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AI in Drug Discovery
Abstract
Artificial Intelligence (AI) is transforming the field of drug discovery by enabling faster, more efficient, and cost-effective processes across all stages of pharmaceutical development. Through machine learning, deep learning, and predictive modeling, AI facilitates virtual screening of chemical compounds, predicts drug-target interactions, and assesses potential toxicity early in the pipeline. These capabilities significantly reduce time and resources traditionally required for laboratory experimentation. Additionally, AI contributes to personalized medicine by analyzing genomic and clinical data to design patient-specific therapies. Despite its advantages, AI-based drug discovery faces challenges such as data bias, lack of transparency in decision-making, and has regulatory uncertainties. This article discusses key AI methodologies, real-world applications, and emerging trends in drug discovery, emphasizing the role of AI as a transformative force in modern biomedicine.
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