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Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System

Published on: December 11, 2016

Big Data Transforms Discovery-Utilization Therapeutics Continuum.

S A Waldman¹, A Terzic²

¹Department of Pharmacology and Experimental Therapeutics, Division of Clinical Pharmacology, Department of Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.

Clinical Pharmacology and Therapeutics

|February 19, 2016

Summary

This summary is machine-generated.

Omic technologies provide deep molecular insights into health and disease. Integrating this biological data with clinical and environmental information using big data analytics is transforming modern therapeutics.

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Area of Science:

Biomedical Informatics
Genomics
Computational Biology

Background:

Omic technologies generate vast, high-dimensional biological data for understanding health and disease.
Integrating omics data with medical, demographic, and environmental datasets offers systems-level insights.

Discussion:

Big data analytics is crucial for storing, transferring, and analyzing diverse datasets.
This interdisciplinary field merges biology, medicine, and information science.

Key Insights:

Holistic molecular insights into health and disease are enabled by omic technologies.
Systems-level data integration drives healthcare evolution.
Big data analytics facilitates the merging of omics, clinical, and environmental data.

Outlook:

The integration of omics and big data is systematically transforming therapeutics.
Advancements span drug discovery, development, regulation, and utilization.
This convergence promises a new era in personalized and precision medicine.