The general framework and various criteria for experimental design optimisation are presented. The methodology is applied to the estimation of receptor-ligand reaction model parameters with dynamic positron emission tomography data. The possibility of improving parameter estimation using a new experimental design combining an injection of the beta+-labelled ligand and an injection of the cold ligand is investigated. Numerical simulations predict a remarkable improvement in the accuracy of the parameter estimates with this new experimental design and particularly the possibility of separate estimations of the association constant (k+1) and of the receptor density (B'max) in a single experiment. Simulation predictions are validated using experimental PET data in which parameter uncertainties are reduced by factors ranging from 17 to 1000.