A new precision medicine initiative at the dawn of exascale computing.
Ruth NussinovHyunbum JangGuy NirChung-Jung TsaiFeixiong ChengPublished in: Signal transduction and targeted therapy (2021)
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.
Keyphrases
- artificial intelligence
- signaling pathway
- induced apoptosis
- big data
- machine learning
- pi k akt
- primary care
- deep learning
- single cell
- case report
- cell cycle arrest
- epithelial mesenchymal transition
- genome wide
- protein protein
- emergency department
- cell therapy
- gene expression
- binding protein
- amino acid
- palliative care
- transcription factor
- endoplasmic reticulum stress
- dna damage
- quality improvement
- copy number
- dna methylation
- mesenchymal stem cells
- tertiary care
- cell proliferation
- decision making