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InterAx Biotech

Translating Complex Biology into Breakthrough Medicines

Most drug discovery starts from the molecule and its target. We start from the cell: we identify the response a drug must trigger there, its cellular mechanism of action, and let that biology drive the chemistry.

The challenge

Many drugs reach clinical trials with the wrong mechanism, so they fail on efficacy or safety.

90% of clinical candidates fail. Chemistry can now be optimized fast, but the drug's biology is still poorly understood: the mechanism is set early, by precedent or trial and error, and validated only in the clinic, years later.

InterAx approach

Before clinical trials, we get the mechanism right.

Conventional drug discovery focuses on the molecule, and AI-driven discovery even more so, because that is where the data is. Both barely touch the biology: what the drug triggers in the cell after it binds its target, which signals it turns up or down, how strongly, and for how long. The mechanism to aim for is assumed, not derived.

InterAx Deep Signal™ measures the cell's response over time, in living cells, and decodes it with one mechanistic model of the whole system, so the drug's cellular mechanism is derived from evidence and becomes the design target, already in discovery.

How it works →

Genes and targets
Which receptor to drug
Genomics and AI target discovery
Molecules
How a compound binds
Medicinal chemistry and generative AI, InterAx included
Cell signaling The missing layer
What the drug must trigger inside the cell: this decides efficacy and tolerability
InterAx Deep Signal™: measured over time, decoded by a mechanistic model
Organism
Does the drug work, and is it tolerated
Clinical trials and AI trial optimization; the answer is seen here first
AI

We bring AI to cell signaling, the layer where a drug's outcome is decided.

AI works where data exists and is clean: genomics to find targets, chemistry and structure to design molecules. Cell signaling has stayed out of its reach because its data is inconsistent: the same drug reads differently in every assay, cell and time point. Our mathematical model of signaling makes that data consistent, turning each experiment into mechanistic parameters, a dataset AI can learn from.

1
Molecule and structure
drug design AI widely used
2
Cell signaling
the mechanism AI unlocked by InterAx
3
Genome and gene expression
target discovery AI widely used
Pipeline

Our programs, designed from the cellular mechanism up.

In-house

GLP-1

Oral small molecule for obesity and type 2 diabetes, built on the cellular profile that gives the injectable peptides their efficacy and tolerability, a profile no oral compound reported so far has matched. Preclinical with in vivo data. IND targeted for Q4 2027.

Partnered

Metabolic program

Oral small molecule for obesity, undisclosed target. Preclinical.

Discovery

New therapeutic areas

CNS (undisclosed indication), inflammation and autoimmune disorders.

Full pipeline →

10+
years of platform development
3,000+
time-resolved assays performed
15+
GPCRs with kinetic signaling models, across classes A, B and C
1,000+
drug candidates characterized
1,000+
GPCR-ligand molecular dynamics simulations
100+
GPCR publications across the team
Traction

Backed by partners, grants and investors.

Partner
Alveus Therapeutics, collaboration and licensing agreement
Selected research collaborations
Boehringer IngelheimLundbeckInversago (acquired by Novo Nordisk)Nxera (former Sosei Heptares)
Selected grants
Horizon 2020Horizon Europe EIC PathfinderInnosuisseETH Pioneer Fellowship
Capital efficiency

For every dollar of equity raised, InterAx has secured half a dollar of non-dilutive funding.

Discuss an asset or a co-development.

More drugs should enter Phase 2 with the right mechanism. We partner differentiated GPCR candidates with pharma and biotech. If you want a candidate in a GPCR indication where the current drugs fall short on efficacy or tolerability, or are building a company around a disease area, we would like to talk.