Roland Piquepaille writes: "As it now costs a whopping $800 million to develop a new drug, American researchers have developed a forecasting computer model which could reduce drug development costs, saving hundreds of millions of dollars per new drug. Their Bayesian network model is based on publicly available data about 500 successful and failed new drugs. And they say that the application of their model would reduce mean capitalized expenditures by an average of $283 million per successful new drug (from $727 to $444 million). Now it remains to be seen if the pharmaceutical industry will use this forecasting tool. Read more for additional references and a chart showing the pharmaceutical industry performance for delivering new drugs when analyzed with this computer model."