Adelaide-based startup OmnigeniQ has unveiled a game-changing software that can digitally recreate how human proteins behave inside the body, a discovery set to have a profound impact on drug development and the future of precision medicine.

OmnigeniQ co-founder and CEO Jordana Blackman was in San Francisco in January for the Biotech Showcase, where she presented the discovery she says will potentially reshape drug development, toxicity testing and the long-term vision of biological in silico twins.

The company is modelling living systems, treating proteins and cells as dynamic, energetic fields rather than static structures. It says this shift allows for a new, physics-driven approach to understanding biology and has huge implications specifically for drug discovery and pharmaceutical progress.

“What this unlocks for modern medicine is profound. If you know the true, dynamic structure of a protein, you can design a drug that engages it with far higher specificity. That means fewer off target effects, fewer failed candidates, and a faster path to viable therapies. The industry spends billions each year on molecules that fail because their target wasn’t fully understood. Physics accurate protein computation changes that equation and gives us the ability to completely overturn the process of drug development.” – Jordana Blackman at the Biotech Showcase.

A commercial ‘pivot’

Launched in 2024 by Jordana Blackman and co-founder and chief science officer Tiffanwy Klippel-Cooper, OmnigeniQ has its origins in space technology research. Tiffanwy Klippel-Cooper, whose qualifications span medical science, genetics, pathology and biological science, with a passion for both quantum and astrophysics, started out in the space programme at the Innovation Collaboration Centre (ICC) at the University of South Australia.

She designed a bioreactor to produce insulin and other biological consumables that work in zero-gravity environments and deep space missions, including the NASA Artemis Program. “To do this we needed to understand how electromagnetic fields, microgravity and quantum scale forces influence protein folding. Those insights became the foundation of our proprietary computational framework.”

“I was looking at developing a bioreactor for deep space missions so that we would have supplies of insulin, because currently that’s one of the limiting factors – human health support in deep space missions,” she said.

“And while doing that, I had to develop a very granulated understanding of how microgravity environments or non-Earth environments impact cell cultures.

She built a virtual model to predict how proteins behave in non-Earth environments. “Proteins fold differently in space,” she said. “Pressure, gradients — all of that matters.”

But the turning point came when she tested whether the system could predict how drugs bind to proteins. The results were so successful they triggered a commercial pivot for OmnigeniQ, moving to broader applications of the research.

Future vision

Head of Technology Development and Commercialisation Rosa Miles, who has three decades of experience in drug development and cell and gene therapies, said her role was initially to validate the technology – and attempt to break it.

“My role initially was to evaluate the tool for validation and essentially try to break it,” she said.

Ms Miles said the system was tested against known drug–target interactions, including proprietary data she had worked on during her career.

“The hit rate was like nothing I’ve ever seen.”

She said despite advances in AI, core drug development methodologies remain largely unchanged.

“These methods have not changed in 30 years,” she said. “They might have been refined. They might have been high-throughput. It hasn’t changed. Filling in the gaps with AI is not the promise that everyone thought it may be.”

If the platform performs as claimed, Ms Miles said it could allow researchers to model drug-target binding, off-target toxicity and mutation-specific behaviour before laboratory testing.

“You then have the units to build, ultimately, the in-silico twin,” she said.

An in-silico twin refers to a computer-based biological replica that allows disease progression and treatment response to be simulated before real-world intervention.

The fourth member of the all-female team is Dr Lauren Urban a senior data scientist and AI researcher based in California. With a biophysics degree from Brown and a PhD in microbiology and immunology from USC, Irvine, Dr Urban  leads development and optimisation of the platform’s algorithms and bioinformatics pipelines.

OmnigeniQ is headquartered in Adelaide-based and is currently raising capital as it scales the next phase of development.