FRAMINGHAM, Mass., Sept. 18, 2020 /PRNewswire/ -- BERG, a clinical-stage biotech that employs artificial intelligence (AI) to investigate diseases and develop innovative treatments, today announced two major medical/clinical research developments on pancreatic ductal adenocarcinoma (PDAC) to be presented virtually at the European Society for Medical Oncology (ESMO) 2020 Congress taking place from September 19-21, 2020.
The first study entitled "Project Survival®: High Fidelity Longitudinal Phenotypic and Multi-omic Characterization of Pancreatic Ductal Adenocarcinoma (PDAC) for Biomarker Discovery", is the culmination of the largest existing high-fidelity characterization of pancreatic cancer from a phenotypic/adaptive multi-omic perspective. BERG's Interrogative Biology® platform was employed to identify causal relationships between existing pancreatic cancer therapies and changes in proteomic, metabolic and lipidomic responses to 253 treatment interventions and 211 progression events.
The research cohort included PDAC patients across different stages including early, locally advanced and metastatic to yield the most accurate characterization of the evolution of the disease. Throughout the course of the study, 470,000 clinical data points were gathered.
"Valid biomarkers will have a dramatically positive impact on patients suffering from pancreatic cancer," said Dr. A. James Moser, Co-Director of the Pancreas and Liver Institute at Beth Israel Deaconess Medical Center (BIDMC), and Professor of Surgery at Harvard Medical School. "The Project Survival and BPM study data cross an important threshold on the road to personalized treatment, underscoring the vital role of comprehensive and sustained research collaborations in the fight against this dreadful cancer."
Entire Cohort (n=452)
Age, yrs (IQR)
Sex, male, %
Af Am, Jewish, White, Other
5.0%, 6.3%, 92.1%,
5.2%, 7.2%, 92.4%,
Pancreatitis hx, %
Family History PDAC %
Weight Loss, lbs. median
The second study, Validation of Response and Survival Biomarkers in a Phase 2 Trial of BPM 31510—IV Advanced Refractory Pancreatic Ductal Adenocarcinoma (PDAC), identified two potential biomarkers predictive of response and overall survival in PDAC patients in response to BPM 31510-IV treatment.
The Interrogative Biology® platform was applied to patient Buffy Coat (BC) samples being treated with BERG's pancreatic drug cancer candidate, BPM 31510-IV, in a Phase 1 trial to identify novel markers. The biomarkers were then independently confirmed for utility between survival (OS), stable disease (SD), and progressive disease (PD) in a Phase 2 trial.
"PDAC is the most common type of pancreatic cancer and is an infamously devastating disease," said Dr. Niven R. Narain, BERG Co-founder, President and Chief Executive Officer. "We are fully committed to continue advancing these critical developments and leveraging our proprietary Interrogative Biology® platform to identify therapeutic improvements for patients. We're honored to present these findings at the ESMO 2020 Congress, and continue fostering partnerships with pioneers across the oncology field."
Project Survival®: High Fidelity
Validation of Response and Survival
Conference Link: https://www.esmo.org/meetings/esmo-virtual-congress-2020]
BERG LLC is a clinical-stage, artificial intelligence-powered biotech leveraging its proprietary platform, Interrogative Biology®, to map disease and revolutionize treatments across oncology, neurology and rare diseases. By taking a Back to Biology™ approach, BERG is able to identify critical biomarkers that can accelerate the discovery and development of treatments aimed at the most promising therapeutic targets and pathways. BERG has leveraged both Interrogative Biology and traditional R&D methods to develop a robust pipeline of first-in-class product candidates and diagnostics that advance bold innovations that have the potential to improve patient lives. To learn more about how we're enabling bold innovation, visit berghealth.com.
Glo Lindenmuth The Sway Effect
Email: [email protected]
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SOURCE BERG Health