Literature DB >> 9118582

Bayesian forecasting in paediatric populations.

M M Fernández de Gatta1, M J García, J M Lanao, A Domínguez-Gil.   

Abstract

Bayesian forecasting offers several important advantages for dosage individualisation in children, although, unlike for adults, its use in this population is much lower. Indeed, currently Bayesian methods are underused in this patient population. The paucity of paediatric population pharmacokinetic parameters, and the unavailability of specific clinical pharmacokinetic software for the whole paediatric population, are the main limitations to the application of Bayesian methods in these patients. When these problems have been overcome, this approach will allow clinicians to achieve therapeutic concentrations more readily, faster and more precisely, thus making the methodology highly attractive in the paediatric setting.

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Year:  1996        PMID: 9118582     DOI: 10.2165/00003088-199631050-00001

Source DB:  PubMed          Journal:  Clin Pharmacokinet        ISSN: 0312-5963            Impact factor:   6.447


  48 in total

1.  An evaluation of Bayesian microcomputer predictions of theophylline concentrations in newborn infants.

Authors:  M G Murphy; C C Peck; G B Merenstein; D Rodden
Journal:  Ther Drug Monit       Date:  1990-01       Impact factor: 3.681

2.  Aminoglycoside dosing in pediatric patients.

Authors:  B C Carlstedt; M Uaamnuichai; R B Day; L Bowman; D C Brater
Journal:  Ther Drug Monit       Date:  1989       Impact factor: 3.681

Review 3.  Principles of drug biodisposition in the neonate. A critical evaluation of the pharmacokinetic-pharmacodynamic interface (Part II).

Authors:  J B Besunder; M D Reed; J L Blumer
Journal:  Clin Pharmacokinet       Date:  1988-05       Impact factor: 6.447

4.  A Bayesian feedback method of aminoglycoside dosing.

Authors:  M E Burton; D C Brater; P S Chen; R B Day; P J Huber; M R Vasko
Journal:  Clin Pharmacol Ther       Date:  1985-03       Impact factor: 6.875

Review 5.  Computers in pharmacokinetics. Choosing software for clinical decision making.

Authors:  D E Buffington; V Lampasona; M H Chandler
Journal:  Clin Pharmacokinet       Date:  1993-09       Impact factor: 6.447

6.  Dosage optimization methods applied to imipramine and desipramine in enuresis treatment.

Authors:  M Tamayo; M M Fernández de Gatta; M J García; A Domínguez-Gil
Journal:  J Clin Pharm Ther       Date:  1992-02       Impact factor: 2.512

Review 7.  Principles of drug biodisposition in the neonate. A critical evaluation of the pharmacokinetic-pharmacodynamic interface (Part I).

Authors:  J B Besunder; M D Reed; J L Blumer
Journal:  Clin Pharmacokinet       Date:  1988-04       Impact factor: 6.447

8.  Prediction of gentamicin concentrations in neonates and infants using a Bayesian pharmacokinetic model.

Authors:  K A Rodvold; C A Gentry; G S Plank; D M Kraus; E Nickel; J R Gross
Journal:  Dev Pharmacol Ther       Date:  1993

9.  Potential of population pharmacokinetics to reduce the frequency of blood sampling required for estimating kinetic parameters in neonates.

Authors:  L Collart; T F Blaschke; F Boucher; C G Prober
Journal:  Dev Pharmacol Ther       Date:  1992

10.  Bayesian forecasting of serum vancomycin concentrations in neonates and infants.

Authors:  K A Rodvold; C A Gentry; G S Plank; D M Kraus; E Nickel; J R Gross
Journal:  Ther Drug Monit       Date:  1995-06       Impact factor: 3.681

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  3 in total

Review 1.  Adaptive control methods for the dose individualisation of anticancer agents.

Authors:  A Rousseau; P Marquet; J Debord; C Sabot; G Lachâtre
Journal:  Clin Pharmacokinet       Date:  2000-04       Impact factor: 6.447

2.  Influence of real-time Bayesian forecasting of pharmacokinetic parameters on the precision of a rocuronium target-controlled infusion.

Authors:  Cyrus Motamed; Jean-Michel Devys; Bertrand Debaene; Valérie Billard
Journal:  Eur J Clin Pharmacol       Date:  2012-02-19       Impact factor: 2.953

3.  A Population Pharmacokinetic Model of Gentamicin in Pediatric Oncology Patients To Facilitate Personalized Dosing.

Authors:  C C Llanos-Paez; C E Staatz; R Lawson; S Hennig
Journal:  Antimicrob Agents Chemother       Date:  2017-07-25       Impact factor: 5.191

  3 in total

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