新型扩展 IVIVC 结合设计空间法预测制剂组成与药代动力学的关系。
Novel extended IVIVC combined with DoE to predict pharmacokinetics from formulation compositions.
机构信息
School of Pharmacy, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon, Gyeonggi 16419, Republic of Korea.
College of Pharmacy, Daegu Catholic University, 13-13 Hayang-ro, Hayang-eup, Gyeongsan, Gyeongbuk 38430, Republic of Korea.
出版信息
J Control Release. 2022 Mar;343:443-456. doi: 10.1016/j.jconrel.2022.01.048. Epub 2022 Feb 4.
The objective of this study was to develop a novel extended in vitro in vivo correlation (IVIVC) model combined with design of experiment (DoE) that integrates the DoE into IVIVC, which can predict the pharmacokinetics of sustained-release (SR) tablets from their formulation compositions, and vice versa. To develop the extended IVIVC model, ketoprofen was used as a model drug. Nineteen types of ketoprofen SR tablets with different formulation compositions were prepared based on the mixture design and used to derive mathematical relationships between the formulation composition and the in vitro dissolution profiles for DoE. The predictability of the DoE equation was externally validated by using additional seven types of SR formulations with prediction errors (%PE) of less than 11.45%. For the development of IVIVC model, three SR formulations that have fast, medium, and slow drug-releasing rates were selected, and the in vivo pharmacokinetics were assessed in Beagle dogs. The pharmacokinetic properties of ketoprofen SR tablets were described by a population pharmacokinetics (POP-PK) model which incorporated the pH-dependent dissolution of ketoprofen by a time-dependent Hill-type equation. The final POP-PK model could describe the overall in vivo pharmacokinetic profiles and allowed estimation of the in vivo dissolution parameters. The POP-PK model estimated in vivo dissolution parameter, K were then correlated with the in vitro dissolution parameter, K by linear regression (R = 0.9989), establishing IVIVC. Finally, the equation derived from DoE was introduced to the IVIVC model to develop the extended IVIVC, which connects the formulation composition, in vitro dissolution, and in vivo pharmacokinetic profiles. The average %PE of the final extended IVIVC model was 4.24% for C and 4.46% and AUC. Finally, the final extended IVIVC was applied to predict the in vivo PK profiles of SR tablets from their formulation compositions as well as to design the optimal formulation to achieve certain target PK profiles. The %PE of the final extended IVIVC model was less than 14.67% for C and 12.41% for AUC, satisfying the FDA criteria of conventional IVIVC. The present extended IVIVC model may provide a useful tool towards rationalized design and development of new SR formulations.
本研究旨在开发一种新的扩展体外-体内相关性（IVIVC）模型，结合实验设计（DoE），将 DoE 纳入 IVIVC 中，可以从制剂成分预测缓释（SR）片剂的药代动力学，反之亦然。为了开发扩展的 IVIVC 模型，使用酮洛芬作为模型药物。基于混合设计，制备了 19 种不同配方组成的酮洛芬 SR 片剂，用于为 DoE 建立制剂成分与体外溶出曲线之间的数学关系。通过使用预测误差（%PE）小于 11.45%的另外 7 种 SR 制剂对 DoE 方程的可预测性进行外部验证。对于 IVIVC 模型的开发，选择了具有快速、中速和慢速药物释放速率的三种 SR 制剂，并在比格犬中评估体内药代动力学。酮洛芬 SR 片剂的药代动力学特性采用群体药代动力学（POP-PK）模型描述，该模型通过时变 Hill 型方程纳入了酮洛芬的 pH 依赖性溶解。最终的 POP-PK 模型可以描述总体体内药代动力学特征，并允许估计体内溶解参数。然后，通过线性回归（R = 0.9989）将 POP-PK 模型估算的体内溶解参数 K 与体外溶解参数 K 相关联，建立 IVIVC。最后，将来自 DoE 的方程引入 IVIVC 模型，以开发连接制剂成分、体外溶解和体内药代动力学特征的扩展 IVIVC。最终扩展 IVIVC 模型的平均 %PE 为 C 的 4.24%和 AUC 的 4.46%。最后，将最终扩展的 IVIVC 应用于从制剂成分预测 SR 片剂的体内 PK 特征以及设计实现特定目标 PK 特征的最佳制剂。最终扩展 IVIVC 模型的%PE 为 C 的 14.67%和 AUC 的 12.41%，满足 FDA 对常规 IVIVC 的标准。本研究建立的扩展 IVIVC 模型可能为新的 SR 制剂的合理化设计和开发提供有用的工具。
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