Phorecaster: Forecasting Tool Could Reduce Drug Development Costs

Filed in archive Diagnostics, Methodologies and Instrumentation , Genomics, Proteomics and Bioinformatics on February 14, 2007

A teams of researchers from the Children's Hospital Boston Informatics Program (CHIP) has developed a forecasting model called Phorecaster, to predict the probability that a given new drug would pass successfully through Phase III trials and receive New Drug Application (NDA) approval.The model used publicly available safety and efficacy data for about 500 successful and failed new drugs, and the validity was tested in a group of cancer drugs whose fates were already known.

This analysis, using summary data on industry-reported expenditures and revenues, indicated that application of the model would reduce mean capitalized expenditures by an average of $283 million per successful new drug (from $727 to $444), and increase revenues by an average of $160 million per Phase III trial (from $347 to $507 million) during the drug's first seven years on the market.

In the report published recently in Nature Reviews Drug Discovery, the authors point out that such a model could help

• eliminate unsafe investigational new drugs;


• avoid subjecting patients to unnecessary drug trials; r


• educe the cost of prescription drugs for consumers;


• and empower the industry to take risks on truly innovative new drugs, so that more get to market.

From the Phorecaster's main page:

At Phorecaster's core is a set of models that can predict regulatory (FDA) approval of investigational drugs with 78-89% accuracy, improve drug development efficiency, reduce drug development costs, eliminate unsafe or ineffective investigational new drugs, and reduce prescription drug costs without hampering research, development, and innovation in the pharmaceutical and biotechnology sectors.