High-throughput Organoid Drug Efficacy Screening Platform

Combining microfluidics, synthetic biology, tissue engineering, and machine learning to tackle efficient drug screening

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Overview: Clinical treatment of glioblastoma, a disease that kills over 10,000 Americans annually, is limited by the lack of a scalable, physiologically-relevant model for testing therapeutics. Duke iGEM is developing NODES, a high-throughput organoid-based drug screening platform to characterize treatment efficacy in common glioma variants. We designed a non-invasive reporter device that quantifies the drug response of mutation-specific glioma cells in a mini-brain co-culture model, grown in a droplet-based system. Additionally, we modeled our reporter system, which detects oncometabolite levels throughout brain tumor development, to improve device characteristics and developed a machine-learning based image analysis pipeline for organoid screening. To identify the social and ethical implications of our work, we interviewed patients, clinicians, and other stakeholders and integrated their feedback into our design. By recapitulating the brain microenvironment, NODES has the potential to accurately characterize drug responses, offering new hope to patients in their fight against this lethal disease.

Recognitions: This ongoing project is sponsored by the Lord Foundation, Woo Center for Big Data and Precision Medicine, Duke Biomedical Engineering, and Bass Connections.