About Workshop
This workshop introduces microphysiological systems, including 3D organoids and organ-on-a-chip platforms, for advanced in vitro drug screening. Participants will learn how human-relevant 3D models, microfluidics, automated image analysis, and AI-based toxicity prediction are transforming modern biomedical and pharmaceutical research.
Aim
To provide practical understanding of how 3D organoids, organ-on-a-chip systems, and AI tools are used for drug screening, toxicity testing, and next-generation biomedical research.
What Participants Will Learn
- Understand 3D organoid architecture and its role in drug screening.
- Learn organ-on-a-chip design, fluid flow, and tissue barrier concepts.
- Explore automated image analysis for organoid measurement.
- Understand microfluidic flow and wall shear stress simulation.
- Apply basic AI/ML methods for toxicity prediction.
Structure
📅 Day 1: 3D Organoid Architectures & Automated Screening
- Moving from traditional flat 2D cell cultures to advanced 3D human-relevant biological models
- The shift from animal testing toward modern alternative methodologies in biomedical research
- Understanding 3D organoid cultures and their role in replicating human tissue-like structures
- Scaling up organoid systems for screening, testing, and translational research applications
- Biology in 3D: how organoids help model tissue layers, growth behavior, and cellular organization
- The data challenge in organoid research: limitations of manual cell counting and visual assessment
- Automated visual profiling for measuring organoid size, roundness, growth changes, and screening outcomes
- Skills gained: high-throughput screening concepts and automated cell measurement approaches
- Tools covered: Google Colab, Python, open-source image processing tools, microscopy image datasets
Hands-on Activity:
- Automated 3D Organoid Image Analysis in Google Colab: Use open-source image processing tools to segment 3D organoid microscopy images and extract key physical metrics such as size, roundness, and growth-related changes
📅 Day 2: Organ-on-a-Chip Engineering & Fluid Dynamics
- Replicating blood flow, tissue barriers, and multi-organ interactions using organ-on-a-chip platforms
- Introduction to tissue chip design and the role of microfluidics in human-relevant disease modeling
- Fluid dynamics in organ-on-a-chip systems: how continuous liquid flow mimics human blood vessels
- Understanding how fluid flow stimulates cell growth, tissue function, and physiological responses
- Barrier models: designing chips that replicate complex biological boundaries such as the Blood-Brain Barrier
- Modeling integrated systems such as the gut-liver axis for drug testing and toxicity studies
- Real-time sensing in tissue chips: monitoring cell health without destroying the biological sample
- Skills gained: tissue chip design principles and fluid shear stress analysis
- Tools covered: Google Colab, Python, microfluidic flow simulation concepts, basic fluid dynamics calculations
Hands-on Activity:
- Microfluidic Flow and Shear Stress Simulation in Google Colab: Simulate fluid flow through a microfluidic channel, calculate wall shear stress, and evaluate whether a chip design matches human physiological conditions
📅 Day 3: AI-Driven Drug Screening & Toxicity Prediction
- Combining laboratory data with Artificial Intelligence to predict drug safety and screening outcomes
- The convergence of tissue chip data, organoid screening, and AI-driven drug discovery workflows
- Understanding how experimental data from organ-on-a-chip systems can support AI model training
- Virtual screening: using public chemical databases to digitally evaluate large numbers of compounds
- Introduction to cheminformatics for handling chemical structures and molecular descriptors
- Safety testing with machine learning: predicting liver, heart, or kidney toxicity before physical trials
- Modeling toxic versus safe compound behavior using structured chemical and biological data
- Skills gained: chemistry software basics, cheminformatics concepts, and predictive machine learning
- Tools covered: Google Colab, Python, public chemical datasets, cheminformatics tools, Scikit-learn
Hands-on Activity:
- AI-Based Drug Toxicity Prediction in Google Colab: Process chemical data structures and train a machine learning classifier to predict whether a new drug molecule is toxic or safe
Important Dates
Registration Ends
7:00 PM
Workshop Dates
2026-07-08
8:00 PM
8:00 PM
What You Will Gain
Outcomes
- Understand the role of 3D organoids and organ-on-a-chip systems in next-generation drug screening.
- Differentiate between traditional 2D culture models and advanced 3D microphysiological models.
- Explain how organoids can be used to replicate tissue-like structures for disease modeling and drug response studies.
- Describe how microfluidic chip systems simulate blood flow, tissue barriers, and organ-level interactions.
- Perform basic automated image analysis for organoid measurement using open-source tools.
- Simulate fluid flow in a microfluidic channel and interpret wall shear stress values.
- Understand the role of real-time sensing in monitoring cell and tissue health.
- Process basic chemical structure data for virtual screening workflows.
- Build a simple machine learning model for toxicity prediction.
- Gain practical exposure to the convergence of biotechnology, microfluidics, image analysis, cheminformatics, and AI in drug discovery.