perform the contract in accordance with the tender specifications. The tenderer overall must have extensive and demonstrable experience in the subject matter of the call*, i.e., regulatory allergenicity risk assessment of proteins in food and feed (including expertise on thresholds of allergological concern), and in silico, in vitro and in vivo methodologies for allergenicity assessment of proteins in food and feed (i.e., clinically relevant cross-reactivity to known allergens and de novo sensitisation).
Ability to Provide a Team of Experts Compliant with Specific Expertise Requirements: The tenderer must have the ability to provide a team of scientists compliant with the below minimum expertise requirements (a to e) and able to perform the contract in accordance with the tender specifications. Expertise (a to e) shall be demonstrated by three (3) relevant scientific projects (with a minimum duration of 6 months) or scientific articles (published) carried out in the course of the past 5 years. Scientific projects shall be completed or close to completion within the requested timeframe. a) At least one scientist with professional experience in regulatory allergenicity risk assessment of proteins in food and feed (including expertise on thresholds of allergological concern). b) At least one scientist with professional experience in in silico methodologies for allergenicity assessment of proteins in food and feed (clinically relevant cross-reactivity and de novo sensitisation). The scientist's expertise should cover, as broadly as possible, the main bioinformatic and computational approaches and tools used in this field, such as sequence homology analysis and similarity search (e.g. BLAST NCBI), phylogenetic analysis (e.g. PhyML, MEGA), 3D structural modelling and simulation tools (e.g. Charmm, NAMD, Gromacs), machine learning based allergen prediction tools (e.g. AllergenFP, AlgPred, AllerCatPro), binary fingerprint similarity methods (e.g. AllergenFP), and HLA binding prediction models, without the expectation of full proficiency in every single technique. Knowledge of main 3D structure prediction tools such as AlphaFold2, ESMFold, OpenFold and RosettaFold. The scientist shall also have professional experience with scripting languages for scientific computation and analysis (e.g., Python, R), machine learning algorithms and containerisation technologies. c) At least one scientist with professional experience in in vitro methodologies for allergenicity assessment of proteins in food and feed (clinically relevant cross-reactivity and de novo sensitisation). d) At least one scientist with professional experience in in vivo methodologies for allergenicity assessment of proteins in food and feed (clinically relevant cross-reactivity and de novo sensitisation). e) At least one scientist with professional experience in intelligence gathering (e.g., systematic literature review) to be demonstrated.
English Language Capacity of Each Team Member Individually: The scientists proposed to meet the selection criterion 2.4.B.2 must have an excellent level of spoken and written English. For non-native speakers, this must be demonstrated by an Official certificate of English proving a C1 level OR at least 3 years of work in an English-speaking environment OR by proof of (co)authorship of at least 5 scientific publications and/or reports in English language.
Overall at Organisational Level (Tools and Infrastructure): The tenderer must have the following minimum technical capacity to perform the contract: · Access to at least three multidisciplinary and biomedical bibliographic databases (e.g., Web of Science, Scopus, PubMed, Embase) and a reference manager software compatible with EndNote20. · Access to license-free open-source programming languages: R, Python, Java/Javascript, C/C++/C#, Nextflow, shell scripting and SQL (where applicable). · Access to Docker, Apptainer or Singularity container. · Access to code versioning and tracking platforms (e.g., Azure DevOps, GitHub).
a) Signed declaration on honour.
a) Signed declaration on honour.
Environmental protection is an integral part of EFSA's governance. EFSA has established, implemented and maintains a certified environmental management system in accordance with the international standard ISO 14001 and the European EMAS regulation. Environmental impacts of EFSA's activities are identified, managed and monitored in order to improve environmental performance. This commitment to environmental sustainability requires us to consider a life-cycle perspective when purchasing our services. For this reason we are asking you some information on the environmental management of your activities, to be provided filling in Annex 3 (Information on environmental management). To be completed by the tenderer or leading partner. The answers will not be considered under any criteria, neither selection nor award criteria.
In accordance with articles 143(1)(d) and 170(1)(c) of the Financial Regulation and paragraphs 166 and 167 of the recitals, if EFSA, based on the assessment of the technical and professional capacity evidence, as well as the information within the Declaration of honour (section C), concludes that the tenderer has a professional conflicting interest and therefore does not possess the professional capacity to perform the contract to an appropriate quality standard, the tenderer may be rejected.
Published 17 April 2026 · rebuilt nightly from the official notice.