According to a story from Financial Buzz, the precision oncology company Notable has recently announced that it has opened enrollment for a new observational clinical trial that will focus on a variety of blood cancers. This study will take place at several different sites across the US. Notable is focused on improving cancer treatment through the development of a new platform to advance cancer drug development.
About The Study
Notable is hoping to recruit up to 1,000 patients for this study. The trial will collect biospecimens with matched clinical data. These specimens will be de-identified, meaning that the specimens will be recorded and used anonymously, without linking back to the identity of the individual patient. The primary goal of the trial will be the creation of a sample registry that includes clinical outcome data. The data needed for the study will be collected from the patients when they enter the study and then during regular visits for a one year period.
The study will encompass a diverse array of blood malignancies, including myeloproliferative neoplasms, multiple myeloma, chronic myeloid leukemia, acute myeloid leukemia, lymphoma, myelodysplastic syndromes, and acute lymphoblastic leukemia. Other related diseases may be included as well. As from the primary goal of the trial, the study will also seek to identify potential biomarkers that correspond with certain clinical responses and presentations, as well as correlating the results of ex vivo functional tests with clinical outcomes.
Notable is developing an automated platform that is designed to dramatically improve the treatment of these cancers. The function of this platform is to predict patient’s response to a given treatment, ideally in just a week’s time. This can improve a patient’s chances of getting the most effective therapy as promptly as possible. Notable also hopes that this technology can help speed up the development of new therapies.
A recent study concluded that Notable’s platform was able to predict retrospective patient responses with an accuracy rate of 84 percent in its current iteration. Ultimately, the data gathered from this observational trial will only increase the platform’s predictive capabilities.
