Model‐informed target identification and validation through combining quantitative systems pharmacology with network‐based analysis

[...]in silico screening of an entire molecular network in the context of the whole genome may be more effective in identifying potential targets that simultaneously modulate multiple disease genes. [...]it facilitates exploring “multiple drugs, multiple targets, multiple pathways operating in multiple tissues” aiming at identifying optimal nodes for intervention to have maximum therapeutic effect. [...]depending on the data that are fed into an NBA framework, it can be used to connect tissue, cell, pathway, and target data at the level of an individual patient to drug response, as illustrated in Figure 1 (see Material S1 for more details). Historically, a broad spectrum of computational and modeling methods that aim to understand how drugs affect the physiological system under consideration have been referred to as “Systems Pharmacology.” [...]systems pharmacology is an umbrella term that spans the entire spectrum from qualitative to quantitative modeling approaches, that is, from biological NBA to QSP models typically used in pharmaceutical R&D. Although static NBA methods exploit the entire target interactome and provide insights on key pathways and targets, current QSP approaches are based on multiscale, physiology-based pharmacodynamic models to predict the effects of therapeutic interventions over time. 8 In our proposed new paradigm, the systems-level propagation of the target mechanism in the cell-specific and tissue-specific manner first identified by NBA (“target identification”) can subsequently be investigated through QSP models to understand if modulating the target would provide a potential therapeutic benefit (“target validation”).