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Updated: Jun 4, 2025

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Machine learning-based analysis of microfluidic device immobilized C. elegans for automated developmental toxicity

Andrew DuPlissis1, Abhishri Medewar1, Evan Hegarty1

  • 1vivoVerse, LLC, Austin, TX, 78731, USA.

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|January 2, 2025
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Summary

A new machine learning platform, vivoBodySeg, rapidly analyzes C. elegans development toxicity (DevTox) data. This high-throughput approach significantly accelerates toxicity testing, enabling faster chemical safety assessments.

Keywords:
C. elegansDevelopmental toxicityFew-shot learningHigh-throughput screeningMicrofluidicsU-Net

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Area of Science:

  • Toxicology
  • Developmental Biology
  • Computational Biology

Background:

  • Developmental toxicity (DevTox) testing traditionally uses mammalian models.
  • New Approach Methodologies (NAMs) offer alternatives, with *C. elegans* showing promise for high-throughput screening.
  • Current *C. elegans* DevTox methods are limited by low resolution and labor intensity.

Purpose of the Study:

  • To develop a rapid, high-throughput image analysis platform for *C. elegans* developmental toxicity studies.
  • To overcome the limitations of manual analysis for large datasets generated by microfluidic devices.
  • To enable accurate phenotyping of sub-lethal developmental effects.

Main Methods:

  • Utilized a large-scale microfluidic device (vivoChip) for high-resolution 3D imaging of approximately 1000 *C. elegans* per experiment.
  • Developed a machine learning (ML)-based image analysis platform (vivoBodySeg) employing a 2.5D U-Net architecture for *C. elegans* segmentation.
  • Processed large image datasets (36 GB per device) on a desktop PC, achieving automated phenotyping.

Main Results:

  • vivoBodySeg achieved a high segmentation accuracy with a Dice score of 97.80%.
  • The platform analyzed data 140x faster than manual methods, completing analysis in 35 minutes per device.
  • Generated highly reproducible DevTox parameters with low coefficients of variation (4-8%).

Conclusions:

  • The ML-based vivoBodySeg platform enables rapid, high-throughput, and reproducible developmental toxicity testing using *C. elegans*.
  • This approach significantly enhances the efficiency and statistical power of chemical toxicity assessments.
  • vivoBodySeg facilitates the broader adoption of *C. elegans* as a NAM for regulatory toxicology.