On September 9, 2024 Cellworks Group Inc., a leader in Personalized Therapy Decision Support and Precision Drug Development, reported findings from a study using the Cellworks Platform to predict the benefits of adding chemotherapy to osimertinib treatment in patients with EGFR mutated non-small cell lung cancer (NSCLC) (Press release, Cellworks, SEP 9, 2024, View Source [SID1234646458]). Leveraging data from a real-world retrospective cohort, the biosimulation study confirmed that adding chemotherapy to osimertinib led to a higher predicted overall response rate (ORR). The study revealed that while all patients responded to the addition of chemotherapy, the magnitude of benefit varied among individuals and was intricately determined by underlying genomic abnormalities, enabling the identification of patients who would benefit from combination therapies, and others who would achieve similar outcomes without the addition of chemotherapy.
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Results from the study were showcased in a poster presentation (P1.06A.03) titled ‘Use of Biosimulation to Predict Concomitant Chemotherapy Benefit in NSCLC Patients with EGFR Mutations Being Treated with Osimertinib’ as part of the IASLC 2024 World Conference on Lung Cancer hosted by the International Association for the Study of Lung Cancer in San Diego, California on September 8, 2024.
"Osimertinib has become a standard treatment option in patients with NSCLC harboring EGFR mutations," said Dr. Charu Aggarwal, MD, MPH, Professor of Medicine, University of Pennsylvania, Associate Director, PC3I and Director, Program in Precision Oncology Innovation, Penn Center for Cancer Care Innovation; and Principal Investigator for the study. "However, while targeted therapies are generally effective for these patients, response rates can vary significantly, and the potential advantage of incorporating chemotherapy in some patients remains unclear. This study demonstrates how utilizing Cellworks biosimulation can provide valuable insights by more accurately predicting the benefit of chemotherapy, as it allows for a deeper understanding of an individual patient’s therapy response based on biosimulation of their full mutation profile."
"This study opens new potential avenues for optimizing treatment strategies in NSCLC patients with EGFR mutations," said Dr. Michael Castro, Cellworks Chief Medical Officer. "By identifying additional biomarkers that influence chemotherapy response in NSCLC patients, we gain a deeper understanding of how each patient’s unique disease profile impacts therapy effectiveness. EGFR blockade can reverse chemotherapy resistance for some patients by downregulating apoptotic blockade and DNA repair caused by EGFR. Through the use of Cellworks personalized therapy biosimulation, we can pave the way for individualized decision making to determine which patients should be offered combination therapy upfront, thereby improving survival outcomes."
Study Design
Cellworks computational biosimulation was performed in this study to evaluate the additive value of chemotherapy in patients with advanced non-small cell lung cancer (NSCLC) with EGFR mutations. A real-world retrospective cohort of 116 frontline NSCLC patients treated with osimertinib were obtained from the nationwide (US based) de-identified Flatiron Health-Foundation Medicine NSCLC clinico-genomic database (FH-FMI-CGDB). Biosimulated efficacy scores were generated for both osimertinib alone and in combination with carboplatin and pemetrexed. The study then analyzed chemotherapy-driven improvements in predicted clinical response, using the upper 95% confidence interval of the osimertinib ES as a threshold.
Study Results
The efficacy scores for osimertinib were significantly associated with clinical outcomes, confirming the predictive power of Cellworks computational biosimulation. Importantly, the biosimulated addition of chemotherapy to osimertinib led to a higher efficacy score for some patients, allowing for a more refined selection of patients, moving beyond the generalized conclusion that chemotherapy is beneficial in combination, which may apply to some, but not all, patients. The benefit of chemotherapy is unevenly distributed in the population, and biosimulation aids in the selection of which patients are most likely to get a benefit from combination compared to sequential treatment.