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Lewis Sheiner


2019
Stockholm, Sweden



2018
Montreux, Switzerland

2017
Budapest, Hungary

2016
Lisboa, Portugal

2015
Hersonissos, Crete, Greece

2014
Alicante, Spain

2013
Glasgow, Scotland

2012
Venice, Italy

2011
Athens, Greece

2010
Berlin, Germany

2009
St. Petersburg, Russia

2008
Marseille, France

2007
K°benhavn, Denmark

2006
Brugge/Bruges, Belgium

2005
Pamplona, Spain

2004
Uppsala, Sweden

2003
Verona, Italy

2002
Paris, France

2001
Basel, Switzerland

2000
Salamanca, Spain

1999
Saintes, France

1998
Wuppertal, Germany

1997
Glasgow, Scotland

1996
Sandwich, UK

1995
Frankfurt, Germany

1994
Greenford, UK

1993
Paris, France

1992
Basel, Switzerland



Printable version

PAGE. Abstracts of the Annual Meeting of the Population Approach Group in Europe.
ISSN 1871-6032

Reference:
PAGE 24 (2015) Abstr 3563 [www.page-meeting.org/?abstract=3563]


Poster: Drug/Disease modeling - Absorption & PBPK


IV-73 Muhammad Waqas Sadiq A whole-body physiologically based pharmacokinetic (WBPBPK) model of ciprofloxacin for prediction of bacterial killing at the site of infection

M. W. Sadiq (1,2), E. I. Nielsen (1), M. O. Karlsson (1), L. E. Friberg (1)

(1) Uppsala University, Sweden; (2) CVMD iMed DMPK, AstraZeneca R&D, 431 83, M÷lndal, Sweden

Objectives: Aim of this study was to develop a WBPBPK model for ciprofloxacin to predict the tissue concentration time profiles in patients with only plasma concentrations data available. WBPBPK model was further combine to a PKPD model to illustrate the time-course of bacterial killing for infections with E. coli strains with different levels of resistance.

Methods: Based on 102 adult ICU patient’s plasma concentration data, a WBPBPK model for ciprofloxacin was developed [1]. NONMEM was used to apply population approach for data analysis. Tissue to plasma distribution coefficients (Kp) for ciprofloxacin in 10 different tissues including lung, muscle, kidney and adipose were taken from clinical studies available in literature. These literature Kp values were used as informative priors while estimating the individual tissue Kp values. Time-course of the bacterial killing for E. coli in different tissues were quantitatively predicted by coupling the final WBPBPK model to a pharmacokinetic-pharmacodynamic (PKPD) model [2].

Results: The developed WBPBPK model successfully characterized both the typical trends and variability of the available ciprofloxacin data, as demonstrated by visual predictive checks. Stable PK estimates including clearance and tissue Kp values were generated by model, comparable to previously reported literature values. By connecting the predicted PK profile of unbound ciprofloxacin with the PKPD model the rate and extent of take-over of mutant bacteria in different tissues could be predicted. A series of simulation scenarios of different dosing regimens, mixtures of bacterial population with different levels of resistance and immune response were performed to illustrate the concept and the impact of different PK-profiles.

Conclusions: For prediction of time course of bacterial killing in different tissues a novel method of combining the concentration time profile from WBPBPK with PKPD model was successfully implemented.

Acknowledgements: This work was supported by the DDMoRe (www.ddmore.eu) project and Swedish Foundation for Strategic Research.



References:
[1] Khachman D., et al., J Antimicrob Chemother, 2011. 66(8): p. 1798-809. 
[2] Khan D.,et al., ICAAC 2011-Chicago (poster) A1-1761.