More than 25 million people in the United States suffer from neuropathic pain. Currently available drugs include opioids, anti-epileptics, topicals such as lidocaine, NMDA antagonists, and tricyclic antidepressants, none of which achieve clinical significance greater than 50%. To address this problem of significant clinical need and poor clinical significance, new mechanisms of action must be identified for pain therapeutics. Genome-scale technologies such as gene expression microarray data have contributed an exponential amount of diverse biological information available to the public. The goal of this project is to analyze this data to generate new understanding of underlying biological mechanisms which can lead directly to a marketable pain therapeutic. Recently, many researchers have extracted biological pathway information from gene expression microarray experiments performed in-house. In order to take advantage of the much more diverse information contained in public microarray data, this proposal tests the feasibility of new methods to combine unstructured information from multiple public datasets to derive new insight on biological pathways underlying neuropathic pain. Newly associated pathway information is used to identify therapeutics which affect the identified pathway and which have been tested in man, but whose mechanism of action has not been previously associated with pain. The identified drugs will be validated in animal models. Since the identified therapeutic by definition is an IND, successful demonstration of efficacy in animals will lead directly to clinical phase 2 proof of concept in man during the SBIR Phase II renewal. Thus this project proposes a method to significantly reduce drug discovery and early development risk by triaging public gene expression data to progress directly to product identification and late stage clinical studies for pain therapeutics with new mechanisms of action. Neuropathic pain patients tend to become globally disabled and are heavy users of healthcare resources. Current therapies have limited efficacy and issues with side effects. The present project proposes a method to significantly reduce drug discovery and early development risk by triaging public gene expression data to progress directly to product identification and late stage clinical studies for pain therapeutics with new mechanisms of action. ? ? ?
