Comparison of Deconvolution-Based and Absorption Modeling IVIVC for Extended Release Formulations of a BCS III Drug Development Candidate

IVIVC公司 基于生理学的药代动力学模型 反褶积 吸收(声学) 化学 药代动力学 计算机科学 溶解试验 材料科学 药理学 算法 医学 生物制药分类系统 复合材料
作者
Filippos Kesisoglou,Binfeng Xia,Nancy Agrawal
出处
期刊:Aaps Journal [Springer Nature]
卷期号:17 (6): 1492-1500 被引量:45
标识
DOI:10.1208/s12248-015-9816-7
摘要

In vitro–in vivo correlations (IVIVC) are predictive mathematical models describing the relationship between dissolution and plasma concentration for a given drug compound. The traditional deconvolution/convolution-based approach is the most common methodology to establish a level A IVIVC that provides point to point relationship between the in vitro dissolution and the in vivo input rate. The increasing application of absorption physiologically based pharmacokinetic model (PBPK) has provided an alternative IVIVC approach. The current work established and compared two IVIVC models, via the traditional deconvolution/convolution method and via absorption PBPK modeling, for two types of modified release (MR) formulations (matrix and multi-particulate tablets) of MK-0941, a BCS III drug development candidate. Three batches with distinct release rates were studied for each formulation technology. A two-stage linear regression model was used for the deconvolution/convolution approach while optimization of the absorption scaling factors (a model parameter that relates permeability and input rate) in GastroplusTM Advanced Compartmental Absorption and Transit model was used for the absorption PBPK approach. For both types of IVIVC models established, and for either the matrix or the multiparticulate formulations, the average absolute prediction errors for AUC and C max were below 10% and 15%, respectively. Both the traditional deconvolution/convolution-based and the absorption/PBPK-based level A IVIVC model adequately described the compound pharmacokinetics to guide future formulation development. This case study highlights the potential utility of absorption PBPK model to complement the traditional IVIVC approaches for MR products.
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