WOrM Podcast: Whole Organism Analytics Podcast13 Elo 2025

EPISODE 24: Worms on the Chip – Machine Learning Meets Toxicology

In this episode, we explore a high-tech twist on developmental toxicology. Researchers have combined microfluidic engineering with machine learning to automate the analysis of thousands of C. elegans for chemical toxicity testing — no anaesthetics or low-res imaging required.

Using the vivoChip device and a custom ML model called vivoBodySeg, the team:

Captures 3D images of ~1000 worms from 24 populations at once
Achieves near-human segmentation accuracy (Dice score: 97.8%)
Measures subtle toxicity effects like changes in body size and gut autofluorescence
Identifies EC10 and LOAEL values with high precision
Uses few-shot learning to adapt the model to new worm shapes and sizes

This platform slashes analysis time by 140× and sets a new benchmark for high-throughput New Approach Methodologies (NAMs) in toxicology.

📖 Based on the research article:

“Machine learning-based analysis of microfluidic device immobilised C. elegans for automated developmental toxicity testing”

Andrew DuPlissis, Abhishri Medewar, Evan Hegarty, et al.

Published in Scientific Reports (2025)

🔗 https://doi.org/10.1038/s41598-024-84842-x

🎧 Subscribe to the WOrM Podcast for more stories where whole-organism biology meets cutting-edge tech!

This podcast is generated with artificial intelligence and curated by Veeren. If you’d like your publication featured on the show, please get in touch.

📩 More info:

🔗 ⁠⁠www.veerenchauhan.com⁠⁠

📧 veeren.chauhan@nottingham.ac.uk

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