Literature DB >> 29175411

Mechanistic Physiologically Based Pharmacokinetic (PBPK) Model of the Heart Accounting for Inter-Individual Variability: Development and Performance Verification.

Zofia Tylutki1, Aleksander Mendyk2, Sebastian Polak3.   

Abstract

Modern model-based approaches to cardiac safety and efficacy assessment require accurate drug concentration-effect relationship establishment. Thus, knowledge of the active concentration of drugs in heart tissue is desirable along with inter-subject variability influence estimation. To that end, we developed a mechanistic physiologically based pharmacokinetic model of the heart. The models were described with literature-derived parameters and written in R, v.3.4.0. Five parameters were estimated. The model was fitted to amitriptyline and nortriptyline concentrations after an intravenous infusion of amitriptyline. The cardiac model consisted of 5 compartments representing the pericardial fluid, heart extracellular water, and epicardial intracellular, midmyocardial intracellular, and endocardial intracellular fluids. Drug cardiac metabolism, passive diffusion, active efflux, and uptake were included in the model as mechanisms involved in the drug disposition within the heart. The model accounted for inter-individual variability. The estimates of optimized parameters were within physiological ranges. The model performance was verified by simulating 5 clinical studies of amitriptyline intravenous infusion, and the simulated pharmacokinetic profiles agreed with clinical data. The results support the model feasibility. The proposed structure can be tested with the goal of improving the patient-specific model-based cardiac safety assessment and offers a framework for predicting cardiac concentrations of various xenobiotics.
Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  disposition; in silico modeling; pharmacokinetic/pharmacodynamic models; pharmacokinetics; physiological model

Mesh:

Substances:

Year:  2017        PMID: 29175411     DOI: 10.1016/j.xphs.2017.11.012

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  5 in total

Review 1.  State-of-the-Art Review on Physiologically Based Pharmacokinetic Modeling in Pediatric Drug Development.

Authors:  Venkata Yellepeddi; Joseph Rower; Xiaoxi Liu; Shaun Kumar; Jahidur Rashid; Catherine M T Sherwin
Journal:  Clin Pharmacokinet       Date:  2019-01       Impact factor: 6.447

2.  Towards Bridging Translational Gap in Cardiotoxicity Prediction: an Application of Progressive Cardiac Risk Assessment Strategy in TdP Risk Assessment of Moxifloxacin.

Authors:  Nikunjkumar Patel; Oliver Hatley; Alexander Berg; Klaus Romero; Barbara Wisniowska; Debra Hanna; David Hermann; Sebastian Polak
Journal:  AAPS J       Date:  2018-03-14       Impact factor: 4.009

3.  Physiologically based pharmacokinetic-quantitative systems toxicology and safety (PBPK-QSTS) modeling approach applied to predict the variability of amitriptyline pharmacokinetics and cardiac safety in populations and in individuals.

Authors:  Zofia Tylutki; Aleksander Mendyk; Sebastian Polak
Journal:  J Pharmacokinet Pharmacodyn       Date:  2018-06-25       Impact factor: 2.745

Review 4.  Review of applications and challenges of quantitative systems pharmacology modeling and machine learning for heart failure.

Authors:  Limei Cheng; Yuchi Qiu; Brian J Schmidt; Guo-Wei Wei
Journal:  J Pharmacokinet Pharmacodyn       Date:  2021-10-12       Impact factor: 2.745

Review 5.  Physiologically Based Pharmacokinetic Models Are Effective Support for Pediatric Drug Development.

Authors:  Kefei Wang; Kun Jiang; Xiaoyi Wei; Yulan Li; Tiejie Wang; Yang Song
Journal:  AAPS PharmSciTech       Date:  2021-07-26       Impact factor: 3.246

  5 in total

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