Using AI to treat cancer
Nanoparticles (NPs) are small particles ranging between 1 and 100 nanometres in size. For perspective, it would take eight hundred 100-nanometre particles side by side to match the width of a human hair. These versatile NPs provide new avenues for cancer research because they can improve the accuracy of diagnosis and provide tailored treatment directly to tumours. NPs can be used to deliver drugs to cancer cells. They are engineered in such a way that they are attracted to diseased cells. This enables direct treatment of such cells.
At the forefront of cancer nanomedicine
Researchers on the EU-funded EVO-NANO project have developed revolutionary open-source software that can grow and treat virtual tumours by using AI. The AI automatically optimises the design of NPs to treat the tumours. They introduced the so-called EVONANO platform and presented their findings in the journal ‘Computational Materials’. Growing and treating virtual tumours is a major advance in the development of new cancer therapies. The medical community can use virtual tumours to enhance the design of NP-based drugs before they are tested in the lab or on patients. “Simulations enable us to test many treatments, very quickly, and for a large variety of tumours,” comments Dr Sabine Hauert, associate professor of swarm engineering at project partner University of Bristol in a press release. “We are still at the early stages of making virtual tumours, given the complex nature of the disease, but the hope is that even these simple digital tumours can help us more efficiently design nanomedicines for cancer.” Dr Hauert explains that having the software to grow and treat virtual tumours could be beneficial in developing targeted cancer treatments. “In the future, creating a digital twin of a patient tumour could enable the design of new nanoparticle treatments specialised for their needs, without the need for extensive trial and error or laboratory work, which is often costly and limited in its ability to quickly iterate on solutions suited for individual patients.”
Targeting cancer cells more efficiently
The research team used the EVONANO platform to simulate simple tumours and more complex tumours with cancer stem cells. These could be difficult to treat, and some cancer patients suffer a relapse as a result. Co-lead author Dr Igor Balaz from project coordinator University of Novi Sad elaborates: “The tool we developed in EVONANO represents a rich platform for testing hypotheses on the efficacy of nanoparticles for various tumour scenarios. The physiological effect of tweaking nanoparticle parameters can now be simulated at the level of detail that is nearly impossible to achieve experimentally.” “This was a big team effort involving computational researchers across Europe over the past three years,” concludes co-lead author Dr Namid Stillman from the University of Bristol. “I think this demonstrates the power of combining computer simulations with machine learning to find new and exciting ways to treat cancer.” The main aim of EVO-NANO (Evolvable platform for programmable nanoparticle-based cancer therapies) is to create an entirely new nanoparticle design platform for rapid development and assessment of new anticancer treatments. The project ends in March 2022. For more information, please see: EVO-NANO project website
Keywords
EVO-NANO, cancer, nanomedicine, cancer cell, nanoparticle, tumour