Review of Optimization Methods for Cancer Chemotherapy Treatment Planning

  • Sbeity H
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Abstract

Volume 8(1) 074-095 (2015) -75 J Comput Sci Syst Biol ISSN: 0974-7230 JCSB, an open access journal the patient and their medical history, personal preferences and other relevant factors. Typically, chemotherapy is administered into the veins through an injection—this mode of injecting the drug into the vein is known as intravenous chemotherapy. Chemotherapy can also be administered orally with the help of tablets and capsules; this method is known as oral chemotherapy. Chemotherapy drugs can be injected directly into the muscles, known as intramuscular injection, or beneath the skin's surface, called subcutaneous injection. In intravenous chemotherapy, the drug reaches the blood stream directly [12]. Although clinical trials have been used to determine the most reliable and efficient chemotherapy treatment plans, they are limited by high costs, long trial times, and the difficulty of having to test multiple options. In addition to the treatment cost and the effectiveness of the chemotherapy plan, its feasibility should also be evaluated. All of these steps multiply the cost; for this reason, we are studying chemotherapy treatment planning as an optimization problem using a mathematical model. As several researchers note, further refinement of chemotherapy will require attention to rigorously derived models because clinical empiricism can be an inefficient method of understanding and developing a treatment strategy [13,14]. To this end, Mathematical modeling provides a low-cost method to evaluate different treatment strategies more efficiently, quantifying the relationships among several important factors, such as the population of cancerous cells, toxicity, and drug resistance. Mathematical models also aid researchers in understanding the effects of other variables, such as the tumor growth and drug infusion rates, on the performance of the optimal treatment plan. Therefore, there is a growing interest among researchers on the problem of chemotherapy treatment optimization. A close collaboration with an oncologist will improve the model, making the research more practical and meaningful.

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Sbeity, H. (2015). Review of Optimization Methods for Cancer Chemotherapy Treatment Planning. Journal of Computer Science & Systems Biology, 8(2). https://doi.org/10.4172/jcsb.1000173

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