Literature DB >> 28823852

Incorporation of lysosomal sequestration in the mechanistic model for prediction of tissue distribution of basic drugs.

Frauke Assmus1, J Brian Houston1, Aleksandra Galetin2.   

Abstract

The prediction of tissue-to-plasma water partition coefficients (Kpu) from in vitro and in silico data using the tissue-composition based model (Rodgers & Rowland, J Pharm Sci. 2005, 94(6):1237-48.) is well established. However, distribution of basic drugs, in particular into lysosome-rich lung tissue, tends to be under-predicted by this approach. The aim of this study was to develop an extended mechanistic model for the prediction of Kpu which accounts for lysosomal sequestration and the contribution of different cell types in the tissue of interest. The extended model is based on compound-specific physicochemical properties and tissue composition data to describe drug ionization, distribution into tissue water and drug binding to neutral lipids, neutral phospholipids and acidic phospholipids in tissues, including lysosomes. Physiological data on the types of cells contributing to lung, kidney and liver, their lysosomal content and lysosomal pH were collated from the literature. The predictive power of the extended mechanistic model was evaluated using a dataset of 28 basic drugs (pKa≥7.8, 17 β-blockers, 11 structurally diverse drugs) for which experimentally determined Kpu data in rat tissue have been reported. Accounting for the lysosomal sequestration in the extended mechanistic model improved the accuracy of Kpu predictions in lung compared to the original Rodgers model (56% drugs within 2-fold or 88% within 3-fold of observed values). Reduction in the extent of Kpu under-prediction was also evident in liver and kidney. However, consideration of lysosomal sequestration increased the occurrence of over-predictions, yielding overall comparable model performances for kidney and liver, with 68% and 54% of Kpu values within 2-fold error, respectively. High lysosomal concentration ratios relative to cytosol (>1000-fold) were predicted for the drugs investigated; the extent differed depending on the lysosomal pH and concentration of acidic phospholipids among cell types. Despite this extensive lysosomal sequestration in the individual cells types, the maximal change in the overall predicted tissue Kpu was <3-fold for lysosome-rich tissues investigated here. Accounting for the variability in cellular physiological model input parameters, in particular lysosomal pH and fraction of the cellular volume occupied by the lysosomes, only partially explained discrepancies between observed and predicted Kpu data in the lung. Improved understanding of the system properties, e.g., cell/organelle composition is required to support further development of mechanistic equations for the prediction of drug tissue distribution. Application of this revised mechanistic model is recommended for prediction of Kpu in lysosome-rich tissue to facilitate the advancement of physiologically-based prediction of volume of distribution and drug exposure in the tissues.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Basic drugs; Lysosomal sequestration; PBPK modeling; Prediction of tissue distribution

Mesh:

Substances:

Year:  2017        PMID: 28823852     DOI: 10.1016/j.ejps.2017.08.014

Source DB:  PubMed          Journal:  Eur J Pharm Sci        ISSN: 0928-0987            Impact factor:   4.384


  7 in total

1.  Global Sensitivity Analysis of the Rodgers and Rowland Model for Prediction of Tissue: Plasma Partitioning Coefficients: Assessment of the Key Physiological and Physicochemical Factors That Determine Small-Molecule Tissue Distribution.

Authors:  Estelle Yau; Andrés Olivares-Morales; Michael Gertz; Neil Parrott; Adam S Darwich; Leon Aarons; Kayode Ogungbenro
Journal:  AAPS J       Date:  2020-02-03       Impact factor: 4.009

2.  Advancing Predictions of Tissue and Intracellular Drug Concentrations Using In Vitro, Imaging and Physiologically Based Pharmacokinetic Modeling Approaches.

Authors:  Yingying Guo; Xiaoyan Chu; Neil J Parrott; Kim L R Brouwer; Vicky Hsu; Swati Nagar; Pär Matsson; Pradeep Sharma; Jan Snoeys; Yuichi Sugiyama; Daniel Tatosian; Jashvant D Unadkat; Shiew-Mei Huang; Aleksandra Galetin
Journal:  Clin Pharmacol Ther       Date:  2018-09-12       Impact factor: 6.875

Review 3.  Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies.

Authors:  Neil A Miller; Micaela B Reddy; Aki T Heikkinen; Viera Lukacova; Neil Parrott
Journal:  Clin Pharmacokinet       Date:  2019-06       Impact factor: 6.447

4.  Physiologically Based Pharmacokinetics of Lysosomotropic Chloroquine in Rat and Human.

Authors:  Xin Liu; William J Jusko
Journal:  J Pharmacol Exp Ther       Date:  2020-12-04       Impact factor: 4.030

5.  Pulmonary Delivery of Aerosolized Chloroquine and Hydroxychloroquine to Treat COVID-19: In Vitro Experimentation to Human Dosing Predictions.

Authors:  Aditya R Kolli; Tanja Zivkovic Semren; David Bovard; Shoaib Majeed; Marco van der Toorn; Sophie Scheuner; Philippe A Guy; Arkadiusz Kuczaj; Anatoly Mazurov; Stefan Frentzel; Florian Calvino-Martin; Nikolai V Ivanov; John O'Mullane; Manuel C Peitsch; Julia Hoeng
Journal:  AAPS J       Date:  2022-02-07       Impact factor: 4.009

6.  Physiologically Based Pharmacokinetic (PBPK) Modeling to Predict PET Image Quality of Three Generations EGFR TKI in Advanced-Stage NSCLC Patients.

Authors:  I H Bartelink; E A van de Stadt; A F Leeuwerik; V L J L Thijssen; J R I Hupsel; J F van den Nieuwendijk; I Bahce; M Yaqub; N H Hendrikse
Journal:  Pharmaceuticals (Basel)       Date:  2022-06-27

7.  Meta-Assessment of Metformin Absorption and Disposition Pharmacokinetics in Nine Species.

Authors:  Yoo-Seong Jeong; William J Jusko
Journal:  Pharmaceuticals (Basel)       Date:  2021-06-07
  7 in total

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