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We analyze Laplace method in the context of optimal Bayesian experimental design and extend this method from the classical scenario,where a single dominant mode of the parameters can be completely-determined by the experiment,to the scenarios where a non-informative parametric manifold exists.While Laplace method requires a concentration of measure,multi-level Monte Carlo method can be used to tackle the problem when there is a lack of measure concentration.