LDBT instead of DBTL: combining machine learning and rapid cell-free testing

Alia Clark-ElSayed, Isa Madrigal Harrison, Meagan L. Olsen, John T. Lazar, Michael C. Jewett () and Andrew D. Ellington ()
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Alia Clark-ElSayed: University of Texas at Austin
Isa Madrigal Harrison: University of Texas at Austin
Meagan L. Olsen: Northwestern University
John T. Lazar: Stanford University
Michael C. Jewett: Northwestern University
Andrew D. Ellington: University of Texas at Austin

Nature Communications, 2025, vol. 16, issue 1, 1-5

Abstract: Synthetic biology is defined by Design-Build-Test-Learn cycles. Recent advances in machine learning are changing the landscape; thus, we propose that “Learning” can precede “Design”. Moreover, adopting cell-free platforms can further accelerate “Building” and “Testing” for megascale data generation and models.

Date: 2025
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DOI: 10.1038/s41467-025-65281-2

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