Learning in Transformative Research Niches: The Case of Non-Animal Methods for Thyroid Disrupting Chemicals Risk Assessment

Abstract

Transformative change is increasingly recognized as essential to address complex sustainability challenges such as chemical pollution. Within this context, non-animal new approach methodologies (NAMs) offer promising alternatives to traditional animal testing for chemical risk assessment. However, the uptake of NAMs has been slow and fragmented, particularly in the case of endocrine disrupting chemicals (EDCs) such as those affecting the thyroid system. This study explores the role of collective learning conditions in enabling the formation and successful development of transformative research niches (TRNs), using the development of NAMs for thyroid disrupting chemicals (TDCs) as an empirical case. Focusing on scientific laboratories as key actors, the study investigates how specific features of collaboration networks, such as position, diversity, and institutional linkages, influence a laboratory’s success in developing and advancing NAMs. Two original datasets were constructed: one covering co-authorship networks in R&D publications, and another covering laboratory involvement in validation activities. Social network analysis and statistical correlation tests were applied to assess the relationship between success (measured by the number of NAMs developed by a laboratory and the number of those NAMs reaching stages beyond R&D) and several structural and relational variables. The results show that the TRN for NAMs for TDCs is in an early but articulated phase of development, characterised by high fragmentation, regional clustering, and low connectivity. Laboratories occupying brokerage positions, those connecting otherwise disconnected communities, were significantly more successful in developing NAMs. Additionally, laboratories collaborating with a diverse range of institutional actors (e.g. regulatory, academic, private) tended to produce more NAMs. However, these conditions 2 were not strongly associated with the progression of NAMs beyond the R&D phase. Rather, success in advancing NAMs appeared linked to participation in validation networks, proximity to regulatory bodies, and strategic brokerage positions. The study contributes to the literature on socio-technical transitions and TRNs by identifying which learning network conditions matter at different stages of innovation. It highlights that while diverse and well-connected networks foster innovation, regulatory uptake may require complementary institutional mechanisms. The findings also refine assumptions about international collaboration, showing that strategic links held by central actors may be more effective than broad global partnerships in early-stage niches. By identifying key learning conditions, this thesis offers insights to support more effective governance, collaboration, and implementation strategies in emerging scientific transitions like the adoption of NAMs.