Literature DB >> 28402537

Performance Assessment and Translation of Physiologically Based Pharmacokinetic Models From acslX to Berkeley Madonna, MATLAB, and R Language: Oxytetracycline and Gold Nanoparticles As Case Examples.

Zhoumeng Lin1, Majid Jaberi-Douraki1,2, Chunla He3, Shiqiang Jin1,4, Raymond S H Yang5,6, Jeffrey W Fisher7, Jim E Riviere1.   

Abstract

Many physiologically based pharmacokinetic (PBPK) models for environmental chemicals, drugs, and nanomaterials have been developed to aid risk and safety assessments using acslX. However, acslX has been rendered sunset since November 2015. Alternative modeling tools and tutorials are needed for future PBPK applications. This forum article aimed to: (1) demonstrate the performance of 4 PBPK modeling software packages (acslX, Berkeley Madonna, MATLAB, and R language) tested using 2 existing models (oxytetracycline and gold nanoparticles); (2) provide a tutorial of PBPK model code conversion from acslX to Berkeley Madonna, MATLAB, and R language; (3) discuss the advantages and disadvantages of each software package in the implementation of PBPK models in toxicology, and (4) share our perspective about future direction in this field. Simulation results of plasma/tissue concentrations/amounts of oxytetracycline and gold from different models were compared visually and statistically with linear regression analyses. Simulation results from the original models were correlated well with results from the recoded models, with time-concentration/amount curves nearly superimposable and determination coefficients of 0.86-1.00. Step-by-step explanations of the recoding of the models in different software programs are provided in the Supplementary Data. In summary, this article presents a tutorial of PBPK model code conversion for a small molecule and a nanoparticle among 4 software packages, and a performance comparison of these software packages in PBPK model implementation. This tutorial helps beginners learn PBPK modeling, provides suggestions for selecting a suitable tool for future projects, and may lead to the transition from acslX to alternative modeling tools.
© The Author 2017. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Berkeley Madonna; MATLAB; PBPK modeling; R language; acslX

Mesh:

Substances:

Year:  2017        PMID: 28402537     DOI: 10.1093/toxsci/kfx070

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.849


  12 in total

1.  Probabilistic risk assessment of gold nanoparticles after intravenous administration by integrating in vitro and in vivo toxicity with physiologically based pharmacokinetic modeling.

Authors:  Yi-Hsien Cheng; Jim E Riviere; Nancy A Monteiro-Riviere; Zhoumeng Lin
Journal:  Nanotoxicology       Date:  2018-04-14       Impact factor: 5.913

2.  Harnessing Human Microphysiology Systems as Key Experimental Models for Quantitative Systems Pharmacology.

Authors:  D Lansing Taylor; Albert Gough; Mark E Schurdak; Lawrence Vernetti; Chakra S Chennubhotla; Daniel Lefever; Fen Pei; James R Faeder; Timothy R Lezon; Andrew M Stern; Ivet Bahar
Journal:  Handb Exp Pharmacol       Date:  2019

Review 3.  Current Approaches and Techniques in Physiologically Based Pharmacokinetic (PBPK) Modelling of Nanomaterials.

Authors:  Wells Utembe; Harvey Clewell; Natasha Sanabria; Philip Doganis; Mary Gulumian
Journal:  Nanomaterials (Basel)       Date:  2020-06-29       Impact factor: 5.076

4.  Meta-Analysis of Nanoparticle Delivery to Tumors Using a Physiologically Based Pharmacokinetic Modeling and Simulation Approach.

Authors:  Yi-Hsien Cheng; Chunla He; Jim E Riviere; Nancy A Monteiro-Riviere; Zhoumeng Lin
Journal:  ACS Nano       Date:  2020-03-04       Impact factor: 15.881

Review 5.  Image-guided mathematical modeling for pharmacological evaluation of nanomaterials and monoclonal antibodies.

Authors:  Prashant Dogra; Joseph D Butner; Sara Nizzero; Javier Ruiz Ramírez; Achraf Noureddine; María J Peláez; Dalia Elganainy; Zhen Yang; Anh-Dung Le; Shreya Goel; Hon S Leong; Eugene J Koay; C Jeffrey Brinker; Vittorio Cristini; Zhihui Wang
Journal:  Wiley Interdiscip Rev Nanomed Nanobiotechnol       Date:  2020-04-21

6.  Physiologically based pharmacokinetic modeling of nanoceria systemic distribution in rats suggests dose- and route-dependent biokinetics.

Authors:  Ulrika Carlander; Tshepo Paulsen Moto; Anteneh Assefa Desalegn; Robert A Yokel; Gunnar Johanson
Journal:  Int J Nanomedicine       Date:  2018-05-01

7.  A Computational Workflow for Probabilistic Quantitative in Vitro to in Vivo Extrapolation.

Authors:  Kevin McNally; Alex Hogg; George Loizou
Journal:  Front Pharmacol       Date:  2018-05-18       Impact factor: 5.810

8.  Bioinformatics analysis and verification of gene targets for benign tracheal stenosis.

Authors:  Xu-Ze Li; Zi-Chen Wang; Yong Qiu; Shu-Xian Ma; Ling-Bing Meng; Wen-Hao Wu; Pei Zhang; Wei Yang; Wen-Ping Song; Lining Huang
Journal:  Mol Genet Genomic Med       Date:  2020-04-20       Impact factor: 2.183

9.  Identification of Co-expressed Genes Between Atrial Fibrillation and Stroke.

Authors:  Yan-Fei Zhang; Ling-Bing Meng; Meng-Lei Hao; Jie-Fu Yang; Tong Zou
Journal:  Front Neurol       Date:  2020-03-24       Impact factor: 4.003

10.  Berkeley Madonna Version 10-A simulation package for solving mathematical models.

Authors:  Frank V Marcoline; John Furth; Smita Nayak; Michael Grabe; Robert I Macey
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2022-02-01
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.