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Enabling late-stage drug diversification by high-throughput experimentation with geometric deep learning - Nature Chemistry

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Enabling late-stage drug diversification by high-throughput experimentation with geometric deep learning - Nature Chemistry

Late-stage functionalization is an economical approach to optimize the properties of drug candidates. However, the chemical complexity of drug molecules often makes late-stage diversification challenging. To address this problem, a late-stage functionalization platform based on geometric deep learning and high-throughput reaction screening was developed.

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Enabling late-stage drug diversification by high-throughput experimentation with geometric deep learning - Nature Chemistry

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Enabling late-stage drug diversification by high-throughput experimentation with geometric deep learning - Nature Chemistry

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