Abstract: Artificial intelligence (AI) can explore and sort through available data, recognize and learn patterns from the input unstructured/structured data to extract gainful insights from the input data. The integration of Artificial Intelligence (AI) in drug discovery has significantly revolutionized the pharmaceutical industry by expediting the development process and enhancing the precision of drug efficacy predictions. This paper explores key AI-driven innovations in drug discovery, including platforms like Atomwise, Insilico Medicine, and Exscientia, which utilize deep learning and machine learning for drug design, target identification, and clinical trial predictions. However, the adoption of AI also presents challenges such as data quality, regulatory compliance, and ethical considerations. By addressing these challenges, AI can further optimize the drug discovery process, leading to more effective and safer therapeutic solutions.
Keywords: Drug discovery, clinical trial predictions, drug efficacy predictions
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DOI:
10.17148/IJARCCE.2024.13635
