New Disease Targets for Old Drugs; Another Big Data Initiative

Genomic sciences and the growing interest in precision medicine are having a variety of different effects on healthcare delivery.  For example, patients are now being triaged into special clinics focusing on the most aggressive tumor types or tumors of unknown primary (see: New Clinic for High-Risk Prostate Cancer Patients at the University of Michigan; Specialized Clinic Opens for Patients with Cancer of Unknown Primary). We are also now seeing the emergence of hospital executives with portfolio emphasizing precision medicine (see: Do We Need Vice Deans/Vice Presidents for Precision Medicine?; A Closer Look at a New Yale Pathology Outreach Venture). Now comes news about the development of a new process for discovering new disease targets for old drugs. It utilizes some of the newly discovered genetic signatures for diseases and then harnesses the power of Big Data to match old drugs for new treatments of these diseases (see: Hiding in Plain Sight: Finding New Targets for Old Drugs), Below is an excerpt from the article with the details: In late 2011, mice with small-cell lung cancer had their tumors reduced by an anti­depressant called imipramine. The basis of the study was the idea that the cancer switches certain genes on, while imipramine turns them off. A neat trick, but no one would have thought to test it if it hadn’t been for analytics developed by Stanford data scientist Atul Butte. Butte thinks of diseases not in terms of symptoms but of t...
Source: Lab Soft News - Category: Pathologists Authors: Tags: Healthcare Information Technology Hospital Executive Management Hospitals and Healthcare Delivery Laboratory Industry Trends Medical Research Pathology Informatics Pharmaceutical Industry Source Type: blogs