[An integrative drug discovery strategy using real-world data, in silico modeling, and network pharmacology]

Area of Science:

• Computational biology
• Pharmacology
• Bioinformatics

Context:

• Drug-induced myocarditis from immune checkpoint inhibitors.
• Trastuzumab-resistant HER2-positive breast cancer.
• Statin-induced peripheral neuropathy.

Purpose:

• To evaluate an integrated drug discovery strategy combining real-world data, in silico screening, and network pharmacology.
• To identify novel therapeutic and risk-mitigating strategies for complex diseases.

Summary:

• Transcriptomic and adverse event data suggested non-steroidal anti-inflammatory drugs may prevent immune checkpoint inhibitor-induced myocarditis.
• Cheminformatics identified novel YES1 kinase inhibitors for trastuzumab-resistant breast cancer.
• Network analysis indicated statins may protect against drug-induced peripheral neuropathy via shared pathways.

Impact:

• Demonstrates the utility of integrating diverse data modalities for drug discovery.
• Enables the identification of drug repositioning candidates and therapies that mitigate adverse events.
• Highlights a multi-layered, data-driven framework for translational drug discovery focusing on efficacy and safety.