Literature DB >> 27460758

A unified strategy in selection of the best allometric scaling methods to predict human clearance based on drug disposition pathway.

Dongyang Liu1, Hanlin Song1, Ling Song1, Yang Liu1, Yanguang Cao2, Ji Jiang1, Pei Hu1.   

Abstract

1. It is critical to develop a unified strategy to select the best allometric scaling (AS) method for a given group of drugs. 2. A total of 446 drugs with known human CLiv, clear disposition pathway and animal (rat, dog, monkey) CLiv were analyzed. All drugs were stratified based on their disposition pathway, liver extraction ratio (ERH) and ratios of unbound clearance to renal glomerular filtration rate (RGFR). Up to 22 AS methods were applied and compared in prediction of human CLiv to each group of drugs. 3. AS methods that give the best prediction of human CLiv, were identified for drugs primarily eliminated through liver with a fraction of renal elimination (frenal) within 0.3-0.5 or ERH > 0.3, where human CLiv of more than 80% or 90% drugs could be accurately (within 2- or 3-fold error) predicted. For drugs with ERH < 0.3, acceptable accuracy could be achieved by a two species method TSR,D resulting more than 60% or 75% drugs were predicted within 2- or 3-fold error. 4. By stratified analysis of drugs, according to their disposition pathway and organ extraction ratio, a unified strategy was developed to select the best AS method in prediction of human CLiv.

Entities:  

Keywords:  Allometric scaling; disposition pathway; human clearance; prediction

Mesh:

Substances:

Year:  2016        PMID: 27460758     DOI: 10.1080/00498254.2016.1205761

Source DB:  PubMed          Journal:  Xenobiotica        ISSN: 0049-8254            Impact factor:   1.908


  4 in total

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Authors:  Ling Song; Yi Zhang; Ji Jiang; Shuang Ren; Li Chen; Dongyang Liu; Xijing Chen; Pei Hu
Journal:  Clin Pharmacokinet       Date:  2018-10       Impact factor: 6.447

Review 2.  Current Approaches for Predicting Human PK for Small Molecule Development Candidates: Findings from the IQ Human PK Prediction Working Group Survey.

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Journal:  AAPS J       Date:  2022-07-19       Impact factor: 3.603

3.  Development of an in silico prediction system of human renal excretion and clearance from chemical structure information incorporating fraction unbound in plasma as a descriptor.

Authors:  Reiko Watanabe; Rikiya Ohashi; Tsuyoshi Esaki; Hitoshi Kawashima; Yayoi Natsume-Kitatani; Chioko Nagao; Kenji Mizuguchi
Journal:  Sci Rep       Date:  2019-12-11       Impact factor: 4.379

Review 4.  Current trends in drug metabolism and pharmacokinetics.

Authors:  Yuhua Li; Qiang Meng; Mengbi Yang; Dongyang Liu; Xiangyu Hou; Lan Tang; Xin Wang; Yuanfeng Lyu; Xiaoyan Chen; Kexin Liu; Ai-Ming Yu; Zhong Zuo; Huichang Bi
Journal:  Acta Pharm Sin B       Date:  2019-10-18       Impact factor: 11.413

  4 in total

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