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In drug discovery, interest in harnessing the power of AI ramped up significantly with breakthroughs like AlphaFold, where AI predicted protein structures with astounding accuracy. AI’s initial focus was analyzing existing data, with machine learning systems excelling at tasks like predicting new drug interactions, molecular behaviors, and even biological pathways, based on troves of experimental data. ML can also aid in identifying promising drug targets by using natural language processing to analyze scientific literature.
But AI’s role is rapidly evolving. In 2024, AI is poised to transition from analyzing existing data to a more proactive drug discovery role as a predictor and collaborator. Shifts fueling the trend include the rise of generative AI, which can create novel molecular structures and predict their properties. An…