Metablify provides a physics‑based, first‑principles platform that amplifies faint metabolite signals across LC‑MS samples, allowing untargeted quantification of thousands of metabolites without external standards. By aggregating signals using the law of large numbers, it improves detection sensitivity and enables rapid, large‑scale metabolomics screening for researchers in pharma, biotech, plant, and animal sciences.
Funding
$16M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Liquid Chromatography Mass Spectrometry (LC‑MS) generates extremely large, noisy datasets, making it difficult to detect low‑abundance metabolites. Conventional software often misses faint signals, limiting the ability to discover new biomarkers, drug candidates, or biologically relevant compounds.
Solution
Metablify applies physics‑based, first‑principles algorithms that amplify metabolite signals across multiple samples, effectively raising weak, noisy peaks above background. By leveraging the law of large numbers, the platform aggregates faint signals, enabling rapid, untargeted quantification of thousands of metabolites without the need for external standards. This approach transforms LC‑MS data into a more interpretable form, supporting large‑scale screening across medical, plant, and animal research. The resulting output provides accurate relative abundances that can be used for downstream statistical and biological analyses.
Target Audience
Primary users are researchers and analysts in pharmaceutical, biotech, plant science, and animal health fields who perform LC‑MS–based metabolomics and need high‑throughput, untargeted metabolite profiling.
Features
- Signal amplification algorithm that combines faint metabolite peaks across samples to improve detection sensitivity
- Physics‑based modeling of LC‑MS data that operates without requiring reference standards
- Untargeted metabolomics workflow capable of processing thousands of metabolites in large sample cohorts
- Compatibility with existing LC‑MS instruments and data formats for seamless integration
- Scalable analysis pipeline designed for population‑scale studies in biomedical, agricultural, and ecological research