Predicting the risk of emergence of antibiotic resistance is an important part of drug development and research, but generally the methods used by academic researchers and the pharmaceutical industry to assess the risk of resistance evolution are inadequate. For example, serial passage, minimal prevention concentration measurements and determination of mutation rates are at best providing limited, and at worst misleading, information to use for risk assessment and stop/go decisions during drug development.
Determination of the fitness effect of the resistance is more relevant since this parameter will determine the ability of the resistant mutants to enrich after emergence. Combined with knowledge of bacterial population sizes and growth and killing dynamics at relevant infection sites this knowledge will allow improved forecasting of the risk of resistance evolution. Furthermore, since most clinically relevant resistance is due to horizontal gene transfer of pre-existing genes, prediction methods need to incorporate assessment of whether resistance genes already pre-exist in the resistome and whether these genes can transfer into pathogens and be stably maintained.