On August 9, 2022 Cellworks Group, Inc., a world leader in Personalized Medicine in the key therapeutic areas of Oncology and Immunology, reported results from the myCare-203A study, which demonstrate that the Cellworks Biosimulation Platform and Singula Therapy Response Index (TRI) was strongly predictive of Overall Survival (OS) for non-small cell lung cancer (NSCLC) patients and can provide personalized therapy decision guidance (Press release, Cellworks, AUG 9, 2022, View Source [SID1234617960]). In the study, Singula Therapy Response Index (TRI) provided patient-specific scores that demonstrated predictive value of OS beyond NCCN-guideline genomic biomarkers, physician-prescribed treatments and standard clinical factors such as the patient’s age and sex.

Schedule your 30 min Free 1stOncology Demo!
Discover why more than 1,500 members use 1stOncology™ to excel in:

Early/Late Stage Pipeline Development - Target Scouting - Clinical Biomarkers - Indication Selection & Expansion - BD&L Contacts - Conference Reports - Combinatorial Drug Settings - Companion Diagnostics - Drug Repositioning - First-in-class Analysis - Competitive Analysis - Deals & Licensing

                  Schedule Your 30 min Free Demo!

The results from the myCare-203A clinical study were featured in a poster presentation at the IASLC 2022 World Conference on Lung Cancer hosted by the International Association for the Study of Lung Cancer and held in Vienna, Austria from August 6-9, 2022.

"The current population-based cancer therapy guidelines do not consider the full biological complexity of an individual patient’s disease and therefore may limit the patient’s duration of therapy response and overall effectiveness of the treatment," said Dr. Mark Klein, Staff Physician, Hematology/Oncology Section, Minneapolis VA; Associate Professor, Division of Hematology, Oncology and Transplantation, University of Minnesota; and Co-Principal Investigator of the myCare-203A clinical study. "In contrast to population-based therapy guidelines, the Cellworks Biosimulation Platform produces personalized therapy predictions for each NSCLC patient based on a patient-specific multi-omic disease model. The myCare-203A study found that the personalized approach of Cellworks Singula TRI produces a more precise therapeutic decision guide for patients with NSCLC."

"There are multiple approved drugs for treating NSCLC, which makes selecting the most efficacious treatment for each patient more complicated," said Dr. Apar Kishor Ganti, Staff Physician, VA Nebraska Western Iowa Health Care System; Professor in the Department of Internal Medicine, Division of Oncology/Hematology, at the University of Nebraska Medical Center; and Co-Principal Investigator of the myCare-203A clinical study. "The myCare-203A study shows us that the Cellworks Biosimulation Platform and Singula TRI can streamline the treatment decision-making process and improve NSCLC patient outcomes through personalized therapy response predictions."

The Cellworks Biosimulation Platform simulates how a patient’s personalized genomic disease model will respond to therapies prior to treatment. The platform is powered by Cellworks groundbreaking Computational Omics Biology Model (CBM), a network of 7,000+ 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 Singula biosimulation report with Therapy Response Index (TRI) scores from 0 to 100 that predict low to high therapeutic benefit.

myCare-203A Clinical Study

Background
In this study, the Cellworks Biosimulation Platform and Computational Omics Biology Model (CBM) was used to prospectively generate Singula Therapy Response Index (TRI) scores for a retrospective cohort of 453 NSCLC patients aged 39-87 (22 female, 431 male) from Veterans Affairs facilities, who were treated with physician-prescribed therapies.

Methods
Cellworks Singula TRI scores were generated for physician-prescribed therapies and 109 alternate therapies for each patient, enabling selection of optimal therapies with estimates of improvements in median OS compared to standard care. Multivariate Cox Proportional Hazards regression models were used to test the hypothesis that Cellworks Singula TRI provides predictive value of OS above and beyond physician-prescribed treatment, NCCN-guideline genomic biomarkers, patient age and patient sex.

Results and Conclusions
Multivariate analyses demonstrated that Cellworks Singula TRI is a significant predictor of OS and provided predictive value of OS above and beyond physician-prescribed treatment, NCCN-guideline genomic biomarkers, patient age and patient sex. These results show that physicians can use Cellworks Singula TRI scores to more precisely guide therapeutic decisions for individual patients with NSCLC.