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September 10, 2025Open Access

The elephant in the lab: Synthesizability in generative small-molecule design

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This opinion highlights how generative models improve synthesizability in small molecules, suggesting new research directions.

Incorporating synthesizability into generative models enhances the design of small molecules and accelerates discovery.
Notable advancements in addressing the synthesizability of generated candidates promote more effective molecular design methodologies.
Despite progress, many proposed small molecules remain untested in experimental validation, limiting practical applications.
Continued focus on synthesizability is essential for bridging the gap between computational predictions and laboratory outcomes.

Papidocha et al. (2025) studied this question.

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September 10, 2025Open Access

View Full Paper

Ask AI

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Authors

This opinion highlights how generative models improve synthesizability in small molecules, suggesting new research directions.

Incorporating synthesizability into generative models enhances the design of small molecules and accelerates discovery.
Notable advancements in addressing the synthesizability of generated candidates promote more effective molecular design methodologies.
Despite progress, many proposed small molecules remain untested in experimental validation, limiting practical applications.
Continued focus on synthesizability is essential for bridging the gap between computational predictions and laboratory outcomes.

Papidocha et al. (2025) studied this question.

View Full Paper

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Bookmark