Reprogramming the Immune System with Metabolites
Computational Biology for Disease Discovery
Unlike traditional genomics approaches that target single data types, Nexus™ integrates genomics, proteomics, metabolomics, and microbiome data to discover immunometabolic intervention points.
Our multi-omics platform identifies metabolites that reprogram immune function across diseases - transforming therapeutic discovery from years and billions to weeks and thousands. We already have a 68-asset pipeline, two FDA designation approvals, and active licensing negotiations.
Validated Predictive Accuracy
Double-blind validation results demonstrate consistent high-accuracy predictions across multiple disease indications. Our confidence in efficacy and safety stems from discovering these targets already working safely in humans through observational studies and retrospective analysis of existing therapeutics.
Statistical Validation
Examples of double-blind validation & test in confusion matrices
Necrotizing Enterocolitis (NEC)
Propionic Aciduria (PA)
Citrullinemia Type 1 (CTLN1)
Systemic Juvenile Arthritis (sJIA)
From Single Assets to System-Wide Solutions
Nexus™: First platform to systematically reprogram immunity across thousands of diseases
We own the infrastructure that makes biology programmable
Available Therapeutic & Diagnostic Assets by Disease
68 therapeutic and diagnostic assets across 7 major disease categories
Therapeutic & Diagnostic Assets
Real-time development status across disease categories
Platform Summary
68 therapeutic assets discovered across 7 major disease categories with 2 FDA rare pediatric disease designations approved
Our Mission
In 2020 and 2021, DeepMind's AlphaFold solved one of biology's oldest riddles — predicting how proteins fold.
But structure isn't function. Knowing how a protein looks doesn't tell us what it does across the complex circuitry of living systems.
Turing Biosciences, founded in 2022, began with a new premise: that advanced machine learning applied to richly annotated human clinical and multi-omic data could solve the next foundational problem — the problem of combinatorial complexity in systems biology.
Our goal is to build a computational gain-and-loss-of-function engine capable of deciphering how every molecular switch alters a living network.
Our mission goes beyond science. While AI is often blamed for widening the digital divide, we believe its greatest promise is to close the biological divide — bringing curative and protective innovation to diseases and populations that markets overlook.
That's why we built Nexus — a causal-AI platform that runs hundreds of thousands of algorithmic tournaments on human data to reveal what actually drives biology.
Nexus constructs causal graphs of life's code and simulates thousands of virtual perturbations — turning data into a mechanistic rehearsal of biology itself.
From those simulations come two capabilities: the power to repair biology when it fails naturally — and to defend it when it's deliberately manipulated.