I’m thrilled to announce that we’ve developed the first-in-class generative models for metabolomics powered by our innovative platform, mzLearn! 🚀

This is truly one of the most exciting times for AI research. As #generative models like DeepSeek and ChatGPT revolutionize various fields, we are now unlocking their transformative potential in #metabolomics.

With #mzLearn, a novel data-driven algorithm, we’ve automated metabolite signal detection and instrument drift correction without the need for prior knowledge or input parameters. This breakthrough has provided a robust data foundation for developing pre-trained generative AI models in metabolomics.

Using over 20,000 blood-based metabolomics profiles from diverse cohorts, we achieved:
✅ High-fidelity metabolite signal detection at an unprecedented scale
✅ Capturing metabolite representations linked to demographic and clinical variables
✅ Improved clinical predictions, outperforming clinical-grade risk scores in renal cell carcinoma (RCC) outcomes

This milestone is especially timely, as GLP-1 drugs highlight the potential of metabolic interventions in reducing risks for cancer, diabetes, and cardiovascular diseases.
📢Read our press release for more details:📄Explore the science behind mzLearn in our preprint on bioRxiv:We’re thrilled to share this with the scientific community and invite collaborations to advance #precision #medicine.
#generative