AI is employed in drug discovery to accelerate the process of identifying potential drug candidates by utilizing machine learning algorithms and predictive modeling. It aids in virtual screening, drug target identification, and lead optimization, enabling faster and more efficient development of novel drugs and treatments.
The study in the ACS journal Medicinal Chemistry Letters offers an in-depth analysis of AI and ML methods used in generative chemistry to create synthetically feasible molecular structures. The authors recommend rigorous evaluation, experimental validation, and adherence to strict guidelines to enhance the role of AI in drug discovery and ensure the novelty and validity of AI-generated molecules.
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