Report of the First ONTOX Stakeholder Network Meeting : Digging Under the Surface of ONTOX Together With the Stakeholders

The first Stakeholder Network Meeting of the EU Horizon 2020-funded ONTOX project was held on 13-14 March 2023, in Brussels, Belgium. The discussion centred around identifying specific challenges, barriers and drivers in relation to the implementation of non-animal new approach methodologies (NAMs) and probabilistic risk assessment (PRA), in order to help address the issues and rank them according to their associated level of difficulty. ONTOX aims to advance the assessment of chemical risk to humans, without the use of animal testing, by developing non-animal NAMs and PRA in line with 21st century toxicity testing principles. Stakeholder groups (regulatory authorities, companies, academia, non-governmental organisations) were identified and invited to participate in a meeting and a survey, by which their current position in relation to the implementation of NAMs and PRA was ascertained, as well as specific challenges and drivers highlighted. The survey analysis revealed areas of agreement and disagreement among stakeholders on topics such as capacity building, sustainability, regulatory acceptance, validation of adverse outcome pathways, acceptance of artificial intelligence (AI) in risk assessment, and guaranteeing consumer safety. The stakeholder network meeting resulted in the identification of barriers, drivers and specific challenges that need to be addressed. Breakout groups discussed topics such as hazard versus risk assessment, future reliance on AI and machine learning, regulatory requirements for industry and sustainability of the ONTOX Hub platform. The outputs from these discussions provided insights for overcoming barriers and leveraging drivers for implementing NAMs and PRA. It was concluded that there is a continued need for stakeholder engagement, including the organisation of a 'hackathon' to tackle challenges, to ensure the successful implementation of NAMs and PRA in chemical risk assessment.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:52

Enthalten in:

Alternatives to laboratory animals : ATLA - 52(2024), 2 vom: 01. März, Seite 117-131

Sprache:

Englisch

Beteiligte Personen:

Diemar, Michael G [VerfasserIn]
Vinken, Mathieu [VerfasserIn]
Teunis, Marc [VerfasserIn]
Krul, Cyrille A M [VerfasserIn]
Busquet, Francois [VerfasserIn]
Zajac, Julia Dominika [VerfasserIn]
Kandarova, Helena [VerfasserIn]
Corvi, Raffaella [VerfasserIn]
Rosso, Matteo Z [VerfasserIn]
Kharina, Anastasiia [VerfasserIn]
Bryndum, Louise Stab [VerfasserIn]
Santillo, Michael [VerfasserIn]
Bloch, Denise [VerfasserIn]
Kucheryavenko, Olena [VerfasserIn]
Panagiotakos, Demosthenes [VerfasserIn]
Rogiers, Vera [VerfasserIn]
Beekhuijzen, Manon [VerfasserIn]
Giusti, Arianna [VerfasserIn]
Najjar, Abdulkarim [VerfasserIn]
Courage, Carol [VerfasserIn]
Koenig, Torben [VerfasserIn]
Kolle, Susanne [VerfasserIn]
Boonen, Harrie [VerfasserIn]
Dhalluin, Stephane [VerfasserIn]
Boberg, Julie [VerfasserIn]
Müller, Boris P [VerfasserIn]
Kukic, Predrag [VerfasserIn]
Ritskes-Hoitinga, Merel [VerfasserIn]
Grasselli, Elena [VerfasserIn]
Zietek, Tamara [VerfasserIn]
Stoddart, Gilly [VerfasserIn]
Heusinkveld, Harm J [VerfasserIn]
Castell, Jose V [VerfasserIn]
Benfenati, Emilio [VerfasserIn]
Yang, Huan [VerfasserIn]
Perera, Simón [VerfasserIn]
Paini, Alicia [VerfasserIn]
Kramer, Nynke I [VerfasserIn]
Hartung, Thomas [VerfasserIn]
Janssen, Manoe [VerfasserIn]
Fritsche, Ellen [VerfasserIn]
Jennen, Danyel G J [VerfasserIn]
Piumatti, Matteo [VerfasserIn]
Rathman, James [VerfasserIn]
Marusczyk, Jörg [VerfasserIn]
Milec, Lucia [VerfasserIn]
Roggen, Erwin L [VerfasserIn]

Links:

Volltext

Themen:

Artificial intelligence
Confidence
End-user acceptance
Hackathon
Journal Article
NAMs
New approach methodologies
Next generation risk assessment
Non-animal
Probabilistic risk assessment
Stakeholder network
Toxicology

Anmerkungen:

Date Completed 14.03.2024

Date Revised 14.03.2024

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1177/02611929231225730

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM367262355