A new precision medicine initiative at the dawn of exascale computing

Ruth Nussinov; Hyunbum Jang; Guy Nir; Chung Jung Tsai; Feixiong Cheng

doi:10.1038/s41392-020-00420-3

A new precision medicine initiative at the dawn of exascale computing

Ruth Nussinov
, Hyunbum Jang
, Guy Nir
, Chung Jung Tsai
, Feixiong Cheng

National Institutes of Health
Tel Aviv University
Harvard University
Wyss Institute for Biologically Inspired Engineering
University of Texas Medical Branch at Galveston
Cleveland Clinic Foundation
Case Western Reserve University

Research output: Contribution to journal › Article › peer-review

42 Scopus citations

Abstract

Which signaling pathway and protein to select to mitigate the patient’s expected drug resistance? The number of possibilities facing the physician is massive, and the drug combination should fit the patient status. Here, we briefly review current approaches and data and map an innovative patient-specific strategy to forecast drug resistance targets that centers on parallel (or redundant) proliferation pathways in specialized cells. It considers the availability of each protein in each pathway in the specific cell, its activating mutations, and the chromatin accessibility of its encoding gene. The construction of the resulting Proliferation Pathway Network Atlas will harness the emerging exascale computing and advanced artificial intelligence (AI) methods for therapeutic development. Merging the resulting set of targets, pathways, and proteins, with current strategies will augment the choice for the attending physicians to thwart resistance.

Original language	English
Article number	3
Journal	Signal Transduction and Targeted Therapy
Volume	6
Issue number	1
DOIs	https://doi.org/10.1038/s41392-020-00420-3
State	Published - 6 Jan 2021
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2020, The Author(s).

Funding

This project has been funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under contract HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government. This research was supported [in part] by the Intramural Research Program of NIH, National Cancer Institute, Center for Cancer Research.

Funders	Funder number
National Institutes of Health
National Cancer Institute	HHSN261200800001E, ZIABC010441

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Access to Document

10.1038/s41392-020-00420-3

Cite this

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A new precision medicine initiative at the dawn of exascale computing

Abstract

Bibliographical note

Funding

UN SDGs

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