Literature DB >> 7927847

Adaptive control of drug dosage regimens: basic foundations, relevant issues, and clinical examples.

R W Jelliffe1, P Maire, F Sattler, P Gomis, B Tahani.   

Abstract

In this paper we examine several of the fundamental foundations and relevant clinical issues in adaptive control of drug dosage regimens for patients. Truly individualized therapy with drugs having narrow margins of safety first requires a practical pharmacokinetic/dynamic model of the behavior of a drug. Past experience with a drug is stored in the form of a population model. Next, using the information in such a model and its relationship to the incidence of adverse reactions, a specific, explicit therapeutic goal must be selected by the responsible clinician, based on the patient's need for the drug and the risk of adverse reactions felt to be justified by each patient's need, small, moderate, or great. Individualized drug therapy thus begins with the selection of individualized therapeutic goals (low, moderate, or high) for each patient. Using subsequent feedback from the patient's serum drug levels, and using Bayesian fitting, the model is then linked to each patient as a patient-specific model. Control of the model by the dosage regimen increasingly controls the patient, to better obtain the desired explicit therapeutic goals. This process is essentially similar to that of a flight control or missile guidance system.

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Year:  1994        PMID: 7927847     DOI: 10.1016/0020-7101(94)90091-4

Source DB:  PubMed          Journal:  Int J Biomed Comput        ISSN: 0020-7101


  6 in total

1.  Renal elimination of amikacin and the aging process.

Authors:  M Ducher; P Maire; C Cerutti; Y Bourhis; F Foltz; P Sorensen; R Jelliffe; J P Fauvel
Journal:  Clin Pharmacokinet       Date:  2001       Impact factor: 6.447

2.  Selective and validated spectrophotometric methods for the determination of nicorandil in pharmaceutical formulations.

Authors:  Nafisur Rahman; Yasmin Ahmad; Syed Najmul Hejaz Azmi
Journal:  AAPS J       Date:  2004-11-30       Impact factor: 4.009

Review 3.  Paediatric models in motion: requirements for model-based decision support at the bedside.

Authors:  Jeffrey S Barrett
Journal:  Br J Clin Pharmacol       Date:  2015-01       Impact factor: 4.335

Review 4.  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

5.  Integration of modeling and simulation into hospital-based decision support systems guiding pediatric pharmacotherapy.

Authors:  Jeffrey S Barrett; John T Mondick; Mahesh Narayan; Kalpana Vijayakumar; Sundararajan Vijayakumar
Journal:  BMC Med Inform Decis Mak       Date:  2008-01-28       Impact factor: 2.796

6.  Population Pharmacodynamic Modeling of Epoetin Alfa in End-Stage Renal Disease Patients Receiving Maintenance Treatment Using Bayesian Approach.

Authors:  Ly Minh Nguyen; Calvin J Meaney; Gauri G Rao; Mandip Panesar; Wojciech Krzyzanski
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2020-09-29
  6 in total

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