Cancer treatment: new software uses artificial intelligence to grow and treat virtual tumors
EVONANO, a multidisciplinary project, brings together experts in artificial intelligence, computer science, microfluidics, modeling and medicine to propose a new research method on cancer treatment. The new software allows scientists to grow virtual tumors and use artificial intelligence (AI) to design nanoparticles to treat them.
According to Phys.org, the growth and processing of virtual tumors has become an essential step in the development of new cancer therapies, as it allows scientists to optimize the design of nanoparticle-based drugs before testing them in the laboratory. and on patients.
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Scanning electron microscope image, which shows selenium nanoparticles, ejected during femtosecond laser ablation of a bulk selenium target in distilled water. This image captured the molten “tails” of nanoparticles, which emerge as they eject from the bulk target.
EVONANO enables scientists to test the efficacy of nanoparticles for various tumors
In the article entitled “Evolutionary Computational Platform for the Automatic Discovery of Nanocarriers for Cancer Treatment” published in Computational materials of nature, the researchers showed the result of the European project called EVONANO.
The team, led by Dr Igor Balaz of the University of Novi Sad, was able to simulate simple and complex tumors with cancerous stem cells, which are difficult to treat and have an increased risk of relapse. They were able to develop virtual tumors and used artificial intelligence to identify nanoparticle design strategies that were known to be effective and created potential strategies for nanoparticle design.
Dr Balaz said the new software represents a rich platform that allows experts to test hypotheses about the effectiveness of certain nanoparticles in treating various tumors. Scientists can now refine the nanoparticles and simulate at a more detailed level that is almost impossible to achieve in experimentation.
With EVONANO, the new challenge for scientists is to design the right nanoparticle. They used artificial evolution, a machine learning technique that will help them refine nanoparticles until they are able to treat cancer while limiting potential side effects and protecting healthy cells.
Dr Balaz added that their future research on the platform will focus on growing virtual versions of tumors on patients and designing nanoparticles to suit them. This is the most important part of creating new cancer treatments that often fail. The researchers noted that the software is open source so others can create their own AI-powered anti-cancer nanoparticle drugs.
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Why are nanoparticle drugs used in cancer treatment?
Nanotechnology has been used more and more in medicine in recent years for the diagnosis, treatment and targeting of tumors. Studies have shown that nanoparticle (NP) drug delivery systems have many advantages in cancer treatments, such as precise targeting of tumor cells, reduction of side effects, good pharmacokinetics and drug resistance.
An article in Frontiers in Molecular Biosciences reported that nanoparticle-based drug delivery systems are designed based on the size and pathophysiological characteristics of the tumors they are intended to target. They are designed to kill tumors and perform the roles of cytotoxic and gene therapy.
In addition, their size and surface characteristics improve permeability and retention to increase the half-life of NP drugs and induce their accumulation in tumors but without adversely affecting healthy cells.
Finally, a 2017 study showed that a NP-based drug delivery system can enhance immunotherapy and reverse its immunosuppressive tumor microenvironment (TME).
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