AI-NATIVE DRUG-DELIVERY ENGINEERING

The needle is an engineering constraint.
We use AI to rethink it.

Designing better injections with physics, data, and AI.

We are building a computational engineering platform around a patent-pending supported-needle architecture. Real hardware. Physical evidence. A new space to explore.

Explore the platform ↗For investors →
GNU / SUPPORTED-NEEDLE ARCHITECTUREFIG. 01
Conceptual engineering schematic of a needle and its surrounding support architecture
CONCEPTUAL SCHEMATIC PHYSICAL SYSTEM → DESIGN SPACE
THE FOUNDATIONPatent-pending architectureNSF-backed engineeringPhysical prototype testingOur story ↗

01 / THE PHYSICAL BREAKTHROUGH

Rethink the support.
Open the design space.

A smaller needle.
A demanding delivery problem.
A different starting point.

Inside the architecture ↗

Needle geometry has to reconcile competing demands: structural stability, flow, insertion depth, and the properties of the medicine itself. Changing one variable changes the problem.

gNu considers the needle together with the structure supporting it. This patent-pending architecture gives us a distinct physical system to investigate—and a richer set of engineering choices.

Our initial focus is intramuscular delivery, where reaching the intended tissue means length cannot simply be shortened. We want to explore how support, geometry, and fluid behavior can be engineered together.

INVENTION → EVIDENCE → INTELLIGENCE

The architecture grew from engineering insight, NSF-backed development, and physical prototype testing. Computation is the next chapter.

02 / THE PLATFORM WE ARE BUILDING

Every experiment
should make the
next one smarter.

Our platform direction connects proprietary physical test data, physics-informed models, and AI-guided optimization in one learning loop.

Models propose where to look. Hardware tells us what holds up. The goal is a repeatable way to explore design choices and prioritize the next physical experiment.

Explore the development roadmap ↗
  1. 01

    DEFINE

    Start with a delivery challenge. Set the constraints.

  2. 02

    COMPUTE

    Explore mechanics, flow, and candidate geometry.

  3. 03

    BUILD

    Turn a promising design into physical hardware.

  4. 04

    TEST

    Measure what happens under defined conditions.

  5. 05

    LEARN

    Use physical evidence to refine the model.

COMPUTE AGAIN WITH WHAT THE HARDWARE TAUGHT US

03 / WHERE PHYSICS MEETS POSSIBILITY

A platform built around
real constraints.

Useful intelligence begins with a precise question. We are bringing the physical and computational pieces together around delivery challenges that matter.

01 / MECHANICS

Support changes
the equation.

Investigate how the needle and its supporting structure work together across geometry, material, and loading conditions.

02 / FLUID BEHAVIOR

Design for the
medicine, too.

Study delivery alongside formulation properties, flow requirements, and the mechanical constraints of the device.

03 / PHYSICAL EVIDENCE

The test is part
of the model.

Connect measurements to their conditions. Use disagreements between prediction and reality to inform the next iteration.

04 / BUILD THE NEXT CHAPTER

For people who see
the possibility in
atoms and algorithms.

We are seeking investors, drug-delivery teams, and engineering partners to help turn a distinctive physical invention into a disciplined development platform.

Partner with gNu ↗