Pythia provides deep learning-driven precision in CRISPR–Cas9 genome engineering

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Pythia provides deep learning-driven precision in CRISPR–Cas9 genome engineering
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Nature Biotechnology

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Precision CRISPR–Cas9-mediated genome engineering remains challenging, particularly gene integration and editing in non-dividing cells. We present Pythia, a deep learning solution that forecasts optimal repair templates and enables predictable and accurate genome editing in diverse cellular contexts, both in vivo and in vitro.

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Fig. 1: Pythia provides AI-based predictions of repair template performance.

References

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This is a summary of: Naert, T. et al. Precise, predictable genome integrations by deep-learning-assisted design of microhomology-based templates. Nat. Biotechnol. https://doi.org/10.1038/s41587-025-02771-0 (2025).

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Pythia provides deep learning-driven precision in CRISPR–Cas9 genome engineering.
Nat Biotechnol (2025). https://doi.org/10.1038/s41587-025-02818-2

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  • DOI: https://doi.org/10.1038/s41587-025-02818-2

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