Image from scanning electron microscope, which shows selenium nanoparticles, ejected during femtosecond laser ablation of bulk selenium target in distilled water. This image captured the melted “tails” of nanoparticles, which emerge during their ejection from the bulk target.
EVONANO, a multidisciplinary project, brings together experts in artificial intelligence, computer science, microfluidics, modeling, and medicine to offer a novel method for cancer treatment research. The new software enables scientists to grow virtual tumors and use artificial intelligence (AI) to design nanoparticles to treat them.
According to Phys.org, growing and treating virtual tumors has become an essential step in developing new therapies for cancer as it allows scientists to optimize the design of nanoparticle-based drugs before testing them in the laboratory and on the patients.
EVONANO Enable Scientists to Test Efficacy of Nanoparticles for Various Tumors
In the paper, titled “Evolutionary Computational Platform for the Automatic Discovery of Nanocarriers for Cancer Treatment” published in Nature’s Computational Materials, researchers showed the result of the European project called EVONANO.
The team, led by Dr. Igor Balaz from the University of Novi Sad, was able to simulate simple and complex tumors with cancer stem cells, which are difficult to treat and have increase chances of relapse. They were able to grow virtual tumors and used artificial intelligence to identify strategies in nanoparticles design that were known to be effective and created potential strategies for nanoparticle design.
Dr. Balaz said that the new software represents a rich platform that enables experts to test hypotheses on how effective could certain nanoparticles will be in treating various tumors. Scientists can now tweak nanoparticles and simulate at a more detailed level that is almost impossible to achieve in experimentation.
Using EVONANO, the new challenge for scientists is to design the right nanoparticle. They used artificial evolution, a machine learning technique that will help them fine-tune 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 be on growing virtual versions of the tumors on patients and designing nanoparticles that are right for them. These are the most important part of creating novel cancer treatments that often fails. Researchers noted that the software is open-source so others can build their own AI-powered cancer nanoparticle-based drugs.
Why Nanoparticle-Based Drugs are Used in Treatment for Cancer?
Nanotechnology has been increasingly used in medicine in recent years for diagnosis, treatment, and targeting tumors. Studies have shown that nanoparticle-based (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 characteristics of the pathophysiology of tumors it is intended to target. They are designed to kill the tumors and play the roles of cytotoxic and gene therapy.
Furthermore, their size and surface characteristics enhance permeability and retention to increase the half-life of NP-based drugs and induce their accumulation in tumors but without adversely affecting healthy cells.
Lastly, a 2017 study showed that an NP-based drug delivery system can enhance immunotherapy, and reverse its immunosuppressive tumor microenvironment (TME).