Literature DB >> 32562690

Identification of solubility-limited absorption of oral anticancer drugs using PBPK modeling based on rat PK and its relevance to human.

Christina Fink1, Marc Lecomte2, Lassina Badolo2, Knut Wagner3, Karsten Mäder4, Sheila-Annie Peters5.   

Abstract

Solubility is one of the key parameters that is optimized during drug discovery to ensure sufficient drug concentration in systemic circulation and to achieve the desired pharmacological response. We recently reported the application of PBPK analysis of early clinical pharmacokinetic data to identify drugs whose absorption are truly limited by solubility. In this work, we selected ten anticancer drugs that exhibit poor in vitro solubility to explore the utility of this approach to identify solubility-limited absorption based on rat pharmacokinetic data and compare the findings to human data. Oral rat pharmacokinetic studies were performed at the body weight-scaled doses of the model drugs' human food effect studies, and analyzed using a top-down PBPK modeling approach. A good correlation of solubility-limited absorption in rat and human was observed. These results allow an early identification of drugs with truly solubility-limited absorption, with the potential to guide decisions and save valuable resources in drug development.
Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Human PK prediction; PBPK; Poorly water-soluble drugs; Rat pharmacokinetics; Solubility; Tyrosine kinase inhibitors

Mesh:

Year:  2020        PMID: 32562690     DOI: 10.1016/j.ejps.2020.105431

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


  2 in total

1.  Population pharmacokinetic analysis of tepotinib, an oral MET kinase inhibitor, including data from the VISION study.

Authors:  Wenyuan Xiong; Orestis Papasouliotis; E Niclas Jonsson; Rainer Strotmann; Pascal Girard
Journal:  Cancer Chemother Pharmacol       Date:  2022-04-06       Impact factor: 3.288

2.  Prediction for optimal dosage of pazopanib under various clinical situations using physiologically based pharmacokinetic modeling.

Authors:  Chunnuan Wu; Bole Li; Shuai Meng; Linghui Qie; Jie Zhang; Guopeng Wang; Cong Cong Ren
Journal:  Front Pharmacol       Date:  2022-09-12       Impact factor: 5.988

  2 in total

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