Organoid intelligence for developmental neurotoxicity testing

Dowlette-Mary Alam El Din; Jeongwon Shin; Alexandra Lysinger; Matthew J Roos; Erik C Johnson; Timothy J Shafer; Thomas Hartung; Lena Smirnova

doi:10.3389/fncel.2024.1480845

Organoid intelligence for developmental neurotoxicity testing

Front Cell Neurosci. 2024 Oct 8:18:1480845. doi: 10.3389/fncel.2024.1480845. eCollection 2024.

Authors

Dowlette-Mary Alam El Din¹, Jeongwon Shin², Alexandra Lysinger¹, Matthew J Roos³, Erik C Johnson³, Timothy J Shafer⁴, Thomas Hartung^{1

5

6}, Lena Smirnova¹

Affiliations

¹ Center for Alternatives to Animal Testing, Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.
² Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States.
³ Research and Exploratory Development Department, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States.
⁴ Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, United States.
⁵ Center for Alternatives to Animal Testing Europe, University of Konstanz, Konstanz, Germany.
⁶ Doerenkamp-Zbinden Chair for Evidence-based Toxicology, Baltimore, MD, United States.

Abstract

The increasing prevalence of neurodevelopmental disorders has highlighted the need for improved testing methods to determine developmental neurotoxicity (DNT) hazard for thousands of chemicals. This paper proposes the integration of organoid intelligence (OI); leveraging brain organoids to study neuroplasticity in vitro, into the DNT testing paradigm. OI brings a new approach to measure the impacts of xenobiotics on plasticity mechanisms - a critical biological process that is not adequately covered in current DNT in vitro assays. Finally, the integration of artificial intelligence (AI) techniques will further facilitate the analysis of complex brain organoid data to study these plasticity mechanisms.

Keywords: artificial intelligence; developmental neurotoxicity; machine learning; organoid; organoid intelligence; synaptic plasiticity.

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. Dowlette-Mary Alam El Din was supported by the National Institutes of Health (T32 ES007141) and International Foundation for Ethical Research Graduate Fellowship. We gratefully acknowledge research support from the JHU SURPASS program. The work was supported by a Johns Hopkins Discovery award and two Johns Hopkins SURPASS awards. This work was funded by the Combining advances in Genomics and Environmental science to accelerate Actionable Research in ASD (GEARS) Network (R01ES034554); Ladd-Acosta, Volk).