We are excited to announce that a new paper has been published by EVONANO members from the University of Novi Sad and the University of the West of England. This paper focuses on in-silico optimization of multi-component cancer nanotherapies. To read the full paper, check out the link at the start of this post. We will now hear from one of the authors, Michail-Antisthenis Tsompanas, on his results.
Fig. 1 – Metameric representation of two different treatments, one with 4 types of NPs and one with 6 types of NPs. All types of NPs are defined by a group of 5 parameters (different values for every type of NP).
From the author Michail-Antisthenis Tsompanas:
This study is based on the assumption that multiple types of NPs are expected to increase the robustness of the treatment, due to imposing higher complexity on the solution tackling a problem of high complexity, namely the physiology of a tumour.
The evolutionary optimization process utilizes metameric representations and appropriate crossover and mutation operators, in order to optimize both NP characteristics and the number of differentiated NPs.