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Updated: Feb 28, 2026

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography
Published on: August 16, 2020
From conventional screening to self-driving discovery: Organ-on-Chip platforms as engines for AI-guided nanomedicine
Kimia Asadi Jozani1, Karen Shen2, Nicky Anvarihamedani1
1School of Biomedical Engineering, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4L8, Canada.
Abstract:
Nanoparticles have become an essential platform for next-generation drug delivery and therapeutic development, yet clinical translation remains limited by an incomplete understanding of their interactions within human biological systems. Organ-on-a-chip technology offers a powerful approach to evaluate efficacy and safety of nanomedicine under physiologically relevant conditions in human cells by recreating fluid flow, mechanical stress, barrier function, immune interactions and inter-organ communications. These advanced in vitro systems allow quantitative assessments of nanoparticle transport, distribution, and safety with improved human relevance compared to conventional cell culture and animal models. The integration of sensors within organ-on-a-chip platforms enables real-time monitoring of tissue responses and nanoparticle kinetics. Advances in automation and robotic liquid handling support scalable and reproducible testing across multiple tissue models. Artificial intelligence and active learning tools facilitate automated data analysis and experimental optimization, paving the way towards self-driving nanomedicine evaluation platforms that accelerate discovery and clinical translation.

