A haploid-diploid evolutionary algorithm optimizing nanoparticle based cancer treatments

Tsompanas, Michail-Antisthenis; Bull, Larry; Adamatzky, Andrew; Balaz, Igor

Abstract

This paper uses a recent explanation for the fundamental haploid-diploid lifecycle of eukaryotic organisms to present a new evolutionary algorithm that differs from all previous known work using diploid representations. A form of the Baldwin effect has been identified as inherent to the evolutionary mechanisms of eukaryotes and a simplified version is presented here which maintains such behaviour. Using a well-known abstract tuneable model, it is shown that varying fitness landscape ruggedness varies the benefit of haploid-diploid algorithms. Moreover, the methodology is applied to optimise the targeted delivery of a therapeutic compound utilizing nano-particles to cancerous tumour cells with the multicellular simulator PhysiCell.

• Online Publication Date: Aug 12, 2022
• Publication Date: 2022
• Deposit Date: Feb 9, 2023
• Publicly Available Date: Aug 13, 2024
• Publisher: Springer
• Pages: 237-251
• Series Title: Part of the Emergence, Complexity and Computation book series (ECC, Volume 46)
• Series Number: 2194-7287; 2194-7295
• Edition: 1st
• Book Title: Cancer, Complexity, Computation
• Chapter Number: 10
• ISBN: 9783031043789
• DOI: https://doi.org/10.1007/978-3-031-04379-6_10
• Keywords: Baldwin; effect; diploid; NK model; cancer; nano-particles; PhysiCell
• Public URL: https://uwe-repository.worktribe.com/output/10442865
• Publisher URL: https://link.springer.com/chapter/10.1007/978-3-031-04379-6_10
• Related Public URLs: https://link.springer.com/book/10.1007/978-3-031-04379-6 /> ; https://www.springer.com/series/10624