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Principle of Generative Chemistry

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Jeremy Jenkins, PhD

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BioRender Team

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Description: This figure illustrates the core principle of generative chemistry, where machine learning models optimize molecular structures in a multidimensional latent space to design improved compounds. A non-optimal seed molecule is encoded into numerical representations, refined through generator models using multi-objective optimization and decoded into new structures with enhanced properties. This template is adapted from Dr. Jeremy Jenkins' keynote presentation at BioRender's virtual event, 'Mastering the AI Era: Exclusive Insights from Novartis, MIT & Top Biotech Leaders'.

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What does the Principle of Generative Chemistry template show?

This figure illustrates the core principle of generative chemistry, where machine learning models optimize molecular structures in a multidimensional latent space to design improved compounds. A non-optimal seed molecule is encoded into numerical representations, refined through generator models using multi-objective optimization and decoded into new structures with enhanced properties. This template is adapted from Dr. Jeremy Jenkins' keynote presentation at BioRender's virtual event, 'Mastering the AI Era: Exclusive Insights from Novartis, MIT & Top Biotech Leaders'.

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