Rising drug prices are a serious concern for many Americans.
Little relief is expected as drug development costs continue to climb. As of 2016, FDA-approved drugs average $2.6 billion and 15 years of development time.
A large percentage of this effort is wasted on failed drugs. Drug candidates that make it out of the laboratory and into clinical trials have a very low success rate of around 10%.
A 2015 study suggests that the strength of association between a particular gene and medical condition can help determine the probability of generating a successful therapy.
Gene-disease links retrieved from academic databases and literature.Learn More
Data organized and loaded into a centralized database.Learn More
Metrics created to evaluate gene-disease link quality.Learn More
Comparing gene-disease links based on two key metrics.Learn More
Click on a data point to launch a pubmed search
for that gene-disease pair
Tips on interpreting the graph
Data is sourced primarily from academic researchers who share their results through a variety of public databases.
|NIH Genetics Reference||HTML||Web scrape with beautiful soup||Disease categories, few GDAs|
|DisGeNet||CSV||Download and load into pandas dataframe||>420000 GDAs|
|Human Phenotype Ontology||SQL & TSV||Query through sqlite3, ipython, and pandas||>115000 GDAs|
|DISEASES||TSV||Download and load into pandas dataframe||>470000 GDAs|
There are two metrics based on the strength of association and the number of associations for each individual gene and each individual disease.
The DisGeNet About Page has additional information concerning the strength of association metric.