Abstracts (first author)
The role of antiretroviral dynamics in the evolution of drug resistance in HIV
Despite the high inhibition of viral replication achieved by current anti-HIV drugs, many patients fail treatment, often with emergence of drug-resistant virus. Clinical observations show that the relationship between adherence and likelihood of resistance differs dramatically among drug classes. We developed an evolutionary model that explains these observations and predicts treatment outcomes. Our model incorporates drug pharmacokinetics and pharmacodynamics, fitness differences between susceptible and resistant strains, mutations and patient adherence measures. We show that antiviral activity falls quickly for drugs with sharp dose-response curves and short half-lives, such as boosted protease inhibitors, limiting the time during which resistance can be selected for. We find that poor adherence to such drugs causes treatment failure via growth of susceptible virus, explaining puzzling clinical observations. We examine both monotherapy and combination therapy, demonstrating how the concept of the ‘mutant selection window’ can help explain HIV resistance. Furthermore, our model predicts that certain single-pill combination therapies can prevent resistance, even in the case of imperfect adherence and “drug holidays. We use our results to prioritize a wide range of dual- and triple- therapies based on expected clinical outcomes. Our approach represents a first step for simulating clinical trials of untested anti-HIV regimens and may help in the selection of new drug regimens for investigation. More generally, we show how fluctuating drug concentrations exacerbate the problem of resistance compared to constant doses with the same time averaged concentration or inhibition level, especially when multiple mutations are needed for resistance.