Fereidoon Daryaee, Andrew Chang, Johannes Schiebel, Yang Lu, Zhuo Zhang, Kanishk Kapilashrami, Stephen G. Walker, Caroline Kisker, Christoph A. Sotriffer, Stewart L. Fisher, Peter J. Tonge

• Drug-target kinetics enable time-dependent changes in target engagement to be quantified as a function of drug concentration. When coupled to drug pharmacokinetics (PK), drug-target kinetics can thus be used to predict in vivo pharmacodynamics (PD). Previously we described a mechanistic PK/PD model that successfully predicted the antibacterial activity of an LpxC inhibitor in a model of Pseudomonas aeruginosa infection. In the present work we demonstrate that the same approach can be used to predict the in vivo activity of an enoyl-ACPDrug-target kinetics enable time-dependent changes in target engagement to be quantified as a function of drug concentration. When coupled to drug pharmacokinetics (PK), drug-target kinetics can thus be used to predict in vivo pharmacodynamics (PD). Previously we described a mechanistic PK/PD model that successfully predicted the antibacterial activity of an LpxC inhibitor in a model of Pseudomonas aeruginosa infection. In the present work we demonstrate that the same approach can be used to predict the in vivo activity of an enoyl-ACP reductase (FabI) inhibitor in a model of methicillin-resistant Staphylococcus aureus (MRSA) infection. This is significant because the LpxC inhibitors are cidal, whereas the FabI inhibitors are static. In addition P. aeruginosa is a Gram-negative organism whereas MRSA is Gram-positive. Thus this study supports the general applicability of our modeling approach across antibacterial space.…