Accelerating access to safer, more effective and cost-efficient medical solutions
Improving patient outcomes
Preclinical modelling gives researchers and clinicians the power to predict how treatments will perform before they reach people. More effective and accurate models allow clinicians to test proposed therapies, like biomedical devices or drugs, so they can find the right treatment at the right time for the right patient. Researchers can optimise new drugs and devices using computer simulations or 3D tissue or organ models that are safer, faster, more accurate, less costly and reduce the need for animal testing. Better models ensure only the most promising treatments advance into human clinical trials – saving time and resources while improving patient outcomes.

Transforming research into real-world solutions
We develop a variety of next-generation preclinical models to improve patient outcomes.

We discover, develop and deliver the next frontier of biomedical technologies for better patient treatment and quality of life.
Our approach includes:
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computer simulations to improve cancer treatments and radiation targeting
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AI-powered models that predict disease progression, reduce complications and optimise therapies
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3D tissue and organ models for testing drugs and regenerative solutions for bone trauma
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patient-specific simulations to guide surgery and design custom implants
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real-world refinement of models through surgical validation and implant testing
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computer and “patient-on-a-bench” models to investigate artificial heart performance under a range of physiological conditions
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fundamental research into biomechanics, cellular and tissue biology to inform accurate models.
Our researchers
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Assoc Prof Nathalie Bock
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Prof Laura Bray
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Prof Cameron Brown
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Assoc Prof Devakar Epari
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Assoc Prof Andrew Fielding
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Prof Shaun Gregory
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Prof YuanTong Gu
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Prof Travis Klein
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Prof Zhiyong Li
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Assoc Prof Paige Little
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Assoc Prof Saulo Martelli
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Dr Jacqui Mcgovern
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Dr Edmund Pickering
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Prof Peter Pivonka
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Prof Olivier Salvado
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Dr Beat Schmutz
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Dr Andrew Stephens
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Prof Yi-Chin Toh
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Dr Marie-Luise Wille
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Assoc Prof Qianqian Yang
Capability statement
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