Research Spotlight (PFNS/UWE): In silico optimization of cancer therapies with multiple types of nanoparticles applied at different times

Our teams from the University of Novi Sad and the University of the West of England have published another journal article, relating to their work on optimizing the simulation of nanotherapies.

From the author, Michail-Antisthenis Tsompanas:
We investigate the in silico optimization of cancer treatments, utilizing an open-source agent based simulator, in terms of the design parameters of multiple NPs comprising one treatment and their application times. Because the number of different NPs that will achieve the best performance is not known a priori, the evolutionary algorithm uses a variable length genome approach, namely a metameric representation and accordingly modified operators. Initial results highlight the fact that different application times have a significant effect on the robustness of a treatment, whereas, applying all NPs at earlier time slots and without the ordered sequence unveiled by the optimization process, proved to be less effective.