We Are Building the Medicines That Rare Disease Patients Need — With the Technology That Makes It Possible.

The Problem We Set Out to Solve

More than 300 million people worldwide live with a rare disease. The science to address many of these conditions exists — the targets are validated, the mechanisms are understood, the biology is tractable. But fewer than 5% of rare diseases have an approved treatment.

The barrier is not scientific. It is economic. Drug discovery, as it has traditionally been practiced, costs hundreds of millions of dollars and takes over a decade. That makes rare diseases — with small patient populations and uncertain commercial returns — among the least viable programs for large pharmaceutical companies to pursue.

Meanwhile, the computational tools that could change this equation exist. Structural biology databases. Genomic association platforms. ADMET prediction models. Molecular docking algorithms. The science is mature. But access to these tools, in a form that a small team can actually use, has been locked behind enterprise software contracts priced for companies with billion-dollar budgets.

What We Built and Why

Insivio was founded on the conviction that agentic AI could collapse the cost and complexity of computational drug discovery — not incrementally, but by an order of magnitude. Not by augmenting an existing process, but by replacing the infrastructure entirely.

We built our own platform first. We used it on our own programs. We learned what worked, what failed, and what the science actually required. The result is a proprietary agentic AI system that orchestrates the full discovery pipeline — from target selection and virtual screening through ADMET profiling, freedom-to-operate analysis, and regulatory pathway design — in a unified, automated workflow.

Today, Insivio advances an in-house portfolio of small molecule and RNAi candidates targeting rare and underserved diseases. Our programs are IP-protected, preclinically advanced, and designed from the outset for Orphan Drug Designation with the FDA and the EMA. We are building assets to out-license to pharmaceutical partners who can take them through clinical development and to patients.

Why Small Molecule and RNAi

We focus on two modalities because they represent complementary approaches to different classes of therapeutic targets. Small molecule drug design gives us access to the broad landscape of enzyme, receptor, and protein targets where structure-based design and medicinal chemistry can deliver differentiated candidates. RNAi gene silencing lets us reach biology that is simply not accessible by conventional chemistry — validated targets where the disease mechanism is understood, but no small molecule solution exists.

Together, these modalities allow us to follow the science to the best target, rather than the best target that fits a single approach. That flexibility is fundamental to how we build programs.

Where We Are Going

We are a preclinical company today. Our programs are advancing toward IND-enabling studies, with orphan designation filings as the near-term regulatory milestone. Our commercial model is out-licensing — we develop candidates to a stage where the data speaks for itself, then partner with pharmaceutical and biotech companies who can take them the rest of the way.

Alongside our pipeline, we are building two products powered by the same platform: LongeviTwin, a privacy-first health digital twin for longevity optimization, and a Drug Discovery Platform that makes our computational infrastructure available to researchers and institutions who cannot access enterprise alternatives.

The long-term vision is a company that proves something important: that the most effective way to build a pharmaceutical pipeline is to build the AI infrastructure first, and let the science follow from it.