Envision a day that cancer clinicians can ask an app to advise on immuno-oncology (IO) treatment options for a patient. That day may not be far off.
Immune-related adverse events (irAEs) are extremely common in patients being treated with checkpoint inhibitors for advanced melanoma. The type, quality, and severity of these adverse events, however, varies by treatment regimen and by patient.
The promises of Big Data are intuitively appealing: (virtually) unlimited data that will enable us to answer (virtually) any questions that we may have.
Determining the best personalized treatment for a patient will require input from a team of physicians, ideally with access to a patient’s information over time and across multiple modalities. Collecting data in a consistent, secure, and scalable manner with the ability to share across disciplines will be vital to furthering personalized medicine.
As a genitourinary medical oncologist specializing in immunotherapy for kidney and bladder cancers, I am continually striving for more ways to connect with and learn from my patients. The emerging availability of immuno-oncology (IO) drugs for the conditions I treat, as well as many other cancer types, has generated tremendous excitement amongst patients and oncologists, but there still is so much we don’t know.