COVIDrugNet

COVIDrugNet provides network-based analysis of drugs undergoing clinical trials for COVID-19 by integrating drug-target interactions and biological and pharmacological evidence to investigate therapeutic strategies against SARS-CoV-2 infection.

Key Features:

• Holistic overview: Aggregates data on ongoing clinical trials for COVID-19 to provide a comprehensive perspective on candidate drugs.
• Network-based analysis: Constructs and analyzes networks of drugs and molecular targets to explore drug-target interactions relevant to SARS-CoV-2.
• Integration of biological and pharmacological evidence: Combines pharmacological data with biological evidence to assess the consistency of therapeutic approaches against SARS-CoV-2.
• Dynamic dataset exploration: Enables exploratory analysis of the integrated drug-target and clinical-trial dataset.

Scientific Applications:

• Drug-target interaction analysis: Enables analysis of interactions between candidate drugs and molecular targets in the context of SARS-CoV-2 infection.
• Identification of therapeutic candidates: Supports identification and prioritization of promising drugs for COVID-19 based on network structure and integrated evidence.
• Assessment of evidence alignment: Evaluates alignment between proposed drug options and available biological and pharmacological evidence.

Methodology:

A network-based framework integrates data from ongoing clinical trials with biological and pharmacological evidence related to COVID-19, providing a dynamic platform for exploring the integrated dataset and drug-target interactions.