QRGenAI

From patient to precision medicine.

QRGenAI transforms real patient biology into actionable therapeutic opportunities. It is the layer between knowing what broke and knowing what can fix it.

How it works

Six steps, in sequence.

01

Identify the genetic driver of disease

A pathogenic variant in a real patient sets the starting point. Standard genetic pipelines largely end here.

02

Decode how the mutation disrupts biological function

Mutation-specific, four-dimensional protein modelling turns a variant into a mechanism.

03

Match the mechanism with an existing drug

The engine searches approved and known molecules for one whose action fits the broken mechanism.

04

Validate in human-relevant models and patients

Cellular and animal models, then human evidence, test the hypothesis.

05

Develop new, protectable precision indications

A validated match becomes an asset with its own intellectual property position.

06

Expand into larger populations

The same validated mechanism is evaluated in related, more prevalent diseases.

Scale

What the platform has already worked through.

16TReal-world data points the platform is trained on
150+Diseases screened by the engine
180+Rare-disease cases deeply characterised
10+Approved assets identified for new indications
The learning loop

Treated patients are the ultimate evidence.

Treating patients generates data. That data sharpens the engine. A sharper engine produces better programs and better partnerships. Human outcomes are not the end of the process, they are an input to it.

Human genetics

The causal starting point, drawn from patients rather than population correlation.

Mechanistic modelling

Mutation-specific structural biology that shows how function is disrupted.

Patient-derived evidence

Clinical observation and outcomes feeding directly back into prediction.