Modeling Tumor Growth in Animals and Humans: An Evolutionary Approach

  • Dean C. BottinoEmail author
  • Arijit Chakravarty


Disease progression modeling allows more precise quantitation of therapeutic interventions, which in turn enables better decision-making in drug research and development. Cancer biology has a rich history of disease progression modeling both in the animal and patient setting, from exponential growth to carrying capacity models, not to mention enhancements that represent biochemical pathways, cell cycle state, and tumor microenvironment. Recent observations of tumor heterogeneity and treatment emergent resistance to every pharmacologic modality to date support an evolutionary approach to characterizing tumor kinetics. This approach represents an individual’s tumor burden as a collection of independently exponentially growing subpopulations with varying degrees of innate sensitivity or resistance to the therapeutic intervention being studied. A two-population simplified evolutionary model can recapitulate a wide variety of tumor kinetic trajectories observed in the clinic, including primary resistance, initial shrinkage followed by relapse, and durable response, depending on the estimated pre-existing fraction ϕR of initial tumor burden resistant to therapy. Under the assumption that tumor burden exceeding a critical threshold results in death of the patient, it can be shown that this initial resistant fraction ϕR and the growth rate gR of cells resistant to treatment are the key drivers of survival benefit, whereas the kill rate of the treatment on sensitive cells has a negligible effect on survival. By utilizing the totality of continuous tumor burden measurements over the entire course of treatment, evolutionary tumor kinetics modeling enables more accurate treatment benefit assessment and therefore better drug development decision-making than categorical, nontemporal criteria like RECIST.


Oncology Mathematical modeling Mathematical oncology Xenograft Clinical trials Evolutionary dynamics 


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© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Takeda Pharmaceuticals International Co.CambridgeUSA

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