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EVONANO platform makes virtual tumour growth and drug design possible


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Pioneering new research paves the way for A.I. developed nanomedicines that target cancer cells more efficiently.

EVONANO allows virtual tumours to optimise design of nanoparticle-based drugs before they are tested on patients.

Could prove useful in the development of targeted cancer treatments without the need for extensive trial and error.

"The physiological effect of tweaking nanoparticle parameters can now be simulated at the level of detail that is nearly impossible to achieve experimentally," lead author Igor Balaz explained.

Nanoparticles are tiny vehicles that can be engineered to transport drugs to tumours.

Their design changes their ability to move in the body, and correctly target cancer cells.

Using a machine learning technique called artificial evolution, the researchers fine tune designs.

Platform will be used to discover new nanoparticle strategies that can be tested in the laboratory.

The software is open source, so there is hope other researchers will use it to build their own AI-powered cancer nanomedicine.

Research by University of Novi Sad published in Nature journal Computational Materials.

AI-powered software can be an alternative for expensive and extensive lab work

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Nanoparticle design platform to create evolving solutions for cancer treatment

Igor Balaz

Project Leader of EVO-NANO and Assistant Professor in University of Novi Sad

npj Computational Materials

Nature Partner Journal publishing research that apply computational approaches for the design of new materials

University of Bristol

Leading UK university researching infection, human rights, climate change, and information security.

University of Novi Sad

Public University in Serbia