Improving Drug Discovery and Development Using AI: Opportunities and Challenges
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Abstract
Artificial intelligence (AI) has emerged as a transformative tool in drug discovery and development, offering unprecedented opportunities to accelerate the identification of new drug candidates, optimize drug design, and improve clinical trial efficiency. This paper explores the role of AI in various stages of the drug development process, including drug screening, lead optimization, and biomarker discovery. By leveraging machine learning algorithms, deep learning techniques, and data-driven approaches, AI can predict molecular interactions, identify potential drug targets, and forecast clinical outcomes with higher accuracy than traditional methods. Despite these advancements, challenges such as data quality, model interpretability, and regulatory hurdles remain significant barriers to widespread adoption. This paper also discusses the ethical considerations surrounding AI applications in drug development and provides a critical analysis of future trends. The potential of AI to revolutionize the pharmaceutical industry is enormous, but overcoming these challenges will be crucial to realizing its full impact.
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