Final Report Summary - PBDR (The population biology of drug resistance: Key principles for a more sustainable use of drugs)
To address these questions, we first developed population biological models specific to a particular diseases system, investigating the effect of key factors on resistance evolution in a disease specific manner. However, as many of the question listed above are not unique only one disease or pathogen type, we adapted the models to other diseases in order develop a more general understanding how these key factors affect resistance evolution across different disease systems. For example, we developed population dynamical models that incorporate both the within and the between host level of competition between drug-sensitive and resistant strains, and applied these models to HIV and malaria to investigate how the epidemiological and the intra-host level feed back onto each other. Moreover, we studied the benefits and limitations of combination therapy in bacterial diseases, plant fungal infections, and cancer. Our work argues that under a wide range of conditions combination therapy performs best in preventing the emergence of drug resistance. We studied the respective contributions of standing genetic variation and de novo emergence to drug resistance, finding again that under a broad range of conditions standing genetic variation is expected to be the main contributor to drug resistance. We found that methods, models, and concepts can be successfully adapted to study resistance evolution in different disease systems and that scientific exchange across disease systems leads to considerable synergy.