Modernizing Study Enrollment

Faced with regulatory uncertainty and an economy struggling to stabilize, pharmaceutical companies face increasing pressure to bring new drugs to market on time and on budget. Meeting enrollment goals is one critical success factor for addressing these pressures. But enrollment has its own challenges. A lack of a standardized enrollment business process and little transparency of projected outcomes are some of the issues that contribute to enrollment difficulties. In addition, many organizations fail to utilize predictive analytics technologies to identify problems before they rear their ugly head. The end result is a clinical trial peppered with problems and delays.

Everyone in the industry is familiar with the data that indicate the average costs in bringing a new drug to market today exceed $1 billion. And delays in clinical enrollment is a significant contributor to overall trial costs and delays.

To improve trial performance and transparency, life science companies need to stop relying on manual and inconsistent processes, instinct, and last minute changes and utilize technologies that apply predictive modeling to help them stay on course during the enrollment process.

Today's predictive modeling and optimization software applications allow organizations to apply a standardized approach to run simulations and plot scenarios, to collaborate and share best practices, even on a global level.