Literature DB >> 14670695

Calculating the hybrid (macro) rate constants of a three-compartment mamillary pharmacokinetic model from known micro-rate constants.

Richard N Upton1.   

Abstract

INTRODUCTION: While there are published equations for calculating the hybrid (macro) rates constants (lambda1 and lambda2) of a two-compartment mamillary pharmacokinetic model from its micro-rate constants (e.g., k12, k21 etc.), there appears to be no report of an analogous method for a three-compartment model. The hybrid rate constants are the exponents of the multi-exponential equation describing the time-course of the predicted blood concentrations.
METHODS: Using the method of Wagner, the differential equations of a three-compartment model were solved by transformation into the Laplace domain then matrix manipulation. The inversion of the result back into the time domain requires finding the roots of a cubic polynomial. The equations of a convenient method for doing so are reported. This "analytical" method for finding the hybrid rate constants was compared with an alternative "simulation and fitting" method. For this, a model with known micro-rate constants was used to predict a time-course of blood concentrations for a bolus dose, which was then fitted to a tri-exponential equation to find the hybrid rate constants.
RESULTS: The hybrid rate constants for the two methods were identical to at least four significant figures, confirming the validity of the analytical equations. DISCUSSION: The equations presented here fill a gap in the pharmacokinetic literature, which may be useful in some applications considering the widespread use of the three-compartment mamillary pharmacokinetic model.

Mesh:

Substances:

Year:  2004        PMID: 14670695     DOI: 10.1016/j.vascn.2003.09.001

Source DB:  PubMed          Journal:  J Pharmacol Toxicol Methods        ISSN: 1056-8719            Impact factor:   1.950


  8 in total

1.  Population pharmacokinetics of plasma-derived factor IX in adult patients with haemophilia B: implications for dosing in prophylaxis.

Authors:  Sven Björkman; Victor Ahlén
Journal:  Eur J Clin Pharmacol       Date:  2012-01-27       Impact factor: 2.953

2.  Population pharmacokinetics, tolerability, and safety of dihydroartemisinin-piperaquine and sulfadoxine-pyrimethamine-piperaquine in pregnant and nonpregnant Papua New Guinean women.

Authors:  John M Benjamin; Brioni R Moore; Sam Salman; Madhu Page-Sharp; Somoyang Tawat; Gumal Yadi; Lina Lorry; Peter M Siba; Kevin T Batty; Leanne J Robinson; Ivo Mueller; Timothy M E Davis
Journal:  Antimicrob Agents Chemother       Date:  2015-05-11       Impact factor: 5.191

3.  Impact of pharmacogenetics on variability in exposure to oral vinorelbine among pediatric patients: a model-based population pharmacokinetic analysis.

Authors:  Mourad Hamimed; Pierre Leblond; Aurélie Dumont; Florence Gattacceca; Emmanuelle Tresch-Bruneel; Alicia Probst; Pascal Chastagner; Anne Pagnier; Emilie De Carli; Natacha Entz-Werlé; Jacques Grill; Isabelle Aerts; Didier Frappaz; Anne-Isabelle Bertozzi-Salamon; Caroline Solas; Nicolas André; Joseph Ciccolini
Journal:  Cancer Chemother Pharmacol       Date:  2022-06-25       Impact factor: 3.288

4.  Oritavancin population pharmacokinetics in healthy subjects and patients with complicated skin and skin structure infections or bacteremia.

Authors:  Christopher M Rubino; Scott A Van Wart; Sujata M Bhavnani; Paul G Ambrose; Jill S McCollam; Alan Forrest
Journal:  Antimicrob Agents Chemother       Date:  2009-07-27       Impact factor: 5.191

5.  IV and oral fosfomycin pharmacokinetics in neonates with suspected clinical sepsis.

Authors:  Zoe Kane; Silke Gastine; Christina Obiero; Phoebe Williams; Sheila Murunga; Johnstone Thitiri; Sally Ellis; Erika Correia; Borna Nyaoke; Karin Kipper; John van den Anker; Mike Sharland; James A Berkley; Joseph F Standing
Journal:  J Antimicrob Chemother       Date:  2021-06-18       Impact factor: 5.790

6.  A pharmacokinetic model for amiodarone in infants developed from an opportunistic sampling trial and published literature data.

Authors:  Samantha H Dallefeld; Andrew M Atz; Ram Yogev; Janice E Sullivan; Amira Al-Uzri; Susan R Mendley; Matthew Laughon; Christoph P Hornik; Chiara Melloni; Barrie Harper; Andrew Lewandowski; Jeff Mitchell; Huali Wu; Thomas P Green; Michael Cohen-Wolkowiez
Journal:  J Pharmacokinet Pharmacodyn       Date:  2018-02-12       Impact factor: 2.410

7.  Population Pharmacokinetic Analysis of Bortezomib in Pediatric Leukemia Patients: Model-Based Support for Body Surface Area-Based Dosing Over the 2- to 16-Year Age Range.

Authors:  Michael J Hanley; Diane R Mould; Timothy J Taylor; Neeraj Gupta; Kaveri Suryanarayan; Rachel Neuwirth; Dixie-Lee Esseltine; Terzah M Horton; Richard Aplenc; Todd A Alonzo; Xiaomin Lu; Ashley Milton; Karthik Venkatakrishnan
Journal:  J Clin Pharmacol       Date:  2017-04-18       Impact factor: 3.126

8.  Population Pharmacokinetic Analysis of Ixazomib, an Oral Proteasome Inhibitor, Including Data from the Phase III TOURMALINE-MM1 Study to Inform Labelling.

Authors:  Neeraj Gupta; Paul M Diderichsen; Michael J Hanley; Deborah Berg; Helgi van de Velde; R Donald Harvey; Karthik Venkatakrishnan
Journal:  Clin Pharmacokinet       Date:  2017-11       Impact factor: 6.447

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.