167. From Theory to Clinic: Operationalizing Evolutionary Cancer Therapy for Metastatic Non-Small Cell Lung Cancer
Invited abstract in session ME-2: Cancer and personalised care, stream Sessions.
Monday, 15:30-17:00Room: NTNU, Realfagbygget R8
Authors (first author is the speaker)
| 1. | Arina Soboleva
|
| Institute for Health Systems Science, Delft University of Technology | |
| 2. | Kailas Honasoge
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| Institute for Health Systems Science, Delft University of Technology | |
| 3. | Eva Molnárová
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| Institute for Health Systems Science, Delft University of Technology | |
| 4. | Irene Grossmann
|
| Institute for Health Systems Science, Delft University of Technology | |
| 5. | Jafar Rezaei
|
| Engineering Systems and Services, Delft University of Technology | |
| 6. | Katerina Stankova
|
| Institute for Health Systems Science, Delft University of Technology |
Abstract
Evolutionary cancer therapy (ECT) applies principles of evolutionary game theory to prolong the effectiveness of cancer treatment by curbing the development of treatment resistance. The therapy schedule is informed by mathematical models of cancer growth and dynamically adapted based on cancer response. ECT increases the time to progression while decreasing the cumulative drug dose. However, it requires careful follow-up of disease progression with more frequent tests and doctor consultations, which is an important consideration for ECT implementation in clinics. In this study, we translate the results of patient-level ECT models to the hospital operational level to foresee the feasibility and requirements of ECT for non-small cell lung cancer (NSCLC) in clinical practice. The research has two objectives: (i) to assess the robustness of the ECT protocol considering the constraints of hospital resources, and (ii) to estimate the effect of ECT on hospital operations. We implement commonly used models of cancer growth under treatment calibrated with real-world data of NSCLC patients to determine the test frequency required for ECT. We then simulate a pool of virtual patients following ECT and evaluate the effect of the increased testing and consultation frequency for these patients on hospital operations. Our research facilitates the future implementation of ECT by estimating its impact and providing the basis for discussion and collaboration among healthcare stakeholders.
Keywords
- Modelling and simulation
- Clinical modelling
Status: accepted
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