Literature DB >> 18426954

Trend analysis of a database of intravenous pharmacokinetic parameters in humans for 670 drug compounds.

R Scott Obach1, Franco Lombardo, Nigel J Waters.   

Abstract

We present herein a compilation and trend analysis of human i.v. pharmacokinetic data on 670 drugs representing, to our knowledge, the largest publicly available set of human clinical pharmacokinetic data. This data set provides the drug metabolism scientist with a robust and accurate resource suitable for a number of applications, including in silico modeling, in vitro-in vivo scaling, and physiologically based pharmacokinetic approaches. Clearance, volume of distribution at steady state, mean residence time, and terminal phase half-life were obtained or derived from original references exclusively from studies utilizing i.v. administration. Plasma protein binding data were collected from other sources to supplement these pharmacokinetic data. These parameters were analyzed concurrently with a range of simple physicochemical descriptors, and resultant trends and patterns within the data are presented. Our findings with this much expanded data set were consistent with earlier described notions of trends between physicochemical properties and pharmacokinetic behavior. These observations and analyses, along with the large database of human pharmacokinetic data, should enable future efforts aimed toward developing quantitative structure-pharmacokinetic relationships and improving our understanding of the relationship between fundamental chemical characteristics and drug disposition.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 18426954     DOI: 10.1124/dmd.108.020479

Source DB:  PubMed          Journal:  Drug Metab Dispos        ISSN: 0090-9556            Impact factor:   3.922


  82 in total

Review 1.  Applications of human pharmacokinetic prediction in first-in-human dose estimation.

Authors:  Peng Zou; Yanke Yu; Nan Zheng; Yongsheng Yang; Hayley J Paholak; Lawrence X Yu; Duxin Sun
Journal:  AAPS J       Date:  2012-03-10       Impact factor: 4.009

2.  DemQSAR: predicting human volume of distribution and clearance of drugs.

Authors:  Ozgur Demir-Kavuk; Jörg Bentzien; Ingo Muegge; Ernst-Walter Knapp
Journal:  J Comput Aided Mol Des       Date:  2011-11-20       Impact factor: 3.686

Review 3.  Coexistence of passive and carrier-mediated processes in drug transport.

Authors:  Kiyohiko Sugano; Manfred Kansy; Per Artursson; Alex Avdeef; Stefanie Bendels; Li Di; Gerhard F Ecker; Bernard Faller; Holger Fischer; Grégori Gerebtzoff; Hans Lennernaes; Frank Senner
Journal:  Nat Rev Drug Discov       Date:  2010-08       Impact factor: 84.694

4.  Molecular interaction fields (MIFs) to predict lipophilicity and ADME profile of antitumor Pt(II) complexes.

Authors:  Giulia Caron; Mauro Ravera; Giuseppe Ermondi
Journal:  Pharm Res       Date:  2010-11-17       Impact factor: 4.200

5.  Predicting Clearance Mechanism in Drug Discovery: Extended Clearance Classification System (ECCS).

Authors:  Manthena V Varma; Stefanus J Steyn; Charlotte Allerton; Ayman F El-Kattan
Journal:  Pharm Res       Date:  2015-07-09       Impact factor: 4.200

6.  Expansion of a PBPK model to predict disposition in pregnant women of drugs cleared via multiple CYP enzymes, including CYP2B6, CYP2C9 and CYP2C19.

Authors:  Alice Ban Ke; Srikanth C Nallani; Ping Zhao; Amin Rostami-Hodjegan; Jashvant D Unadkat
Journal:  Br J Clin Pharmacol       Date:  2014-03       Impact factor: 4.335

7.  ALOHA: a novel probability fusion approach for scoring multi-parameter drug-likeness during the lead optimization stage of drug discovery.

Authors:  Derek A Debe; Ravindra B Mamidipaka; Robert J Gregg; James T Metz; Rishi R Gupta; Steven W Muchmore
Journal:  J Comput Aided Mol Des       Date:  2013-10-11       Impact factor: 3.686

8.  Estimation of biliary excretion of foreign compounds using properties of molecular structure.

Authors:  Mohsen Sharifi; Taravat Ghafourian
Journal:  AAPS J       Date:  2013-11-08       Impact factor: 4.009

9.  Drug Distribution Part 2. Predicting Volume of Distribution from Plasma Protein Binding and Membrane Partitioning.

Authors:  Ken Korzekwa; Swati Nagar
Journal:  Pharm Res       Date:  2016-12-13       Impact factor: 4.200

10.  Relative importance of intestinal and hepatic glucuronidation-impact on the prediction of drug clearance.

Authors:  Helen E Cubitt; J Brian Houston; Aleksandra Galetin
Journal:  Pharm Res       Date:  2009-01-31       Impact factor: 4.200

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.