First peer-reviewed publication highlighting Notable’s platform published today in Blood Advances
FOSTER CITY, Calif., June 23, 2020 (GLOBE NEWSWIRE) — Notable, which is redefining cancer treatment by taking a functional approach to precision oncology in hematological cancers, announced today that the results of a Stanford study using its drug sensitivity screening platform have been published in Blood Advances (June 23, 2020; Volume 4, Issue 12).
This study was designed to evaluate Notable’s drug sensitivity screening platform in patients with myelodysplastic syndrome (MDS) and related myeloid neoplasms. After piloting the platform in 33 patients, the authors conducted a prospective feasibility study, enrolling 21 MDS patients refractory to standard therapies: azacitidine (Vidaza) or decitabine (Dacogen). The primary endpoint of the study was to determine if the drug sensitivity results could be returned to a Tumor Board within a clinically actionable timeframe (<30 days) to inform personalized treatment recommendations. The study met its primary endpoint with drug sensitivity data provided to the Tumor Board at a median turnaround time of 15 days, and these data helped identify potentially useful drugs and drug combinations for MDS patients refractory to standard therapies. Among 21 patients who received a therapy that was tested in Notable’s platform, the authors demonstrated a positive predictive value of 92%, negative predictive value of 82%, and overall accuracy of 85% of the platform in predicting clinical responses.
Additional key details of the study are listed below:
- 54 patients were enrolled at Stanford University Medical Center between September 2016 and March 2019 and had a diagnosis of MDS, MDS/myeloproliferative neoplasm (MPN), or acute myeloid leukemia (AML).
- Blood samples and bone marrow aspirate samples were provided to Notable Labs, and ex vivo drug sensitivity screening was performed using Notable’s fully automated high-throughput platform, evaluating sensitivity to a panel of 74 individuals drugs and 36 drug combinations.
- Notable’s platform identified three groups of patients with distinct drug sensitivity patterns.
- Correlations were observed between genotype and phenotype, with specific gene mutations associated with distinct drug sensitivity patterns.
Notable and Stanford are currently enrolling a second cohort of patients to validate the initial data set.
“We set out to explore whether this platform could produce accurate results in a timely manner, and the answer is yes,” said Peter Greenberg, MD, Professor of Medicine (Hematology) and Director, Stanford MDS Center at Stanford University Cancer Center. “These data demonstrate the utility of this approach for identifying potentially useful and often novel therapeutic drugs for patients with myeloid neoplasms refractory to standard therapies.”
“This peer-viewed research is a substantial clinical milestone for Notable and for precision medicine in oncology,” said Laurie Heilmann, CEO of Notable. “One significant aspect of this research is the dataset Notable is amassing. Our bioinformatics and machine learning models are generating vast datasets that will help inform future drug development. These data are critical for biotech and pharma companies who want to accelerate their go-to-market. We look forward to working closely with Stanford to continue this important research.”
In Jan. 2020, Notable announced the launch of its new observational clinical trial. The trial is being conducted at multiple sites across the country and will focus on hematologic malignancies (blood cancers). The primary objective is to establish a tumor registry with annotated clinical outcomes. Exploratory objectives will include correlation of ex vivo drug screening results with clinical outcomes as well as identification of potential biomarkers that correlate clinical responses with genotype and/or phenotype. More details on Notable’s Institutional Review Board-approved clinical trial is available at https://clinicaltrials.gov/ct2/show/NCT04014764.
Notable is redefining cancer treatment by taking a functional approach to precision oncology in hematological cancers. Notable’s testing platform combines machine learning, automation and high-throughput screening directly on patient samples to predict responses to potential therapies, and ultimately determine which therapies will be most effective for specific cancers. Notable’s functional precision medicine platform will advance drug development and enable pharmaceutical companies to get new therapies to patients faster. Learn more at https://notablelabs.com/ or follow @notablelabs.