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AI is enhancing preclinical drug discovery by improving the identification, design, and optimization of drug candidates through advanced computational methods.
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Machine learning and deep learning are integral to drug discovery, enabling predictive modeling of drug-target interactions and optimizing lead compounds.
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Despite advancements in AI, drug development remains costly and lengthy, with an average cost of $2.6 billion and a timeline of 10 to 15 years.
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Generative chemistry utilizes AI to create novel drug compounds, employing methods like virtual screening and molecular docking for candidate identification.
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Several AI-driven companies have successfully advanced drug candidates into clinical trials, demonstrating the practical application of these technologies.
