SOURCE-LINKED INTELLIGENCE

Harnessing Genomic Instability with Al-Driven Adaptive Laboratory Evolution for Accelerated Yeast Bioproduction

CORDIS · observation · Publication date unknown

t (S. cerevisiae) platform, transforming a biological challenge, genomic instability, into a powerful engineering asset. Unlike traditional Adaptive Laboratory Evolution (ALE), AI-EvoYeast integrates Artificial Intelligence (AI) and Machine Learning (ML), fuelled by multi-omics data, to decipher adaptive mechanisms and build a predictive model for optimal genomic configurations. Insights from explainable AI (XAI) will then guide precise CRISPR interventions to reconstruct superior phenotypes in a stable industrial chassis. This project pioneers a highly generalisable AI-augmented evolutionary strategy. By creating a predictive platform technology estimated to slash R&D timelines by up to 50%, it will secure a sustainable, cost-effective European supply of vital proteins for the pharmaceutical and food industries. This directly supports EU strategic autonomy and leadership in the global bioeconomy. Synthetic biology, Adaptive Laboratory Evolution (ALE), AI / Machine Learning, Sustainable protein production, Polyploid yeast

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recordType

award

status

SIGNED

region

EU

value

260347.92

unit

EUR