Toward Personalized Computer Simulation of Breast Cancer Treatment: A Multiscale Pharmacokinetic and Pharmacodynamic Model Informed by Multitype Patient Data

Abstract

The usefulness of mechanistic models to disentangle complex multi-scale cancer processes such as treatment response has been widely acknowledged. However, a major barrier for multiscale models to predict treatment outcomes in individual patients lies in their initialization and parametrization which need to reflect individual cancer characteristics accurately. In this study we use multi-type measurements acquired routinely on a single breast tumor, including histopathology, magnetic resonance imaging, and molecular profiling, to personalize parts of a complex multi-scale model of breast cancer treated with chemotherapeutic and anti-angiogenic agents. The model accounts for drug pharmacokinetics and pharmacodynamics. We developed an open-source computer program that simulates cross-sections of tumors under 12-week therapy regimens and use it to individually reproduce and elucidate treatment outcomes of four patients. Two of the tumors did not respond to therapy, and model simulations were used to suggest alternative regimens with improved outcomes dependent on the tumor's individual characteristics. It was determined that more frequent and lower doses of chemotherapy reduce tumor burden in a low proliferative tumor while lower doses of anti-angiogenic agents improve drug penetration in a poorly perfused tumor. Furthermore, using this model we were able to predict correctly the outcome in another patient after 12 weeks of treatment. In summary, our model bridges multi-type clinical data to shed light on individual treatment outcomes. Research.

Experimental Models as Refined Translational Tools for Breast Cancer Research

“…There are also reports of the use of in silico methods combined with in vitro methods to assess the potential of new drugs as anti-cancer agents [207]. Tumors response to a single drug or a combination of drugs was already simulated [205,220], providing a very useful tool for developing more targeted and efficient drugs and for comparing the efficacy of different medicines.…”

A scalable solver for a stochastic, hybrid cellular automaton model of personalized breast cancer therapy

“…Finally, we demonstrate that it is now possible to run simulations of 2D tumor sections 500 times larger than previously. 9,10 2 | METHODS…”

“…To demonstrate the potential of our approach and algorithms, we consider an updated multi‐scale HCA model, previously used for simulating personalized breast cancer therapy 9,10 . In previous work, 9 model simulations were used to explain treatment outcomes at the level of individuals and suggest more successful regimes for tumors that did not respond to therapy. These findings were encouraging, but they were limited to small sections of the tumor with only a few hundred biological cells and were simulated on a single CPU.…”

“…These findings were encouraging, but they were limited to small sections of the tumor with only a few hundred biological cells and were simulated on a single CPU. While the new model is parameterized using the same methods as described, 9 this work is dedicated to describing the unique numerical schemes implementing the stochastic hybrid discrete‐continuum modeling. The new parallel solver allows to simulate more clinically relevant pieces of tumors and to capture the tumor heterogeneity as observed in magnetic resonance imaging (MRI) data.…”

Understanding the effect of measurement time on drug characterization

“…Mathematical models have been widely used in the study of cancer treatment going back to the 1960s when models were developed to predict the growth of tumors [18][19][20][21]. More recently, models are being used to optimize [22,23] or even personalize [24][25][26] treatment regimens for patients. While mathematical models of tumor growth have become increasingly complex [27,28], simpler ordinary differential equation (ODE) models can still help provide insight into cancer dynamics.…”