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Optimization of drug candidates involves modification of chemical structures in order to improve a compound’s desirable properties. We aim to use pharmacokinetic/pharmacodynamics (PK/PD) modelling to prioritize alterations in drug properties such as potency, clearance, and free drug concentrations in order to reduce the predicted efficacious dose. We have used simple differential equations and simulation software to build simple direct effect models to explore how changes in these factors affects a) maintenance of drug levels above 50% inhibition of a biological target or b) maintenance a certain efficacious area under the curve (AUC). We have demonstrated that when the pharmacodynamic target was to maintain >50% inhibition of a biological target, decreasing clearance led to greater decreases in predicted efficacious dose compared to improvements in potency. Changes in free drug levels affects both potency and clearance. The overall effect on dose was dependent on whether the drug was a high, moderate, or low clearance drug. When the pharmacodynamics target was efficacious AUC, improvements in predicted efficacious dose changed linearly with improvements in clearance or potency. These results indicate that the choice of property to optimize depends on the pharmacodynamic endpoint. When target is an efficacious AUC, one can choose to improve either clearance or potency with similar effects in steady-state dose improvements. However, when the target is maintenance of a specific level of target inhibition, better gains in dose reduction can be made by improvement of clearance rather than potency. Our study also demonstrates that application of PK/PD modelling can guide compound optimization in a more rational manner.