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UPDATE -- Cellworks to Present 10 Abstracts at 2018 American Society of Hematology Annual MeetingSAN JOSE, Calif., Nov. 19, 2018 (GLOBE NEWSWIRE) -- Cellworks Group, Inc., a leader in Precision Medicine and a global pioneer of Therapy Response Index (TRI) technology, today announced that results from using its genomics-informed Computational Biology Modeling technology (CBM) to predict drug response within specific cancer tumors will be featured as 10 poster presentations at the American Society of Hematology (ASH) Annual Meeting and Exposition held December 1-4, 2018 in San Diego, California. “Over the past year, we have completed many studies using our AI-driven biosimulation technology to predict drug responses for tumors based the genomic data of each cancer patient,” said Yatin Mundkur, CEO of Cellworks. “The consistent high accuracy of these studies demonstrates tremendous promise for using AI-driven biosimulation to match the best therapy to individual patients the first time. This approach avoids the side-effects, costs and risks associated with nonresponsive treatments, and ultimately saves lives. We look forward to sharing the results of these studies with oncologists and cancer researchers at this year’s ASH meeting.” POSTER PRESENTATIONS Title: Predictive Analysis on Prognostic Impact of Monosomy 7 in AML and Identified Therapy Options for This Cohort Title: WT1 and BCORL1 Identified by Computational Biology Modeling Analysis of Patient Genomics Are Novel Predictors of Response to Azacitidine (AZA) and Lenalidomide (LEN) Treatment in Acute Myeloid Leukemia (AML) Title: Predicting Response to BET Inhibitor in Combination with Palbociclib / Sorafenib Using a Computational Model and Its Validation: A Beat AML Project Study Title: Computational Modeling of Multiple Myeloma Patient Genomic Signatures to Predict Treatment Outcome Title: Predicting Response to Dasatinib Using a Computational Model and Its Validation: A Beat AML Project Study Title: Clinical Validation of Treatment Response Predictions Using a Genomics Driven Computational Biology Modeling Multiple Myeloma Algorithm Title: Analysis of the Evolving MDS/AML Clones to Identify Resistance Mechanisms and Predict New Therapy Options at Relapse Using Computational Biology Modeling: Case-Studies from iCare1 Clinical Study Title: Azacitidine Response Prediction in MDS Patients with NGS Data Using a Computational Biology Modeling (CBM) Based Clinical Decision Support System Title: Predicting Carfilzomib Resistance Mechanisms and Therapeutics Using Computational Modeling of Genomics and Proteomics Title: AraC-Daunorubicin-Etoposide (ADE) Response Prediction in Pediatric AML Patients Using a Computational Biology Modeling (CBM) Based Precision Medicine Workflow Cellworks is transforming personalized cancer therapy through AI-driven biosimulation software models that represent bio molecular and physiological pathways using the genomic data of each patient. Cellworks personalized medicine predictions help transform lives through the early adoption of successful therapies, while saving time and cost across the healthcare ecosystem. Cellworks also benefits the biopharma industry through virtual clinical trials, improved target identification, lead validation and the ability to repurpose and rescue drugs. About Cellworks Group, Inc. All trademarks and registered trademarks in this document are the properties of their respective owners. Media Contacts: Michele Macpherson, Chief Business Officer |