Population PK data from the multiple i.v. and s.c. doses of Epo were analyzed simultaneously using the nonlinear mixed effect modeling approach with NONMEM (Version 7.3; Icon Development Solutions, Ellicott City, Maryland) interfaced with Pirana (version 2.9.5b, Pirana-software.com/">http://www.Pirana-software.com/ ). The first-order conditional estimation method with interaction (FOCEI) and a user-defined subroutine (ADVAN6) were used to estimate the population mean values of the PK parameters, inter-individual variability (IIV), inter-occasion variability (IOV), and residual variability (RV) between observed and individually predicted plasma Epo concentrations. RStudio (version 1.0.143, https://www.rstudio.com/ ) was used for graphical analysis and data handling. Because endogenous Epo cannot be distinguished by the assay from exogenously administered recombinant human Epo, baseline-corrected Epo concentrations were used in our analysis.
Pirana
Manufactured by ICON Development Solutions
Sourced in United States
The Pirana is a versatile lab equipment designed for a range of applications. It features a compact and durable construction, making it suitable for various laboratory settings. The core function of the Pirana is to provide reliable and consistent results for users.
Automatically generated - may contain errors
4 protocols using pirana
1
Pharmacokinetics of Erythropoietin in Humans
2
Population Pharmacokinetic Modeling Analysis
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Population PK/PD analyses were conducted using non-linear mixed-effect modelling (NONMEM) [version 7.4.2; ICON Development Solutions, Ellicott City, MD, USA], supplemented by the PsN-Toolkit (version 4.2.0) and Pirana version 2.9.2 [17 (link), 18 (link)]. Data management, statistical and graphical analyses were performed using R (version 3.6.1) [https://www.r-project.org ].
3
Pharmacokinetic Analysis of Polymyxin B
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Nonlinear mixed-effects modeling (NONMEM) program (version 7.4, Icon Development Solutions, Ellicott City, MD, United States) and Pirana (version 2.9.7) was used to perform PK analysis of polymyxin B. R (Version 3.6.1) was used to analyze the NONMEM output. The first-order conditional estimation with the interaction between inter-patient variability and residual variability was used for model development.
4
Nonlinear Mixed-Effects Modeling of CQ
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Dataset arrangement and exploratory data analysis were performed using R (version 3.5.3, https://www.r-project.org/ ) and RStudio (version 1.1.453, https://rstudio.com/ ). A nonlinear mixed-effects model was implemented in NONMEM (version 7.3, Icon Development Solutions, Ellicott City, MD, USA) interfaced by Pirana (version 2.8) and Perl speaks NONMEM (PsN) (version 3.6.2) toolkit [20 (link)]. Model-based simulations were conducted using the R mrgsolve package. CQ mean concentration-time profiles were extracted using Plot Digitizer (GetData, Version 2.26).
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