An Automated Control System for continuous monitoring of a mini-organ model with a smart biosensor

Overview

https://research.qut.edu.au/cbt/https://research.qut.edu.au/cbt/

Have you ever wondered how scientists can monitor the health of cells in a human organ model without causing any harm to them? This project explores the fascinating field of biomedical engineering, where the goal is to enhance an existing "organ-on-a-chip" model by incorporating a smart biosensor. This innovative model functions as a tiny laboratory that simulates the environment of a real organ through a combination of microfluidics and tissue engineering. Conventionally, cell health monitoring relies on techniques like microscopy or other methods that often result in the destruction of cells. This presents a significant hurdle as it prevents continuous and real-time observation of cell health and behavior. An automated control system for biosensors could potentially assist scientists to keep track of cell function and viability. The mission of this project is to establish an automated control system for smart biosensors including data processing to achieve continuous and real-time analysis of cellular condition, leading to more accurate and insightful data in biomedical research.

Research engagement

Lab-based work and programming

Research activities

Building the Device: You'll learn how to learn to create both the organ-on-a-chip model and the biosensor using cutting-edge electrochemical sensing techniques.

Establishing the automated system: You’ll develop skills to establish a connection between the machine for data acquisition and the biosensors, enabling them to work concurrently and automatically for up to a week.

Data processing: You’ll learn how to manage and process data using programming-based software like MATLAB to interpret and analyze the results effectively.

The student will work closely with Dr. Surasak Kasetsirikul.

Outcomes

The outcome is to establish the automated control system for biosensors and workflow for data analysis.

Skills and experience

The student may have programming-based software background e.g. LABVIEW, MATLAB. Also, wet laboratory practice and basic electronic skills, but is not required.

Start date

1 November, 2024

End date

21 February, 2025

Location

Q Block - Kelvin Grove Campus

Keywords

• Automated system
• Biosensors

Contact

Surasak (Tony) Kasetsirikul, 0402778266, tony.kasetsirikul@qut.edu.au