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AI in drug repurposing for cancer therapies

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Artificial intelligence (AI) is transforming drug discovery by enabling the rapid identification of existing drugs with potential anti-cancer properties, a process known as drug repurposing. This approach offers a cost-effective and time-efficient alternative to traditional drug development, particularly in oncology, where the need for novel therapies is urgent. AI-driven methods, including machine learning (ML) and deep learning (DL), analyze vast datasets to uncover hidden drug-disease relationships, predict drug efficacy, and optimize therapeutic combinations. This letter highlights the transformative potential of AI in drug repurposing for cancer therapies, supported by successful examples from recent research. We also discuss the challenges and ethical considerations of integrating AI into drug repurposing efforts, emphasizing the need for robust validation and regulatory oversight to ensure patient safety and efficacy.
Title: AI in drug repurposing for cancer therapies
Description:
Artificial intelligence (AI) is transforming drug discovery by enabling the rapid identification of existing drugs with potential anti-cancer properties, a process known as drug repurposing.
This approach offers a cost-effective and time-efficient alternative to traditional drug development, particularly in oncology, where the need for novel therapies is urgent.
AI-driven methods, including machine learning (ML) and deep learning (DL), analyze vast datasets to uncover hidden drug-disease relationships, predict drug efficacy, and optimize therapeutic combinations.
This letter highlights the transformative potential of AI in drug repurposing for cancer therapies, supported by successful examples from recent research.
We also discuss the challenges and ethical considerations of integrating AI into drug repurposing efforts, emphasizing the need for robust validation and regulatory oversight to ensure patient safety and efficacy.

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