Nara Yoon

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  Cancer Modeling: Optimal Therapy Scheduling Based on a Pair of Collaterally Sensitive Drugs
  Nara Yoon

  Cancer is a disease developed by uncontrolled growth of mutated cells. To study such cancer, many different scales of researches has been carried out, from a small size of molecules to large size of organisms [1,2]. In this talk, I will give a brief overview about the range of mathematical oncology, and then talk about a recent project of a cellular scale modeling worked by my team.

  
  

  In the project, we developed a model of ordinary differential equations and study the effect of sequential therapy on heterogeneous tumors comprised of resistant and sensitivity cells. Based on the model, we figured out (i) the optimal drug-switch strategy, and (ii) how composition of sensitive and resistant cell populations changes. Beyond our analytic results, we explored an individual based stochastic model and presented the distribution of extinction times for the classes of solutions found. Taken together, our results suggest opportunities to improve therapy scheduling in clinical oncology.

  
  

  Reference

  
  

  1. Anderson, A. R., & Quaranta, V. (2008). Integrative mathematical oncology. Nature reviews. Cancer, 8(3), 227.

  
  

  2. Byrne, H. M. (2010). Dissecting cancer through mathematics: from the cell to the animal model. Nature reviews. Cancer, 10(3), 221.