AUTHOR=Barros de Andrade e Sousa Lisa C. , Kühn Clemens , Tyc Katarzyna M. , Klipp Edda TITLE=Dosage and Dose Schedule Screening of Drug Combinations in Agent-Based Models Reveals Hidden Synergies JOURNAL=Frontiers in Physiology VOLUME=6 YEAR=2016 URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2015.00398 DOI=10.3389/fphys.2015.00398 ISSN=1664-042X ABSTRACT=

The fungus Candida albicans is the most common causative agent of human fungal infections and better drugs or drug combination strategies are urgently needed. Here, we present an agent-based model of the interplay of C. albicans with the host immune system and with the microflora of the host. We took into account the morphological change of C. albicans from the yeast to hyphae form and its dynamics during infection. The model allowed us to follow the dynamics of fungal growth and morphology, of the immune cells and of microflora in different perturbing situations. We specifically focused on the consequences of microflora reduction following antibiotic treatment. Using the agent-based model, different drug types have been tested for their effectiveness, namely drugs that inhibit cell division and drugs that constrain the yeast-to-hyphae transition. Applied individually, the division drug turned out to successfully decrease hyphae while the transition drug leads to a burst in hyphae after the end of the treatment. To evaluate the effect of different drug combinations, doses, and schedules, we introduced a measure for the return to a healthy state, the infection score. Using this measure, we found that the addition of a transition drug to a division drug treatment can improve the treatment reliability while minimizing treatment duration and drug dosage. In this work we present a theoretical study. Although our model has not been calibrated to quantitative experimental data, the technique of computationally identifying synergistic treatment combinations in an agent based model exemplifies the importance of computational techniques in translational research.