This review considers a way in which experimental data can be used to identify safe and effective antifungal regimens for humans. The process begins with experimental models of invasive fungal infections that enable definition of optimal dosages and schedules of antifungal drug administration to be defined. These preclinical models also enable the identification of drug exposure targets that are associated with therapeutic outcomes of interest. Human pharmacokinetic variability results in a considerable range of drug exposures following the use of fixed antifungal drug regimens. This variability can be quantified using population pharmacokinetic modeling techniques. Monte Carlo simulation can then be used to simulate pharmacokinetic variability and thereby estimate the proportion of patients with a therapeutic outcome of interest. Effective and safe regimens can thus be studied appropriately in clinical settings. This approach can, and should, be used to optimize antifungal therapy for a large number of clinical scenarios.