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Children’s Medical Research Institute (CMRI) scientists are part of an ambitious new program that aims to use a combination of proteomics and AI to contribute to a new era of medicine and intelligent healthcare. To succeed, an international consortium mobilising hundreds of cutting-edge expert teams from academia, government and industrial health sectors will be required.
Called π-HuB (The Proteomic Navigator of the Human Body), the overall aims and approaches for this massive project was published online today in the prestigious scientific journal, Nature. Unlike the genome — the entire genetic code — which is essentially identical in every organ and remains unchanged throughout our lifetime, the proteome is different in different organs and also changes over time. The proteome — all the proteins in a cell or tissue — is in constant flux because it adapts to changing conditions, and therefore provides an indicator of the state of health of our cells at any point in time.
“We anticipate that the π-HuB project will make a major contribution to biomedical research in the coming decades,” said CMRI’s Associate Professor Qing Zhong, one of the authors of the paper and an inaugural member of the consortium, who is in charge of the data integration sub-stream of the π-HuB project.
The π-HuB project has three goals. The first is to “discover principles of the human body”. The human body contains trillions of cells, which can assume different states within an individuals’ lifetime. These complexities can neither be predicted from the genome, nor have they been systematically measurable with available technologies previously. However, recent advances in proteomic technology and computational sciences now provide opportunities to investigate the intricate biology of the human body at unprecedented resolution and scale. Understanding the proteome will help unlock this understanding.
The second goal is to develop a “Meta Homo Sapiens model” which is a 3D digital representation of human organs, tissues, body fluids and cells over time, which will enable prediction of complex diseases and impacts of non-genetic factors on health.
The third and ultimate goal is to “build the π-HuB Navigator” which aims to improve diagnosis and treatment diseases, as well as enhancing disease prediction, early warning, and prevention.
Phase one of the project is underway and working to establish core concepts and demonstrate that the requirements of technology and data management are achievable. CMRI’s ProCan® program, which has been a trailblazer in cancer proteomics, has contributed to the technology that will make the π-HuB Navigator possible.
“ProCan’s pioneering work in establishing large scale, reproducible cancer proteomics data, as well as analytics and machine learning advances, has been a significant contributor to this program and will be a vital part of its success going forward,” said Professor Phil Robinson, Co-Director of ProCan and another inaugural member of the consortium.
