Mots-Clés
Organ-On-Chip
Multimodal data
digital signatures
Neurotoxicity
Description
Concerns about the neurotoxicity of pesticides, particularly their effects on the developing brain, are rising among public health authorities and the broader scientific community. Addressing these concerns requires innovative New Approach Methodologies (NAMs) capable of generating mechanistic and predictive insights into neurotoxic hazards, while also reducing the reliance on animal testing.
Among the most promising NAMs, organ-on-chip (OoC) technology enables the co-culture of human-relevant cell types in a controlled microenvironment. In this project, we leverage NETRI’s DuaLink Shift microfluidic platform integrated with microelectrode arrays (MEA) to monitor the electrophysiological activity of hiPSC-derived glutamatergic neurons across spatial compartments. Functional responses, combined with morphological and molecular analyses, are transformed into multimodal datasets from which Digital Signatures of neurotoxicity are derived.
This PhD project aims to develop a fully characterized and robust in vitro method, supported by analysis tools that are scalable and transferable for regulatory and industrial applications. The envisioned outcome is a deployable platform capable of evaluating chemical neurotoxicity using a rich and interpretable data layer.
A central objective of the PhD will be the creation of a comprehensive and interpretable database compiling the multimodal Digital Signatures of tested compounds. The candidate will be responsible for designing and implementing the data architecture, integrating MEA, imaging, and biomarker readouts, and ensuring consistency and traceability across datasets. In addition to the database itself, the candidate will also be expected to develop data-driven tools as needed—such as visualization interfaces, analytical pipelines, or classification algorithms—to support data interpretation, usability, and communication of findings. The candidate will be fully integrated into the Data Management team at NETRI, benefiting from close support and collaboration throughout the project. This database will serve not only as a foundation for internal analysis and model development, but also as a resource for the broader toxicology and regulatory communities, supporting transparency, reproducibility, and future large-scale deployment (FAIR principles).
The candidate will play a central role in building and refining this system, working closely with both NETRI and ANSES in a collaborative and interdisciplinary environment. While hands-on biological work will be minimal (conducted primarily by an ANSES technician), the candidate is expected to develop a strong understanding of the experimental pipeline to enable meaningful interpretation of the resulting data. Beyond technical data processing, they will engage in the biological and toxicological interpretation of results—helping to bridge the gap between raw data and scientific insight.
Project Structure
Phase 1: Establish and validate the experimental workflow using reference compounds such as rotenone and vanillin. This includes defining dose-response curves and collecting multimodal data (MEA recordings, imaging, immunostaining, mitochondrial activity, and neurite outgrowth). Data will be integrated through multivariate and machine learning approaches.
Phase 2: Expand the model to include diverse toxicants targeting mitochondrial function, synaptogenesis, myelination, and epigenetic pathways. Additional readouts will be incorporated and analyzed to assess neurodevelopmental toxicity.
Phase 3: Apply the validated platform to a larger-scale screening effort (~100 compounds) in partnership with the European PARC consortium. The resulting open-access database will correlate compound-specific Digital Signatures with mechanistic and functional profiles, enhancing transparency and regulatory relevance.
Candidate Profile
We are seeking a highly motivated and autonomous PhD candidate with a strong background in data science, computational neuroscience, or bioinformatics. A genuine interest in biology and toxicology is essential, as the candidate will contribute not only to data analysis but also to the interpretation of results in a mechanistic context. Prior knowledge in bioengineering or neurobiology is advantageous but not mandatory. The candidate must have strong analytical and project management skills, effective communication abilities, and adaptability to collaborative, cross-disciplinary work.
Application procedure: send a detailed CV to the PhD supervisor and co-supervisor. NETRI SAS is funding the PhD through CIFRE fellowship program, and the Anses laboratory of Lyon is providing the academic supervision. The two institutions are only 400 meters apart and are part of the Lyon Gerland biocluster