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Home Science & Environment Medical Research

Proteomics and AI unite for a new era in medicine and health care

December 12, 2024
in Medical Research
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Ambitious new program to use proteomics and AI for a new era of medicine and intelligent healthcare
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Ambitious new program to use proteomics and AI for a new era of medicine and intelligent healthcare
The project will take the advantages of latest advances in data and computational sciences to uncover composing principles of the human body, to generate a digitized model called Meta Homo Sapiens, and to build a ‘GPS’ (Global Positioning System) for the human body and the body’s states. Credit: Ï€-HuB Consortium

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 health care. To succeed, an international consortium mobilizing hundreds of cutting-edge expert teams from academia, government and industrial health sectors will be required.

It is called π-HuB (The Proteomic Navigator of the Human Body), and the overall aims and approaches for this massive project are published in 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 Ï€-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 Ï€-HuB project.

The Ï€-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 individual’s 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. It will enable prediction of complex diseases and impacts of non-genetic factors on health.

The third and ultimate goal is to “build the Ï€-HuB Navigator,” which aims to improve diagnosis and treatment of diseases, as well as enhance disease prediction, early warning and prevention.

Phase one of the project is underway, and the researchers are 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 Ï€-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.

More information:
Fuchu He et al, π-HuB: the proteomic navigator of the human body, Nature (2024). DOI: 10.1038/s41586-024-08280-5

Provided by
Children’s Medical Research Institute

Citation:
Proteomics and AI unite for a new era in medicine and health care (2024, December 12)
retrieved 12 December 2024
from https://medicalxpress.com/news/2024-12-proteomics-ai-era-medicine-health.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.




Ambitious new program to use proteomics and AI for a new era of medicine and intelligent healthcare
The project will take the advantages of latest advances in data and computational sciences to uncover composing principles of the human body, to generate a digitized model called Meta Homo Sapiens, and to build a ‘GPS’ (Global Positioning System) for the human body and the body’s states. Credit: Ï€-HuB Consortium

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 health care. To succeed, an international consortium mobilizing hundreds of cutting-edge expert teams from academia, government and industrial health sectors will be required.

It is called π-HuB (The Proteomic Navigator of the Human Body), and the overall aims and approaches for this massive project are published in 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 Ï€-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 Ï€-HuB project.

The Ï€-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 individual’s 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. It will enable prediction of complex diseases and impacts of non-genetic factors on health.

The third and ultimate goal is to “build the Ï€-HuB Navigator,” which aims to improve diagnosis and treatment of diseases, as well as enhance disease prediction, early warning and prevention.

Phase one of the project is underway, and the researchers are 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 Ï€-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.

More information:
Fuchu He et al, π-HuB: the proteomic navigator of the human body, Nature (2024). DOI: 10.1038/s41586-024-08280-5

Provided by
Children’s Medical Research Institute

Citation:
Proteomics and AI unite for a new era in medicine and health care (2024, December 12)
retrieved 12 December 2024
from https://medicalxpress.com/news/2024-12-proteomics-ai-era-medicine-health.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.



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