We present the EVONANO platform for the evolution of nanomedicines with application to anti-cancer treatments. EVONANO includes a simulator to grow tumours, extract representative scenarios, and then simulate nanoparticle transport through these scenarios to predict nanoparticle distribution. The nanoparticle designs are optimised using machine learning to efficiently find the most effective anti-cancer treatments. We demonstrate our platform with two examples optimising the properties of nanoparticles and treatment to selectively kill cancer cells over a range of tumour environments.
@article{arxiv.2102.00879,
title = {Evolutionary computational platform for the automatic discovery of nanocarriers for cancer treatment},
author = {Namid Stillman and Igor Balaz and Antisthenis Tsompanas and Marina Kovacevic and Sepinoud Azimi and Sebastien Lafond and Andrew Adamatzky and Sabine Hauert},
journal= {arXiv preprint arXiv:2102.00879},
year = {2021}
}