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Classroom Card #4335
Understanding mass and momentum transfer using microfluidic devices
Updated: 11/20/2024 12:48 PM by Yuan Tang
Reviewed: 11/20/2024 12:52 PM by Ajmal Khan
Summary
Applying EM concepts to explore oxygen transfer in vitro using computational modeling.
Course

This course integrates the principles of biotransport phenomena with an Entrepreneurial Minded Learning (EML) approach, focusing on studying the oxygen transport in the tumor microenvironment using state-of-the-art microfluidic models. Students will explore the dynamics of oxygen transport, fluid mechanics, and mass transfer within biological systems, particularly within the context of hypoxic tumor microenvironments. By engaging in problem-based learning projects, students will gain hands-on experience with computational modeling and experimental techniques to analyze the interactions between cancer cells and endothelial cells under hypoxic and inflammatory conditions.

Key Learning Objectives:
  • Understand the fundamentals of biotransport phenomena, including diffusion, convection, and reaction kinetics in biological contexts.
  • Develop skills in computational modeling using COMSOL to simulate oxygen transport and cell proliferation in tumor microenvironments.
  • Apply Entrepreneurial Minded Learning (EML) principles to foster curiosity, make meaningful connections, and create value in solving real-world biomedical engineering problems.
  • Gain practical experience with microfluidic devices for studying tumor-EC interactions and the metastatic cascade.
  • Communicate scientific findings effectively to both technical and non-technical audiences, including TNBC survivors and the broader community.
Course Highlights:
  • Hands-on projects involving the application of microfluidic platforms to investigate cancer metastasis.
  • Collaborative team-based learning, emphasizing innovative problem-solving and entrepreneurial thinking.
  • Outreach and knowledge dissemination activities with a focus on engaging underrepresented groups in STEM, particularly high school students and TNBC survivor communities.
Time
Semester
Materials
Prerequisites
Tissue Engineering; Elementary Differential Equations; Some level of programing practice, such as using Matlab or COMSOL
Description

Student year level: Junior (third year)

Number of students: 20-30

Frequency of the course: 3 times per week; 50 minutes each session

Objective: To enhance student understanding of oxygen transfer in hypoxic tumors using in vitro models, integrating EML principles to foster curiosity, connections, and creating value.

Week 1-2: Course Introduction and EML Concepts

Activities:

  1. Course Overview:

    • Introduction to course objectives, structure, and expectations.
    • Overview of biotransport phenomena and their significance in biomedical engineering.

     

  2. EML Principles:

    • Introduction to EML concepts: curiosity, connections, and creating value.
    • Presentation of case studies on innovative solutions in cancer research and biotransport phenomena.

Outcomes:

  • Students understand the course framework and the importance of EML.
  • Students gain insight into real-world applications of biotransport phenomena in cancer research.
Week 3-4: Foundations of Biotransport Phenomena

Activities:

  1. Lectures:

    • Fundamentals of diffusion, convection, and reaction kinetics in biological systems.
    • Specific focus on oxygen transport in hypoxic tumor environments.

     

  2. Project Briefing:

    • Formation of teams of 3-4 students.
    • Assignment of the semester-long project: Investigate oxygen transfer in hypoxic tumors using in vitro microfluidic models.

Outcomes:

  • Students grasp the basic principles of biotransport phenomena.
  • Teams are formed and oriented towards their project goals.
Week 5-6: Problem Definition and Research

Activities:

  1. Literature Review:

    • Teams conduct literature reviews on hypoxia in tumors and oxygen transport mechanisms.
    • Identification of key research questions, hypotheses and parameters related to oxygen transfer in tumor microenvironments.

     

  2. Project Proposal:

    • Development of initial project proposals outlining objectives, hypotheses, and research methodologies.
    • Feedback session with other instructors/TAs to refine project proposals.

Outcomes:

  • Teams develop a strong foundation in the current state of research on hypoxia in tumors.
  • Clear, focused project proposals ready for implementation.
Week 7-8: Computational Modeling Training

Activities:

  1. COMSOL Workshops:

    • Hands-on training sessions in COMSOL Multiphysics, focusing on modeling laminar flow and oxygen diffusion/consumption in tumor microenvironment featuring endothelial cell-tumor cell coculture.
    • Guidance on setting up simulations, defining parameters, and interpreting results.

     

  2. Model Development:

    • Teams begin developing their computational models, simulating oxygen transport in hypoxic conditions.
    • Iterative testing and refinement of models based on initial feedback.

Outcomes:

  • Students gain practical skills in computational modeling using COMSOL.
  • Initial models simulating oxygen transport in tumors are developed.
Week 9-10: Experimental Design and Simulation

Activities:

  1. Lab Sessions (preferably conducted in a tissue culture lab):

    • Establish hypoxic tumor microenvironment by coculturing endothelial cells and tumor cells in the microfluidic device
    • Experimental design to validate computational models, including probing oxygen concertation using fluorescence imaging with a hypoxia dye.

     

  2. Simulation and Data Collection:

    • Teams conduct simulations and begin experimental data collection.
    • Continuous monitoring and adjustment of experimental setups to ensure accurate data collection.

Outcomes:

  • Students apply theoretical knowledge to practical experimental setups.
  • Initial experimental data collected for model validation.
Week 11-12: Data Analysis and Model Refinement

Activities:

  1. Data Analysis:

    • Teams analyze experimental data, comparing it with computational model predictions.
    • Identify discrepancies and refine models to improve accuracy

     

  2. Interim Presentations:

    • Teams present their progress, including model development, experimental data, and preliminary findings.
    • Peer and instructor feedback sessions to guide further improvements.

Outcomes:

  • Improved computational models through data-driven refinement.
  • Enhanced understanding of the relationship between theoretical predictions and experimental observations.
Week 13-14: Solution Development and Finalization

Activities:

  1. Integration of Findings:

    • Teams integrate computational and experimental findings to develop comprehensive solutions to the oxygen transfer problem in hypoxic tumors.
    • Preparation of final project reports and presentations, emphasizing EML principles and real-world applications.

     

  2. Final Project Development:

    • Focus on fine-tuning project deliverables, ensuring clarity and impact.

Outcomes:

  • Comprehensive, well-integrated project solutions.
  • High-quality final reports and presentations ready for delivery.
Week 15: Final Presentations and Course Wrap-up

Activities:

  1. Final Presentations:

    • Teams present their final projects to the class, highlighting the application of EML principles and the significance of their findings.
    • Engage in Q&A sessions and receive constructive feedback from peers and instructors.

     

  2. Reflection and Course Evaluation:

    • Conduct reflective discussions on challenges faced, lessons learned, and overall course experience.
    • Collect feedback on the course structure, content, and EML integration for continuous improvement.

Outcomes:

  • Students demonstrate a deep understanding of oxygen transfer in hypoxic tumors and the use of in vitro tools.
  • Valuable feedback collected for future course enhancements.
Curiosity
  • Demonstrate constant curiosity about our changing world
Connections
  • Integrate information from many sources to gain insight
Creating Value
  • Persist through and learn from failure
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