Academics May Use AI To Greenlight Research Projects

Using AI, researchers and executives can evaluate which areas of study have the best chance of translating to clinical trials. Artificial intelligence may be making more inroads into how scientific research is conducted, with a new tool able to predict which research projects are most likely to move to a clinical trial. The model, developed by colleagues at the Office of Portfolio Analysis (OPA), a part of the National Institutes of Health (NIH) responsible for evaluating and prioritizing research, aims to reduce the period of time between discovery and clinical application with an'Approximate Potential to Translate' (APT) metric. This metric utilizes the OPA's massive open citation collection, which consists of over 420 million citation links, to provide a highly accurate APT value. From this, researchers and executives can evaluate which areas of study have the best chance of translating to clinical trials, and which are likely to sit unused for decades.