Speaker
Description
Cancers are complex evolving systems that adapt to therapeutic intervention through a suite of resistance mechanisms, therefore whilst the maximum tolerated dose (MTD) therapies generally achieve impressive short-term responses, they unfortunately give way to treatment resistance and tumor relapse. The importance of evolution during cancer treatment is becoming more widely accepted. However, MTD treatment strategies continue to dominate precision oncology. Adaptive therapy is an evolutionary therapy that aims to slow down the emergence of drug resistance by controlling tumor burden through competition between drug sensitive and resistant cell populations. This approach was developed through mathematical model driven insights and has been shown to work in preclinical animal models (prostate, ovarian, melanoma, breast) and in pilot clinical trials (NCT02415621; NCT05189457; NCT03543969). In this talk we will discuss how mathematical models and machine learning can be used to optimize treatment strategies \cite{scibilia2025mathematical}, including adaptive therapy, and drive Phase i (imaginary) trials \cite{kim_phase_2016}. We will highlight how mathematical model driven digital twins can: (i) Integrate patient variability; (ii) Bridge between bench and bedside; (iii) Be calibrated from historic clinical data; (iv) Drive Phase i trials; (v) Stratify and optimize treatment; (vi) Predict novel trial outcomes.
Bibliography
@article{scibilia2025mathematical,
title={Mathematical Oncology: How Modeling Is Transforming Clinical Decision-Making},
author={Scibilia, Kevin R and Gallagher, Kit and Masud, MA and Robertson-Tessi, Mark and Gatenbee, Chandler D and West, Jeffrey and Llamas, Paul and Prabhakaran, Sandhya and Gallaher, Jill and Anderson, Alexander RA},
journal={Cancer research},
volume={85},
number={24},
pages={4866--4879},
year={2025},
publisher={American Association for Cancer Research}
}
@article{kim_phase_2016,
title = {Phase i trials in melanoma: {A} framework to translate preclinical findings to the clinic},
volume = {67},
issn = {09598049},
shorttitle = {Phase i trials in melanoma},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0959804916323498},
doi = {10.1016/j.ejca.2016.07.024},
language = {en},
urldate = {2026-03-28},
journal = {European Journal of Cancer},
author = {Kim, Eunjung and Rebecca, Vito W. and Smalley, Keiran S.M. and Anderson, Alexander R.A.},
month = nov,
year = {2016},
pages = {213--222},
}
