Leading Genomic Biosimulation Company Recognized for its High Performance Computing (HPC) Cloud Infrastructure
myCare-004 Study Finds Cellworks Personalized Therapy Biosimulation Provides Superior OS, DFS and TRG Predictions for GEA Patients
Computational biological modeling reveals many dysregulated signaling pathways responsible for hallmark behaviors of cancer and variable drug response in the population. A mechanistic model created for each patient using comprehensive genomic inputs can biosimulate downstream molecular effects of cell signaling and drugs for each patient’s personalized in silico virtual disease model. Singula TRI is designed to predict the outcome of specific therapies with a continuous TRI Score, 0 to 100, for each patient’s unique genomic network.
AML Biomarker Identification Can Improve Clinical Trials for New Drugs and Accelerate Drug Approvals
Over the last 15 years, precision medicine has taken initial steps in diagnosing oncogenic drivers and matching drugs that target oncogene dependencies. A new set of treatment paradigms followed with historically better, often remarkable outcomes for a group of patients with advanced and imminently fatal cancers.
Personalized Therapy Biosimulation Using Multi-Omic Data Accurately Predicts Clinical Outcomes for GBM Patients
Researchers around the world are exploring different approaches to improve our understanding of cancer. The growing need to understand the molecular mechanism of cancer genesis and progression has led to large-scale studies, like the National Institutes of Health Pan-Cancer Atlas, which is aimed at finding tissue-agnostic approaches to treating cancer. Tissue agnostic approaches where the initial genesis of cancer occurred do not impact the techniques used and are central to Cellworks biosimulation methodology.
