This study aimed to establish an extended design of experiment (DoE)-in vitro in vivo correlation (IVIVC) model that defines the relationship between formulation composition, in vitro dissolution, and in vivo pharmacokinetics. Fourteen sustained-release (SR) tablets of a model drug, donepezil, were designed by applying a mixture design of DoE and prepared by the wet granulation method. The in vitro dissolution patterns of donepezil SR tablets were described by Michaelis-Menten kinetics. The mathematical relationship describing the effects of SR tablet compositions on the in vitro dissolution parameter, i.e., the in vitro maximum rate of release (Vmax), was derived. The predictability of the derived DoE model was validated by an additional five SR tablets with a mean prediction error (PE%) of less than 3.50% for in vitro Vmax. The pharmacokinetics of three types of donepezil SR and the immediate-release (IR) tablets was assessed in Beagle dogs following oral administration (n = 3, each). Based on the plasma concentration-time profile, a population pharmacokinetic model was developed, and the in vivo dissolution of SR tablets, represented by in vivo Vmax, was estimated. By correlating the in vitro and in vivo Vmax, level A IVIVC was established. Finally, the extended DoE-IVIVC model was developed by integrating the DoE equation and IVIVC into the population pharmacokinetic model. The extended DoE-IVIVC model allowed one to predict the maximum plasma concentration (Cmax) and the area under the plasma concentration-time curve (AUC) of donepezil SR tablets with PE% less than 10.30% and 5.19%, respectively, by their formulation composition as an input. The present extended DoE-IVIVC model may provide a valuable tool to predict the effect of formulation changes on in vivo pharmacokinetic behavior, leading to the more efficient development of SR formulations. The application of the present modeling approaches to develop other forms of drug formulation may be of interest for future studies.
donepezil; level A IVIVC; mixture design; population pharmacokinetics; prediction of in vivo pharmacokinetics; sustained release.