Conventional kinase inhibitor discovery is largely a linear process that addresses one kinase at a time and requires significant serial investment of time and resources for each target. Traditionally, compounds are screened against the kinase of interest to identify “hits,” which are optimized to generate lead compounds until ultimately a candidate for clinical development is identified. Using this approach, kinase selectivity is typically monitored only sporadically throughout the optimization process. This strategy has at least two significant drawbacks. First, targets are addressed one at a time, and the entire process has to be repeated for each new target of interest. Second, decisions about which targets to pursue are based on biology alone, with minimal upfront knowledge about the selectivity or quality of hits against the designated target within the available chemical library.