There are currently dozens of FDA-approved compounds with no clear mechanism of action. Furthermore, laboratories consistently identify promising compounds with potential therapeutic value. In order to decide whether to pursue such compounds, laboratories typically perform toxicity and efficacy experiments. These experiments are expensive, time consuming, and need to be repeated for each identified therapeutic drug candidate.
Professor Robin Dowell has developed an algorithm that allows for highthroughput identification of a drug's direct transcriptional targets. This approach also provides a critical layer of information to be assessed when deciding whether to pursue a compound as a therapeutic, thereby saving resources that would be spent in pursuing a suboptimal therapeutic lead.
It typically takes about 15 years and $800 million USD to convert a promising new compound into a drug on the market. These tangible and intangible costs reflect the complexity of the process. Because drug development return on investment (ROI) is declining, pharmaceutical companies are under pressure to either improve their success rates or reduce their cost of failure. One way these comapnies can minimize development costs and increase success rate is by employing technolgies such as Dr. Dowell's early in the screening process. Dr. Dowell's platform would also be beneficial in repositioning of exisiting FDA approved drugs that lack a clear mechanism of action.