The FDA is thinking big. Under its regulatory science initiative, it's looking for high-horsepower data mining and scientific computing capabilities. It wants to use these tools during drug reviews to apply lessons learned from one study to another, to gain insight about diseases and therapies, and to understand the mechanisms that govern a treatment's success or failure.
The ideas are part of its strategic priorities, stated in Advancing Regulatory Science for Public Health: A Framework for FDA's Regulatory Science Initiative, published by the Office of the Chief Scientist last month. In it, the regulator describes how the efforts will help to enhance patient outcomes and bring the "FDA fully into the 21st century."
The document says that the regulator needs to make investments in software tools and establish collaborations to begin mining data from clinical trials, healthcare settings and biological studies. On its to-do list: Apply modeling as well as adaptive and Bayesian clinical trial designs to aid in developing novel products.
Another item on the list is an IT infrastructure upgrade that can support meta-analyses and computer models for risk assessment. Along these same lines, it hopes to use simulations to aid in risk assessment and risk communication strategies.
- here's the document