Most work on precision medicine focuses on developing new treatments based on an individual's genetic, environmental, and lifestyle profile. The result is a data-driven approach investigating the best treatment for an individual patient. This promising approach has led to significant advances, including an explosion of scientific research, as embodied by the Precision Medicine Initiative (PMI). This presents an information problem for clinicians, however, as the vast literature available for precision medicine can make it difficult to find the most appropriate treatment for the clinician's current patient. The ability to quickly locate relevant information for a current patient using information retrieval (IR) has the potential to be an important tool for helping clinicians find the most up-to-date evidence-based treatment for their patients.
The TREC Precision Medicine track is a specialization of the previous TREC Clinical Decision Support track. Specifically, the 2017 Precision Medicine track focuses on the case of providing clinical decision support to cancer patients with genetic variations that might impact the choice of treatment. The track uses synthetic patients developed by precision oncologists at the world-famous MD Anderson Cancer Center in Houston, TX. For each patient, participants are challenged with retrieving relevant scientific literature articles discussing potential treatments, as well as potential clinical trials for which the patient may be eligible.