Advantages, Challenges, and Impact of Drug Repurposing for Cancer Treatment

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Abstract

Drug repurposing involves identifying new therapeutic uses for existing drugs, offering a cost-effective and time-efficient alternative to traditional drug discovery against cancer. Key approaches include computational, experimental, and drug-centric strategies, which have demonstrated success in targeting specific cancer types such as colorectal cancer with aspirin and BCC with itraconazole. Additionally, repurposing has shown potential in combination therapies, enhancing treatment efficacy, preventing metastasis, disrupting metabolic processes in cancer cells, improving cancer immunotherapy, and overcoming resistance mechanisms. Despite its benefits, drug repurposing faces significant obstacles, including cancer’s biological complexity, clinical trial design challenges, intellectual property barriers, biases affecting repurposing outcomes, and access to knowledge. Cancer heterogeneity complicates the development of universally effective therapies, while high costs and regulatory hurdles of clinical trials hinder rapid advancement. Furthermore, limited patent incentives reduce industry interest in repurposing projects. AI is revolutionizing drug repurposing by identifying new therapeutic targets and predicting drug interactions, yet challenges related to data quality, interpretability, and computational requirements necessitate careful integration. To overcome these barriers, collaboration between academia, industry, and regulatory bodies, alongside innovations in bioinformatics and clinical trial methodologies, is critical for advancing drug repurposing as a viable strategy for cancer treatment. This chapter explore the advantages, impacts, and challenges of drug repurposing in oncology, emphasizing its potential to accelerate the development of effective therapies while navigating obstacles such as data quality, regulatory challenges, and the necessity for comprehensive clinical validation.

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