Abstract

Cancer is the major public health complication in increasing life expectancy and ranked second in the cause of deaths all over the world, and colorectal cancer is the most commonly diagnosed and the third leading cause of cancer deaths. Though new drugs are added every year to the anticancer arsenal, there are many impediments to reach the drugs into the markets and to patients, viz. long drug discovery progress, expensive (cost) of new drug, adverse side effects, and inefficiency of novel agents. These barriers can be overcome by the recent revolution in drug discovery, that is, drug repurposing. These repurposed drugs are already approved drugs but failed in efficacy in human clinical trials or drugs withdrawn from markets because of safety concerns. If these drugs are used in the drug discovery process for new uses, it can effectively reduce both cost and time. Currently, many of the companies are adopting this repurposing technology to redevelop some of their Food and Drug Administration (FDA)-approved and unsuccessful molecules as innovative therapies against various diseases, including cancers. Computer-aided drug repurposing is having high-impact patients through their novel personalized treatments. In this chapter, reviews on the drug repurposing, principles and tools used in drug repurposing, various classes of drugs used against human cancers and colorectal cancer, repurposed drugs used in colon cancer, and finally computational methods used in the development of drugs through drug repurposing are discussed. Integrating the computational approaches like artificial intelligence and machine learning with omics-study and other network-based tools will help in future repurposed drugs for colon cancer treatment. The computational approaches predicted that drug discoveries should be validated with preclinical and clinical trials and finally used as a novel drug in the treatment of colon cancer.

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