Project Abstract

Cell culture growth is an important aspect towards society’s good health and well-being, where it is an essential precursor and enabler in many critical areas such as vaccine development and research into personalised medicine. Current methods used in bio-manufacturing require trained experts to periodically observe cell culture to determine its growth and characteristics, which can be difficult, time-consuming and prone to human errors.

Therefore, we propose an in-depth characterisation and analysis of cell culture to enable the development of an automated Artificial Intelligence of Things (AIoT) system to reduce the dependency on humans and provide more accurate and consistent results. The proposed AIoT design applies deep-learning algorithms to monitor cell characteristics such as the cell count and confluency with temperature, humidity and other data to monitor the growth environment.

An AIoT-based Artificial Intelligence (AI) system, preferably deployed on a single board computer integrated with a digital microscope system, will enable real-time analysis of the cell culture growth. Eventually, it is hoped that this AIoT project will have a positive impact and contribute towards the implementation of IR 4.0 in bio-manufacturing-based industries to enable a healthier society. The scope of the project includes: (1) Characterisation and analysis of cell culture growth. (2) Development of a novel deep-learning algorithm to monitor cell culture characteristics and (3) validation of the model in a research or industrial environment.

This project is a multi-disciplinary collaboration with 2 other public universities in Malaysia and potentially a national governmental agency.