Cellworks Group, Inc., a world leader in Personalized Medicine in the key therapeutic areas of Oncology and Immunology, today announced results from the myCare-020-01 and myCare-020-02 clinical trials, which found that Cellworks Singula™ predicted response to standard care therapies with 92.3% accuracy for Acute Myeloid Leukemia (AML) patients and 90.3% accuracy for Myelodysplastic Syndromes (MDS) patients.
SOUTH SAN FRANCISCO, Calif., Dec. 07, 2020 (GLOBE NEWSWIRE) -- Cellworks Group, Inc., a world leader in Personalized Medicine in the key therapeutic areas of Oncology and Immunology, today announced results from the myCare-020-01 and myCare-020-02 clinical trials, which found that Cellworks Singula™ predicted response to standard care therapies with 92.3% accuracy for Acute Myeloid Leukemia (AML) patients and 90.3% accuracy for Myelodysplastic Syndromes (MDS) patients. The studies also show that Singula™ has high specificity in identifying AML and MDS patients who are unlikely to respond to physician prescribed therapies and can provide alternative treatment recommendations for these patients.
Singula™ predictions can be used to validate or reject a physician’s therapy selection decision prior to treatment, reduce patient risks and payer costs of unsuccessful treatments, and provide alternative treatment recommendations. Results from the myCare-020-01 clinical study will be featured as oral and poster abstract #989 during the all-virtual 62nd American Society of Hematology (ASH) Annual Meeting and Exposition,December 5-8, 2020. The myCare-020-02 clinical study is available online at Blood®.
Cellworks Singula™ therapy response predictions are generated through extensive biosimulation of a personalized patient disease model based on the patient’s multi-omics data. Utilizing an in-silico model of thousands of genes, Singula™ analyzes the downstream pathway impact of genomic, proteomic, transcriptomic and epigenomic aberration information on a patient’s disease. These downstream effects generate phenotypic impact, which are calculated against specific drugs or drug combinations to determine treatment efficacy.
“Despite using cytogenetic and molecular-risk stratification, the current overall outcome of AML and MDS patients remains relatively poor,” said Dr. Guido Marcucci, MD, Chair and Professor, Department of Hematologic Malignancies Translational Science, Director, Gehr; Family Center for Leukemia Research, Professor, Department of Hematology & Hematopoietic Cell Transplantation, City of Hope; and Principal Investigator for the myCare-020-01 and myCare-020-02 clinical studies. “By using Cellworks multi-omic biosimulation, we can know an individual patient’s response to drugs before treatment, thereby identifying the most efficacious therapy for each patient more quickly and improving overall outcomes for AML and MDS patients.”
“Therapy selection for AML and MDS patients is often based on information considering only cytogenetics and/or molecular aberrations and ignoring other patient-specific omics information that could potentially enable selection of more effective treatments,” said Dr. Anthony Stein, MD, Hematologist/Oncologist, Director of the Leukemia Program; Co-Director of the Gehr Family Center for Leukemia Research; Clinical Professor of Hematology & Hematopoietic Transplantation at City of Hope; and Principal Investigator for the myCare-020-01 and myCare-020-02 clinical studies. “Cellworks multi-omic biosimulation is more comprehensive and takes into consideration the downstream pathway impact of genomic, proteomic, transcriptomic and epigenomic aberrations of a patient’s disease. This unique approach can identify the precise therapy for a patient’s variant of a particular cancer.”
myCare-020-01 Clinical Study
In this study, the performance of Singula™ was evaluated in a cohort of 474 AML patients aged 2 to 85. Singula™ utilizes individual patients’ next-generation sequencing (NGS) profiles to provide a dichotomous prediction of response or non-response to the physician prescribed treatments. The clinical outcome data for these subjects, i.e., complete response (CR) and overall survival (OS), were obtained from the TCGA and other 144 PubMed publications, each including information on patients’ cytogenetics, targeted gene mutations, and/or whole exome sequencing.
Blinded to clinical outcomes, Cellworks utilized the cytogenetic and molecular data to generate a Singula™ predicted response (i.e., CR vs non-response) classification for each patient. Statistical analyses, including assessments of accuracy, sensitivity, specificity, and negative (NPV) and positive predictive (PPV) values were performed to compare the Singula™ predicted clinical response to the actual observed clinical response.
Study results show Cellworks Singula™ had 92.3% accuracy in predicting correctly observed patient complete response to the prescribed treatment with 97.3% sensitivity. Singula™ had 83.3% specificity for the non-responder patients. For each of the non-responders, Singula™ provided an alternative treatment therapy predicted to produce clinical response.
myCare-020-02 Clinical Study
Cellworks Singula™ was evaluated in an independent, randomly selected, retrospective cohort of 144 MDS patients aged 28 to 89 years (median 69). Singula™ utilizes an individual’s genomics profile to provide a dichotomous prediction of response or non-response to a given physician prescribed treatment (PPT). Outcome data for these subjects, including measurement of complete response (CR), were obtained from 42 PubMed publications, each including patient genomics data of either karyotyping, targeted gene panels, and/or whole exome sequencing.
Blinded to clinical outcomes, Cellworks utilized these data to generate a Singula™ classifier of responder vs non-responder in this MDS cohort. Statistical analyses, including assessments of accuracy, sensitivity, specificity, negative (NPV) and positive predictive (PPV) values were performed on the merged data to compare the Singula™ predicted response with the actual observed CR. Multivariate logistic regression models of complete response were performed incorporating covariates for patient age, PPT, and the Singula™ Classifier.
Study results reveal that Singula™ had 90.3% accuracy in predicting observed patient response from the physician prescribed treatment and accurately identify responders with 90.0% sensitivity. Importantly, Singula™ had 90.6% specificity for the subset of 64 patients (44.4%) that had a non-response. For 32% (17/54) of the Non-Responders patients, Singula™ provided an alternative Standard of Care treatment therapy. The remaining 37 patients were predicted to be non-responders to all remaining Standard of Care options, so did not have alternate treatment predictions.
About Cellworks Group
Cellworks Group, Inc. is a world leader in Personalized Medicine in the key therapeutic areas of Oncology and Immunology. Using innovative multi-omics modeling, computational biosimulation and Artificial Intelligence heuristics, Cellworks predicts the most efficacious therapies for patients. The Cellworks unique biosimulation platform is a unified representation of biological knowledge curated from heterogeneous datasets and applied to finding cures. 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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