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Expanding diversity in chemical space

Nature Chemistry (2026)Cite this article

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Known chemical space has grown exponentially, driven by the repetitive use of a narrow range of reactants, reaction conditions, and reaction classes — and it is dominated by low-diversity CHNO compounds. Left unchecked, AI self-driven labs risk reinforcing this bias; however, through training with less biased chemical data — achievable through robotic and historical strategies — AI self-driven labs could instead help to expand chemical diversity.

We have expanded chemical space at an exponential rate, doubling roughly every 16 years3. Yet this growth has been uneven, with most discoveries confined to small CHNO-based organic compounds within narrow molecular weight ranges and specific structural templates (Fig. 1c)4, leaving much of the potential space untouched. This low diversity stems from repeated reliance on a small ‘toolkit’ of reactants3 used to extend the space through a reduced set of reaction classes5 under a narrow set of reaction conditions6. However, chemical space’s diversity is not inherently limited: computational studies suggest that far greater diversity is feasible7. Unlocking this potential requires identifying and addressing the factors that constrain diversification, which appear to be driven less by reaction efficiency than by cost, habit and socio-economic influences6,8.

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Fig. 1: Chemical space(s).

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  1. Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany

    Guillermo Restrepo

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  1. Guillermo Restrepo
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Correspondence to Guillermo Restrepo.

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Restrepo, G. Expanding diversity in chemical space. Nat. Chem. (2026). https://doi.org/10.1038/s41557-026-02105-w

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