Cancer code research is committed to discovery of the biologic rules and mathematical laws that govern the organization and number of cells in normal human tissues (the “normal code”), and how, when those rules and laws are transformed into a modified code (the “cancer code”), they cause progressive loss of tissue organization, tumor cell overpopulation and development of cancer.
Normal tissue has a strict or formal cellular-based code embodied in its organization while cancer tissue has a relaxed or informal code. To test this hypothesis it is first necessary to discover the code for normal tissue organization in order to determine how the code becomes modified in cancer development.
To discover the codes for normal and cancerous tissue organization in terms of the biologic rules and mathematical laws that govern the organization of cells in normal human tissues, and how those rules and laws, when altered, cause progressive loss of tissue organization and cancer.
The main discovery tool will be mathematical modeling because mathematical modeling is the main method used to understand mechanisms that underlie complex systems. This computational approach will also build tumor biology into a precision science by using mathematical modeling to elucidate the dynamic cellular mechanisms that are responsible for cancer development and to use quantitative biology to validate these mechanisms. Past history shows that the major discoveries that have changed the way we understand the world have come through mathematical modeling. Indeed, many of the modern technological advances (air travel, cell phones, credit cards, computers, internet, and television; to mention just a few) that we take for granted were made possible by discoveries using mathematical modeling.
Determining how biologic rules and mathematical laws that maintain normal tissue organization, when altered, drive cancer development will clarify how to design effective therapies in cancer treatment. The potential impact of translation of this discovery into clinical practice is tremendous because of the enormity of the cancer problem worldwide. Overall, the lifetime risk that a person will develop cancer is 1:2 (50%) and that that a person will die from cancer is 1:4 (25%). Thus, among the 8 billion people alive today, it is predicted that 4 billion will develop cancer and 2 billion will die of cancer. It is quite disappointing that 60 years after the advent of chemotherapy we still fail to cure most patients with advanced cancer. Obviously we need some fresh innovative scientific approaches to accurately understand the hidden complexities that drive cancer development and growth in order to discover treatments that will save the lives of those afflicted with cancer.
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Bruce Boman – Investor