Ligand (un)binding kinetics is being recognized as a determinant of drug specificity and efficacy in an increasing number of systems. However, the calculation of kinetics and the simulation of drug unbinding is more difficult than computing thermodynamic quantities, such as binding free energies. Here we present the first full simulations of an unbinding process at pharmacologically relevant time scales (11 min), without the use of biasing forces, detailed prior knowledge, or specialized processors using the weighted ensemble based algorithm, WExplore. These simulations show the inhibitor TPPU unbinding from its enzyme target soluble epoxide hydrolase, which is a clinically relevant target that has attracted interest in kinetics optimization in order to increase efficacy. We make use of conformation space networks that allow us to conceptualize unbinding not just as a linear process, but as a network of interconnected states that connect the bound and unbound states. This allows us to visualize patterns in hydrogen-bonding, solvation, and nonequilibrium free energies, without projection onto progress coordinates. The topology and layout of the network reveal multiple unbinding-pathways, and other rare events, such as the reversal of ligand orientation within the binding site. Furthermore, we make a prediction of the transition state ensemble, using transition path theory, and identify protein-ligand interactions which are stabilizing to the transition state. Additionally, we uncover trends in ligand and binding site solvation that corroborate experimental evidence from more classical structure kinetics relationships and generate new questions as to the role of drug modifications in kinetics optimization. Finally, from only 6 mu s of simulation time we observed 75 unbinding events from which we calculate a residence time of 42 s, and a standard error range of 23 to 280 s. This nearly encompasses the experimental residence time 11 min (660 s). In addition to the insights to sEH inhibitor unbinding, this study shows that simulations of complex processes on timescales as long as minutes are becoming feasible for more researchers to perform.