[Value of the theory of the optimal sampling scheme for bioequivalence studies]

Use of optimal sampling theory (OST) in pharmacokinetic studies allows a large reduction of the number of sampling times without loss in parameter estimation precision. OST has been applied to the determination of bioavailability parameters [area under the curve (AUC), maximal concentration (Cmax), time to reach maximal concentration, (Tmax)]. Three different Monte-Carlo simulations in twelve subjects have been performed, corresponding to different pharmacokinetic models: one-compartment with or without a lag time, two-compartment. Bioavailability parameters were estimated using a non-compartmental method (with 12 to 16 sampling times) and OST method (6 to 7 sampling times). Estimates were compared with true values. Bias and RMSE were similar with both methods for AUC and Cmax, while Tmax was better estimated using OST method. However, when a posteriori identifiability of the model was poor, use of a maximum a posteriori Bayesian estimator improved considerably the efficacy of OST method. Potential interest of OST for increasing statistical power of bioequivalence studies at the same cost is discussed, as well as possible limitations.