Article Impact Level: HIGH Data Quality: STRONG Summary of Nature, 636(8042), 322–331. https://doi.org/10.1038/s41586-024-08280-5 Dr. Fuchu He et al.
Points
- The π-HuB project is an international initiative using advanced proteomics and AI to revolutionize healthcare by improving disease understanding, risk assessment, diagnosis, and therapeutic strategies.
- Unlike the static genome, the proteome reflects real-time health and disease states, varying across organs and over time due to environmental and health factors, making it a critical focus for the project.
- A key objective is developing a 3D digital model of human biology to predict complex diseases and analyze the impact of non-genetic factors on health, forming the basis of the π-HuB Navigator for enhanced diagnosis and prevention.
- Through the ProCan program, the Children’s Medical Research Institute provides expertise in cancer proteomics and machine learning analytics, contributing significantly to the project’s proteomic data integration efforts.
- The first phase focuses on establishing foundational technologies, data systems, and core concepts to support the project’s ambitious goals for advancing healthcare.
Summary
The π-HuB project (Proteomic Navigator of the Human Body) is a groundbreaking international initiative to leverage advanced proteomics and artificial intelligence (AI) to transform healthcare. The project’s overarching goals are to enhance our understanding of human biology, improve disease risk assessment and diagnosis, uncover new drug targets, and optimize therapeutic strategies. Led by an international consortium of researchers from academic, industrial, and government sectors, the project focuses on utilizing multimodal proteomic datasets to explore the complexities of the human proteome, which varies across organs and changes over time due to environmental and health factors. This dynamic aspect of the proteome contrasts with the static nature of the genome, providing a real-time indicator of health and disease.
One key objective of the project is to develop the “Meta Homo Sapiens model,” a 3D digital representation of human organs, tissues, fluids, and cells that evolves. This model aims to predict complex diseases and assess the impact of non-genetic factors on health. The ultimate goal is to create the π-HuB Navigator, a system designed to improve disease diagnosis, enhance early detection, and enable prevention through better prediction of health outcomes. The project’s first phase is already underway, focusing on establishing core concepts and ensuring that the necessary technological and data management systems are in place.
The CMRI (Children’s Medical Research Institute) team, including Associate Professor Qing Zhong, plays a pivotal role in the project’s data integration substream. Their contributions to proteomic technology, mainly through the ProCan program—which has been a leader in cancer proteomics—will be integral to the success of π-HuB. This program’s innovative approaches in large-scale, reproducible cancer proteomics data collection and machine learning analytics will serve as a foundation for the broader healthcare project applications.
Link to the article: https://www.nature.com/articles/s41586-024-08280-5
References He, F., Aebersold, R., Baker, M. S., Bian, X., Bo, X., Chan, D. W., Chang, C., Chen, L., Chen, X., Chen, Y.-J., Cheng, H., Collins, B. C., Corrales, F., Cox, J., E, W., Van Eyk, J. E., Fan, J., Faridi, P., Figeys, D., … Zhu, Y. (2024). π-HuB: The proteomic navigator of the human body. Nature, 636(8042), 322–331. https://doi.org/10.1038/s41586-024-08280-5
