EDEN: The AI system that learns from a million species to design new treatments

"Since then, gene editing has continued to advanced, so much so that the Massachusetts Institute of Technology (MIT) listed it as one of the top 10 breakthrough technologies for 2026. The new research demonstrates this with the first generation of AI models capable of modifying and inserting genes in a programmable way: replacing defective genetic codes and reprogramming cells for therapeutic purposes, paving the way for a new generation of treatments against cancer and hereditary diseases."

"Large-scale genetic evolutionary AI models, explains De la Fuente, attempt to capture the deep logic of life by learning directly from evolution, which is, in essence, a planetary-scale optimization process because it has explored a vast space of sequences and retained configurations that work in the real world. In this way, using the natural database of DNA and proteins from countless species and ecosystems, we can learn which patterns are stable, which combinations are viable, and which structures"

Genomic code errors can cause disorders such as sickle cell anemia, predispositions to high cholesterol, or cancer. Understanding the effects and evolutionary dynamics of genetic alterations enables targeted treatments. A collaboration between major technology firms, an AI research company, and university genetic researchers applies large-scale evolutionary AI models to learn from vast natural DNA and protein databases. CRISPR/Cas molecular scissors remain central for cutting and pasting genomic sequences. First-generation AI models can programmatically modify and insert genes, replace defective codes, and reprogram cells for therapeutic purposes, leveraging evolution as a planetary-scale optimization process that identifies stable and viable sequence patterns.

Read at english.elpais.com