Simulation App Introduces Personalized Approach to Oncology Care

A groundbreaking simulation app is set to revolutionize oncology care by introducing a personalized approach to cancer treatment. Developed by initiatives for Bio-Materials Behavior (iBMB Srls), a spin-off of the University of Basilicata, the CancerMate app utilizes advanced computational modeling to predict tumor progression and treatment outcomes in patients with nonmetastatic triple-negative breast cancer.

Predictive Oncology: A Shift Towards Precision Medicine

The CancerMate app represents a significant leap in the field of predictive oncology, moving away from traditional cancer treatments towards a more precise, patient-specific approach. By integrating patient data with complex mathematical models, the app allows oncologists to anticipate treatment outcomes and adjust therapeutic strategies accordingly.

"The current treatments on the market lack personalization and precision," said Gianpaolo Ruocco, CEO of iBMB Srls. "CancerMate allows doctors to run virtual scenarios, reducing the burden on the patient and the cost of the treatment."

Advanced Modeling and Virtual Biomarkers

At the heart of CancerMate's functionality is a sophisticated mathematical model developed using COMSOL Multiphysics® software. This model incorporates virtual biomarkers, which are digital or computational indicators representing biological processes or disease characteristics. These virtual biomarkers, including personalized malignancy and pharmacodynamic efficiency, inform the app's predictions of tumor growth and treatment response over time.

The app's user interface allows for input of patient-specific data such as total observation period, patient mass, body surface area, baseline Ki67 and tumor-infiltrating lymphocytes (TILs) values, dosage, and creatinine levels. After processing this information, CancerMate provides numerical results for predicted clinical lesion values and generates a graphic displaying the progress of predicted cancer lesion volume and integrated drug concentration.

Clinical Validation and Future Applications

CancerMate has been validated against data from a clinical experiment involving patients treated with LYNPARZA® (olaparib) for nonmetastatic triple-negative breast cancer. This validation process helped identify key breast carcinoma biomarkers, including TILs and protein Ki67, which describe immune response and tumor aggressiveness, respectively.

While the current version of CancerMate is tailored for triple-negative breast cancer treated with LYNPARZA®, Ruocco indicates that the underlying technology has the potential to be adapted for other breast cancer subtypes, different types of cancer, and various drug products. This versatility positions CancerMate as a valuable tool in the broader landscape of personalized cancer treatment.

As the field of predictive oncology continues to evolve, tools like CancerMate are poised to play a crucial role in shaping the future of personalized medicine. By enabling clinicians to more accurately assess and monitor tumor lesion volumes, these innovative applications have the potential to optimize treatment durations and improve patient outcomes.