**5. Conclusion**

In this chapter, we introduced agent-based modeling of cancer evolution along with methodologies for data fitting and sensitivity analysis. Although there is a long history of theoretical science in the field of cancer research, this approach has been overshadowed by experimental science until recently. However, with a recent explosive increase in cancer genome data, there is now an increasing need to integrate experimental and theoretical science. As an example, this chapter introduced methods for modeling and analyzing the evolutionary processes generating ITH, which is experimentally observed by multiregion sequencing. We also presented exemplifying applications: e.g., agent-based simulation modeling and analysis successfully demonstrated that ITH in colorectal cancer is generated by neutral evolution, which is caused by a high mutation rate and stem cell hierarchy. For cancer genome analyses, new experimental technologies are actively being developed. For example, single-cell sequencing technologies can profile IHT at the ultimate resolution [30] while liquid biopsy technologies, such as the sequencing of circulating tumor DNA, enables us to non-invasively track cancer evolution during treatment [31]. These technologies will unveil more various aspects of cancer evolution when combined with the approach introduced in this chapter. This chapter also exemplified how simulation modeling helps to solve scientific problems raised by new experimental technologies. We hope that this chapter will provides readers with some hints to solve their own problems using simulation modeling.
