  Broadly neutralizing antibodies are promising candidates for treatment and
prevention of HIV-1 infections. Such antibodies can temporarily suppress viral
load in infected individuals; however, the virus often rebounds by escape
mutants that have evolved resistance. In this paper, we map an in vivo fitness
landscape of HIV-1 interacting with broadly neutralizing antibodies, using data
from a recent clinical trial. We identify two fitness factors, antibody dosage
and viral load, that determine viral reproduction rates reproducibly across
different hosts. The model successfully predicts the escape dynamics of HIV-1
in the course of an antibody treatment, including a characteristic frequency
turnover between sensitive and resistant strains. This turnover is governed by
a dosage-dependent fitness ranking, resulting from an evolutionary tradeoff
between antibody resistance and its collateral cost in drug-free growth. Our
analysis suggests resistance-cost tradeoff curves as a measure of antibody
performance in the presence of resistance evolution.
