Thousands of chemicals have been profiled by high-throughput screening (HTS) programs such as ToxCast and Tox21. These chemicals are tested in part because there are limited or no data on hazard, exposure, or toxicokinetics (TK). TK models aid in predicting tissue concentrations resulting from chemical exposure, and a “reverse dosimetry" approach can be used to predict exposure doses sufficient to cause tissue concentrations that have been identified as bioactive by high-throughput screening. To facilitate transparent, open-access to data and models, we have created a R software package for high throughput TK (“httk”). The package includes both empirical and physiologically based TK (PBTK) models, which are designed to be parameterized using high-throughput in vitro data (plasma protein binding and hepatic clearance), as well as physicochemical properties and species-specific physiological data. We include a three-compartment steady state model that is similar to what has been used by previous “reverse dosimetry” translations of HTS data (Rotroff et al. (2010), Wetmore et al. (2012,2013,2014,2015)). This package is structured to be augmented with additional chemical data and models as they are published in the peer-reviewed scientific literature. “httk” enables the inclusion of toxicokinetics in the statistical analysis of chemicals undergoing high-throughput screening.