Drug development is a long and expensive endeavor with a low success rate. A billion dollar market, artificial intelligence (AI) applications in preclinical research are being adopted by biopharma manufacturers and CROs as well as serving as the core platform of novel biotechs and service providers. AI in the life sciences has evolved from its roots in machine learning to applications of generative AI, natural language processing, deep learning and increasingly combinations of the latter 3. These tools are being applied to accelerate target discovery as well as improve design and processing, information aggregation and synthesis, as well as the repurposing of existing drugs. Herein we define and describe leading and emerging applications of AI in preclinical drug development and provide examples of models and companies shaping this burgeoning space.

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