Digital twins for biomedical and microgravity research
ALTDATA is an Australian deep-tech company building digital twins that help researchers compare biological conditions before committing scarce samples, lab time or a flight opportunity.
Flight data remains the final test.
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The data gap
Experiments are slow, expensive and unforgiving. That leaves research teams with small datasets and a long list of questions they cannot afford to test. Generic AI can still produce a convincing answer, but it cannot tell you whether that answer will hold when conditions change.
Prediction has become fast. Trust remains the barrier. Researchers need models that are checked against reality, clear about uncertainty and honest about where a physical experiment is still required.
The bill for that lands somewhere. More than half of preclinical research doesn’t reproduce, an estimated US$28 billion a year in the United States alone (Freedman et al., PLOS Biology, 2015). Not fraud. Mostly data that was never solid enough to build on.
We don’t claim to move that number. We work on one part of the problem: helping teams explore more possibilities in software, then spend real samples and lab time on the experiments that matter.
How it works
Synthetic Data creates evidence for a model. Inside the Digital Twin, physics provides the grounding. AI provides the speed. Uncertainty shows when to verify.
Generate useful records for a model when real data is restricted, scarce or missing important cases.
Compare biological conditions in software, then take the questions that still matter into the lab.
Proven offering · Build the dataset
A standalone synthetic-data service for teams whose real data cannot be used as it stands. Each dataset is built for a defined task and checked for fidelity and privacy risk.
Core product · Run virtual experiments
A working digital-twin engine for biological research. It helps teams choose better experiments and learn more from each physical test, rather than simply generating simulations.
Where it stands
The current engine has been checked against real public 1G biological data. We are now building the interface and supporting tools that will let research teams use it directly.
Preparing an AI analytics layer for cervical precancer screening by aligning expert-annotated data, validation criteria and the regulatory pathway before model development.
Space · microgravityALTDATA is the digital twin partner in a ResearchSat-led Australian project preparing to connect biological models with real data from a planned ISS mission.
Bring a research question, the data you have and the experiment you're deciding whether to run. We'll tell you plainly where the engine fits and where it doesn't.