Investigating pharmacokinetic profiles of <i>Centella asiatica</i> using machine learning and PBPK modelling-Reference-Cited by-同舟云学术

Investigating pharmacokinetic profiles of Centella asiatica using machine learning and PBPK modelling

Published:2024-06-11 Issue: Volume: Page:1-16
ISSN:1054-3406
Container-title:Journal of Biopharmaceutical Statistics
language:en
Short-container-title:Journal of Biopharmaceutical Statistics

Author:

Pumkathin Siriwan¹,Hanlumyuang Yuranan²,Wattanathana Worawat²,Laomettachit Teeraphan³⁴,Liangruksa Monrudee⁵

Affiliation:

1. Department of Sustainable Energy and Resources Engineering, Faculty of Engineering, Kasetsart University, Bangkok, Thailand

2. Department of Materials Engineering, Faculty of Engineering, Kasetsart University, Bangkok, Thailand

3. Theoretical and Computational Physics Group, Center of Excellence in Theoretical and Computational Science (TaCS-CoE), King Mongkut’s University of Technology Thonburi (KMUTT), Bangkok, Thailand

4. Bioinformatics and Systems Biology Program, School of Bioresources and Technology, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

5. National Nanotechnology Center (NANOTEC), National Science and Technology Development Agency (NSTDA), Pathum Thani, Thailand

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10543406.2024.2358797

Reference44 articles.

1. Multiple Oral Dosing Pharmacokinetics of Standardized Extract of Centella asiatica ECa 233 and Its Inductive Effect on Efflux Transporters in Rats

2. Pharmacokinetics of a Standardized Extract of Centella asiatica ECa 233 in Rats

3. The Role of BCS (Biopharmaceutics Classification System) and BDDCS (Biopharmaceutics Drug Disposition Classification System) in Drug Development

4. Predicting a Drug’s Membrane Permeability: A Computational Model Validated With in Vitro Permeability Assay Data

5. Evolution of Choice of Solubility and Dissolution Media After Two Decades of Biopharmaceutical Classification System