By Matthew Luchette January 7, 2013 | The pharmaceutical
industry could use a fortuneteller. According to a March 2010
issue of Nature Reviews Drug Discovery, drug companies spend on
average $1.8 billion dollars to bring a new therapy to market,
and that number is estimated to increase in the coming years.
This staggering figure is due in part to the lack of predictive
algorithms to help pharmaceutical companies accurately choose
successful candidate compounds before human testing begins: as
few as 1 out of every 5 drugs that enter FDA clinical testing is
eventually approved for treating patients, and the process that
can take nearly a decade. With such a high rate of attrition and
with millions of dollars wasted on developing and testing
unmarketable compounds, many drug companies are looking to
improve the way they select and develop candidate drugs. A
“crystal ball” algorithm for predicting with certainty the
clinical success of a drug at little-to-no cost to the
pharmaceutical company remains elusive. Yet