A new precision medicine initiative at the dawn of exascale computing

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


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 languageEnglish
Article number3
JournalSignal Transduction and Targeted Therapy
Issue number1
StatePublished - Dec 2021


FundersFunder number
National Institutes of Health
National Cancer InstituteHHSN261200800001E, ZIABC010441


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