The Toxicity of Microplastics Explorer (ToMEx) database is an open-source, open-access database and web application for microplastics toxicity. Its purpose is to provide a valuable easy-to-access tool for data exploration, visualization, and analysis, and a data source for the development of environmentally safe thresholds for micro- and nanoplastic exposure. However, since its release three years ago, the peer-reviewed literature has continued to expand exponentially, rendering ToMEx increasingly obsolete. To guarantee the continued utility of ToMEx, a crowdsourcing approach was employed to establish a global workgroup tasked with updating ToMEx by extracting data from additional studies published after the original release.
We here present the results and the experience with this process, which led to ToMEx 2.0 now having doubled in size. Although the aquatic organisms database now encompasses a greater diversity of species and test particle characteristics, both the aquatic and the human health database remain biased towards a few dominant particle characteristics (polystyrene spheres) and particle-only studies (without additional chemicals, not leachates). To investigate, whether the increased amount of can be used to derive more precise regulatory thresholds, a previously developed framework for establishing health-based microplastic thresholds for the state of California was reapplied. We show that thresholds for ToMEx 2.0 are lower and more precise than earlier thresholds based on ToMEx 1.0. Nevertheless, the data suitable for threshold development remained limited with only few proper dose-response experimental designs added to derive No Observed Effect Concentrations (NOECs) and the shift was driven mainly by two new publications. Given the effort required to update the ToMEx database, we believe that future updates should only incorporate studies that meet strict quality criteria to ensure data utility and ensure feasibility. Nevertheless, ToMEx remains a valuable tool for the research community, and this exercise demonstrates that large, coordinated data-mining efforts are feasible.

Disclaimer/Disclosure:  Funding for this project was provided by the Southern California Coastal Water Research Project Authority. B.C.A. is grateful for funding from the Swedish Research Council for Sustainable Development FORMAS 2018 01201. M.M.M. received funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) SFB 1357 391977956.