Cellworks Personalized Biosimulation Study Identifies Novel MDS Biomarkers and Immune Modulation Predictive of Therapy Response
CellworksGroup, Inc., a world leader in Personalized Medicine in the key therapeutic areas of Oncology and Immunology, today announced the results from two clinical studies using the Cellworks Biosimulation Platform and Computational Omics Biology Model (CBM) to predict therapy response for individual MDS patients were featured in two poster presentations at the 63rd American Society of Hematology (ASH) Annual Meeting and Exposition held December 11-14, 2021 in Atlanta, Georgia. The complete results from these clinical studies are available online in the ASH Meeting Library as Abstract 2615 and Abstract 3690.
In the ASH Abstract 2615 study, the Cellworks Biosimulation Platform and CBM identified genomic and molecular markers for decitabine (DAC) plus valproic-acid (VPA) treatment response in patients with Myelodysplastic Syndromes (MDS). In the ASH Abstract 3690 study, the Cellworks Biosimulation Platform and CBM identified immune modulation as a key pathway for predicting azacitidine (AZA) response in MDS.
“There is a need for a predictive clinical approach that can stratify MDS patients according to their chance of a favorable outcome from current therapies, while also identifying and predicting their responses to new and emerging treatment options,” said Dr. Michael Castro, MD, Chief Medical Officer at Cellworks. “Ideally, patients predicted to be non-responders could be offered to participate in a clinical trial for a new therapy or combination treatment where they were predicted to have a higher likelihood of response based on their genetic biomarkers. By using Cellworks MDS biomarker identifications and therapy response predictions in advance of participation in a clinical trial, pharmaceutical companies can increase the success rate of trials and accelerate the approval timeframe for new treatments.”
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. By reliably predicting an individual patient’s therapy response prior to receiving the treatment, the Cellworks Platform can guide selection of the optimal treatment, help patients avoid ineffective therapies and improve patient outcomes.