Lee Da Young, Shin Soyoung, Kim Tae Hwan, Shin Beom Soo
School of Pharmacy, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon 16419, Korea.
College of Pharmacy, Wonkwang University, 460 Iksan-daero, Iksan 54538, Korea.
Pharmaceutics. 2022 Jun 9;14(6):1226. doi: 10.3390/pharmaceutics14061226.
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 (V), 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 V. The pharmacokinetics of three types of donepezil SR and the immediate-release (IR) tablets was assessed in Beagle dogs following oral administration ( = 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 V, was estimated. By correlating the in vitro and in vivo V, 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 (C) 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.
本研究旨在建立一种扩展的实验设计（DoE）-体外-体内相关性（IVIVC）模型，该模型可定义制剂组成、体外溶出度和体内药代动力学之间的关系。通过应用DoE的混合设计，设计了14种多奈哌齐模型药物的缓释（SR）片剂，并采用湿法制粒法制备。多奈哌齐SR片剂的体外溶出模式用米氏动力学描述。推导了描述SR片剂组成对体外溶出参数（即体外最大释放速率（V））影响的数学关系。通过另外5种SR片剂验证了所推导的DoE模型的可预测性，体外V的平均预测误差（PE%）小于3.50%。在比格犬口服给药后（每组n = 3），评估了三种多奈哌齐SR片剂和速释（IR）片剂的药代动力学。基于血浆浓度-时间曲线，建立了群体药代动力学模型，并估算了以体内V表示的SR片剂的体内溶出度。通过关联体外和体内V，建立了A级IVIVC。最后通过将DoE方程和IVIVC整合到群体药代动力学模型中，建立了扩展的DoE-IVIVC模型。扩展的DoE-IVIVC模型能够以制剂组成为输入，分别预测多奈哌齐SR片剂的最大血浆浓度（C）和血浆浓度-时间曲线下面积（AUC），PE%分别小于10.30%和5.19%。目前的扩展DoE-IVIVC模型可能为预测制剂变化对体内药代动力学行为的影响提供一个有价值的工具，从而更有效地开发SR制剂。将目前的建模方法应用于开发其他形式的药物制剂可能是未来研究的一个关注点。
