Literature DB >> 24492383

A two-compartment population pharmacokinetic-pharmacodynamic model of digoxin in adults, with implications for dosage.

Roger W Jelliffe1, Mark Milman, Alan Schumitzky, David Bayard, Michael Van Guilder.   

Abstract

A population pharmacokinetic/pharmacodynamic model of digoxin in adult subjects was originally developed by Reuning et al in 1973. They clearly described the 2-compartment behavior of digoxin, the lack of correlation of effect with serum concentrations, and the close correlation of the observed inotropic effect of digoxin with the calculated amount of drug present in the peripheral nonserum compartment. Their model seemed most attractive for clinical use. However, to make it more applicable for maximally precise dosage, its model parameter values (means and SD's) were converted into discrete model parameter distributions using a computer program developed especially for this purpose using the method of maximum entropy. In this way, the parameter distributions became discrete rather than continuous, suitable for use in developing maximally precise digoxin dosage regimens, individualized to an adult patient's age, gender, body weight, and renal function, to achieve desired specific target goals either in the central (serum) compartment or in the peripheral (effect) compartment using the method of multiple model dosage design. Some illustrative clinical applications of this model are presented and discussed. This model with a peripheral compartment reflecting clinical effect has contributed significantly to an improved understanding of the clinical behavior of digoxin in patients than is possible with models having only a single compartment, and to the improved management of digoxin therapy for more than 20 years.

Entities:  

Mesh:

Substances:

Year:  2014        PMID: 24492383      PMCID: PMC4286255          DOI: 10.1097/FTD.0000000000000023

Source DB:  PubMed          Journal:  Ther Drug Monit        ISSN: 0163-4356            Impact factor:   3.681


  7 in total

1.  Achieving target goals most precisely using nonparametric compartmental models and "multiple model" design of dosage regimens.

Authors:  R Jelliffe; D Bayard; M Milman; M Van Guilder; A Schumitzky
Journal:  Ther Drug Monit       Date:  2000-06       Impact factor: 3.681

2.  Creating discrete joint densities from continuous ones: the moment matching-maximum entropy approach.

Authors:  M Milman; F Jiang; R Jelliffe
Journal:  Comput Biol Med       Date:  2001-05       Impact factor: 4.589

Review 3.  Some comments and suggestions concerning population pharmacokinetic modeling, especially of digoxin, and its relation to clinical therapy.

Authors:  Roger W Jelliffe
Journal:  Ther Drug Monit       Date:  2012-08       Impact factor: 3.681

4.  Role of pharmacokinetics in drug dosage adjustment. I. Pharmacologic effect kinetics and apparent volume of distribution of digoxin.

Authors:  R H Reuning; R A Sams; R E Notari
Journal:  J Clin Pharmacol New Drugs       Date:  1973-04

5.  Optimal sampling times for pharmacokinetic experiments.

Authors:  D Z D'Argenio
Journal:  J Pharmacokinet Biopharm       Date:  1981-12

Review 6.  Model-based, goal-oriented, individualised drug therapy. Linkage of population modelling, new 'multiple model' dosage design, bayesian feedback and individualised target goals.

Authors:  R W Jelliffe; A Schumitzky; D Bayard; M Milman; M Van Guilder; X Wang; F Jiang; X Barbaut; P Maire
Journal:  Clin Pharmacokinet       Date:  1998-01       Impact factor: 6.447

7.  Estimation of creatinine clearance in patients with unstable renal function, without a urine specimen.

Authors:  Roger Jelliffe
Journal:  Am J Nephrol       Date:  2002 Jul-Aug       Impact factor: 3.754

  7 in total
  5 in total

1.  Author's reply to Veloso HH Comment on "The Role of Digitalis Pharmacokinetics in Converting Atrial Fibrillation and Flutter to Sinus Rhythm".

Authors:  Roger W Jelliffe
Journal:  Clin Pharmacokinet       Date:  2016-05       Impact factor: 6.447

2.  Expert Discussion of the Role of Rate Constant Versus Clearance Approaches to Define Drug Pharmacokinetics: Theoretical and Clinical Considerations.

Authors:  Marilyn N Martinez; Roger W Jelliffe; Johannes H Proost
Journal:  AAPS J       Date:  2020-01-06       Impact factor: 4.009

3.  The role of digitalis pharmacokinetics in converting atrial fibrillation and flutter to regular sinus rhythm.

Authors:  Roger W Jelliffe
Journal:  Clin Pharmacokinet       Date:  2014-05       Impact factor: 6.447

4.  Pharmacokinetic modelling to predict risk of ototoxicity with intravenous tobramycin treatment in cystic fibrosis.

Authors:  Min Dong; Anna V Rodriguez; Chelsea A Blankenship; Gary McPhail; Alexander A Vinks; Lisa L Hunter
Journal:  J Antimicrob Chemother       Date:  2021-10-11       Impact factor: 5.790

Review 5.  Computational Modeling of Electrophysiology and Pharmacotherapy of Atrial Fibrillation: Recent Advances and Future Challenges.

Authors:  Márcia Vagos; Ilsbeth G M van Herck; Joakim Sundnes; Hermenegild J Arevalo; Andrew G Edwards; Jussi T Koivumäki
Journal:  Front Physiol       Date:  2018-09-04       Impact factor: 4.566

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.