R and nlmixr as a gateway between statistics and pharmacometrics

To run the model, one specifies the ODE/solved system and provides initial estimates for the model as described in the nlmixr tutorial. 2 The model then can be solved using the nlme algorithm, or, more optimally, using more advanced algorithms that have been shown to provide more accurate parameter...

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Bibliographic Details
Published in:CPT: pharmacometrics and systems pharmacology 2021-04, Vol.10 (4), p.283-285
Main Authors: Fidler, Matthew, Hooijmaijers, Richard, Schoemaker, Rik, Wilkins, Justin J., Xiong, Yuan, Wang, Wenping
Format: Article
Language:English
Subjects:
Algorithms
Approximation
Biostatistics - methods
Bronchodilator Agents - pharmacokinetics
Drug Approval - methods
Drug Design
Drug Development - methods
Drug Discovery - methods
Drug dosages
Humans
Nonlinear Dynamics
Ordinary differential equations
Pharmaceutical Preparations
Pharmacokinetics
Pharmacology
Physiology
Research Design
Signal transduction
Syntax
Theophylline - pharmacokinetics
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Summary:To run the model, one specifies the ODE/solved system and provides initial estimates for the model as described in the nlmixr tutorial. 2 The model then can be solved using the nlme algorithm, or, more optimally, using more advanced algorithms that have been shown to provide more accurate parameter estimates like first‐order conditional estimation with interaction (FOCEI) 3 and stochastic approximation expectation maximization (SAEM). The syntax for fitting a multiple dose theophylline PK is identical to the previous example, except that extra doses were added as well as extra simulated observations: fit.nlme
ISSN:2163-8306
2163-8306
DOI:10.1002/psp4.12618