We recently described rapid quantitative pharmacodynamic imaging, a novel method for estimating sensitivity of a biological system to a drug. We tested its accuracy in simulated neuroimaging signals with varying receptor sensitivity and varying levels of random noise, and presented initial proof-of-concept data from functional MRI (fMRI) studies in primate brain. However, the initial simulation testing used a simple iterative approach to estimate pharmacokinetic-pharmacodynamic (PKPD) parameters, an approach that was computationally efficient but returned parameters only from a small, discrete set of values chosen a priori. Here we revisit the simulation testing using a Bayesian method to provide more accurate estimates of the PKPD parameters. This produced improved accuracy, and noise without intentional signal was never interpreted as signal. This approach improves the ability of rapid quantitative pharmacodynamic imaging to reliably estimate drug sensitivity (EC50) from simulated data. The success with these simulated data paves the way for analyzing experimental data acquired for rapid quantitative pharmacodynamic imaging to validate it against results obtained by traditional methods in the same subjects.