ASH 2021: myCare-023 Finds Cellworks Personalized Biosimulation a Stronger Predictor of Therapy Response for AML Patients than Physician Prescribed Treatment
Results from myCare-023 Clinical Trial Featured in Oral Presentation at ASH 2021 Annual Meeting
ATLANTA, Georgia, December 14, 2021 – CellworksGroup, Inc., a world leader in Personalized Medicine in the key therapeutic areas of Oncology and Immunology, today announced results from the myCare-023 clinical trial, which found that the Cellworks Biosimulation Platform with its Therapy Response Index (TRI) reliably predicts complete response (CR) and overall survival (OS) for individual Acute Myeloid Leukemia (AML) patients beyond physician prescribed treatment. The myCare-023 study also showed that the Cellworks platform can provide personalized, molecular-based alternate treatment options for AML patients who are predicted to be non-responders to standard care therapies.
“Except for a few targeted therapies, genomic assessment has offered little guidance on treatment for AML patients,” said Dr. Guido Marcucci, MD, Chair and Professor, Department of Hematologic Malignancies Translational Science; Director, Gehr Family Center for Leukemia Research, and Chief of Leukemia Division within the Department of Hematology & Hematopoietic Cell Transplantation, City of Hope; and Principal Investigator for the myCare-023 clinical trial. “This study shows that the Cellworks Biosimulation Platform has the potential to improve treatment guidance by utilizing a comprehensive molecular genomic network to model each patient’s unique cancer and predict how they will respond to specific treatments. Through this personalized therapy biosimulation approach, we can individualize treatment selection and improve patient outcomes.”
The results from the myCare-023 clinical trial were featured as an oral presentation given by Dr. Scott Howard, MD, MSc, at the 63rd American Society of Hematology (ASH) Annual Meeting and Exposition on December 13, 2021 in Atlanta, Georgia and available online in the ASH Meeting Library as Abstract 689.
“Complete remission and cure rates for AML have significant room for improvement,” said Dr. Scott Howard, MD, MSc, University of Tennessee Health Science Center. “Comprehensive molecular profiling shows us that AML is a complex and heterogeneous disease network which impacts the efficacy of individual chemotherapeutics differently in individual patients. By using the Cellworks personalized therapy biosimulation platform to predict the impact of an individual patient’s aberrations and copy number alternations on therapy response, we can address the heterogeneous nature of AML and improve complete remission and cure rates.”
The Cellworks Biosimulation Platform simulates how a patient's personalized genomic disease model will respond to therapies prior to treatment and identifies novel drug combinations for treatment-refractory patients. The platform is powered by the groundbreaking Cellworks Computational Omics Biology Model (CBM), a network of 4,000+ human genes, 30,000+ molecular species and 100+ signaling pathways. As part of the biosimulation process, personalized disease models are created for each patient using their cytogenetic and molecular data as input to the Cellworks CBM. The Cellworks platform analyzes the impact of specific therapies on the patient’s personalized disease model and generates a SingulaTM biosimulation report with Therapy Response Index (TRI) Scores that predict the efficacy of specific chemotherapies.
“The use of genomics to guide therapy for AML patients has generally been restricted to a single-gene approach, which rarely has sufficient predictive power to be clinically useful,” said Dr. Guido Marcucci, MD. “However, comprehensive DNA sequencing used with Cellworks personalized therapy biosimulation can guide optimal treatment selection for individual patients, help patients avoid ineffective therapies and improve patient outcomes.”
Clinical Study: myCare-023
ASH Abstract 689: Therapy biosimulation using the Cellworks Computational Omics Biology Model (CBM) is predictive of individual AML patient probability of clinical response and overall survival.
Methods
Cytogenetic and molecular data obtained from clinical trials including AMLSG 07-04, Beat AML, TCGA and PubMed publications was used to create a personalized in silico models of each patient’s AML. The impact of specific AML therapies on each patient’s disease model was biosimulated to determine a treatment efficacy score by estimating the effect of chemotherapy on the cell growth score, a composite of cell proliferation, viability, apoptosis, metastasis, DNA damage and other cancer hallmarks. The mechanism of action of each therapy was mapped to each patient’s genome and biological consequences determined response.
Results
In this study, specific leukemia therapies generated a variable likelihood of benefit for individual patients. The Cellworks TRI score, scaled from 0 to 100, predicted complete response with a likelihood ratio χ12 = 52.54, p < 0.0001. The Cellworks Biosimulation Platform was able to predict treatment benefit or failure better than physician prescribed treatment alone (likelihood ratio: χ12 = 14.86, p < 0.0001). The use of therapy biosimulation to select therapy is estimated to increase odds of complete response by 19% per every 25 units of the TRI score.
TRI scores were also a significant predictor of overall survival (likelihood ratio: χ12 = 80.41, p < 0.0001) and provides predictive information above and beyond physician prescribed treatment alone (likelihood ratio χ12 = 58.70, p < 0.0001). Inclusion of the Cellworks biosimulation is estimated to reduce the hazard ratio for death above and beyond physician prescribed treatment by 16% per every 25 units of the TRI score.
In addition, predictiveness curves suggest that approximately 25% of de novo AML patients had low probability of complete response resulting in lower overall survival and could benefit substantially from inclusion of therapies and combinations identified by Cellworks biosimulation into frontline management.
Conclusions
This study found that Cellworks TRI predicts complete response and overall survival beyond physician prescribed treatment alone and the Cellworks platform provides individualized, molecular-based alternate treatment options for patients predicted to be non-responders to standard care therapies.
About Cellworks Group
Cellworks Group, Inc. is a world leader in Personalized Medicine in the key therapeutic areas of Oncology and Immunology. Using innovative multiomics modeling, computational biosimulation and Artificial Intelligence heuristics, Cellworks predicts personalized therapy responses for patients. The Cellworks Therapy Biosimulation Platform optimizes the uniqueness of each patient’s cancer by utilizing their multiomic data to create a personalized disease model using Cellworks proprietary Computational Omics Biology Model (CBM). The Cellworks Platform uses the personalized disease model to identify disease-biomarkers unique to each patient and biosimulate the patient’s responses to drugs and therapy regimens. Backed by UnitedHealth Group, Sequoia Capital, Agilent and Artiman, Cellworks has the world’s strongest trans-disciplinary team of molecular biologists, cellular pathway modelers and software technologists working toward a common goal – attacking serious diseases to improve the lives of patients. The company is based in South San Francisco, California and has a research and development facility in Bangalore, India. For more information, visit www.cellworks.life and follow us on Twitter @cellworkslife.
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