In Personalized Medicine Feasibility Study, Stanford Medical Center, With Partners Notable and Tempus, Able to Make Rapid Personalized Treatment Recommendations for 100 Percent of Blood Cancer Patients
SAN FRANCISCO, Calif. – April 15, 2019 – Notable, which is redefining cancer treatment with a clinically validated AI platform that rapidly advances cancer drug development at a fraction of traditional costs, and Stanford University Medical Center announced today the results of a new study on the feasibility of personalized medicine. The study’s objective was to rapidly sequence MDS blood cancer samples; analyze each sample against hundreds of drugs and drug combinations; and make personalized treatment recommendations for each sample – all within a maximum of 30 days. 20 patients were represented in the study, and Stanford/Notable were able to complete their personalized recommendations withinStanford’s target of 30 days for all 20 patients. With respect to accuracy, interim clinical data demonstrated both positive and negative predictive value average of 84 percent.
Effective treatment and time-to-treatment are both essential elements of fighting cancer. Advances in personalized medicine now make it possible to analyze samples for individual patients and point physicians and patients towards the drugs and drug combinations that are likely to be most effective for their unique cancer. This technique has the potential to drastically improve the way physicians treat cancers, and save more lives.
Steps involved in the study:
– Stanford Medical Center sent the blood samples to Notable and Tempus;
– Notable analyzed hundreds of requested drugs and drug combos against each sample; Tempus did the DNA sequencing;
– The Stanford MDS tumor board combined data for each patient into a report; and
– The report and personalized treatment recommendation was then shared with physician for each patient.
“Ex vivo drug sensitivity technology must have a rapid turnaround time, accuracy and efficacy in order to be useful in the clinic,” said Peter Greenberg, MD, Professor of Medicine (Hematology) and Director, Stanford MDS Center at Stanford University Cancer Center. “Notable Lab's ex vivo drug sensitivity assay screened marrow samples we sent them from patients in our recent biologically focused feasibility trial against a collection of investigational and FDA-approved compounds. These patients had higher risk myelodysplastic syndromes (MDS) and were refractory to standard therapy. Potentially actionable therapeutic results were returned to us for the patients enrolled in our trial within a clinically actionable time frame. These data suggest the potential utility of this methodology to aid in decision-making for novel therapeutic drug selection in MDS patients with HMA-refractory disease.” Further data regarding the trial and methodology used will be presented at the upcoming European Hematology Association (EHA) annual meeting hosted in Amsterdam in June.
Notable founder Matt De Silva started the company when his own father was suffering from a deadly brain cancer – his goal was to find a way to help physicians quickly match patients with the most effective treatments. “This partnership represents the future of precision medicine because it combines the strength of molecular sequencing with next-generation functional drug sensitivity tests,” said De Silva. “It’s the type of trial I wish had existed for my dad because these approaches produce immediately actionable treatment options for physicians and their patients.”
Stanford Medical Center, Notable and Tempus are working to prepare a detailed paper on the study’s approach and results, for publication later this year.
Notable is redefining cancer treatment with a clinically validated AI platform that rapidly advances cancer drug development at a fraction of traditional costs. Notable’s approach combines AI with an automated lab to determine which drugs or combination of drugs will be most effective for specific types of cancers, enabling drug companies to recruit the right patients into clinical trials. The resulting high response rates in those trials can accelerate the process, eliminating much of the time and cost in later-stage trials, and helping to get drugs to market years faster at a lower cost to patients. Learn more at https://notablelabs.com/ or follow @notablelabs.