Evidence map›Paper›PMID 26209956›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2015

A pharmacometric case study regarding the sensitivity of structural model parameter estimation to error in patient reported dosing times.

Jonathan Knights, Shashank Rohatagi

Abstract read
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Article in Journal of pharmacokinetics and pharmacodynamics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Jonathan KnightsOtsuka Pharmaceutical Development & Commercialization, Inc., 508 Carnegie Center Blvd. Suite 300, Princeton, NJ, 08540, USA. jonathan.knights@otsuka-us.com.
Shashank RohatagiOtsuka Pharmaceutical Development & Commercialization, Inc., 508 Carnegie Center Blvd. Suite 300, Princeton, NJ, 08540, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although there is a body of literature focused on minimizing the effect of dosing inaccuracies on pharmacokinetic (PK) parameter estimation, most of the work centers on missing doses. No attempt has been made to specifically characterize the effect of error in reported dosing times. Additionally, existing work has largely dealt with cases in which the compound of interest is dosed at an interval no less than its terminal half-life. This work provides a case study investigating how error in patient reported dosing times might affect the accuracy of structural model parameter estimation under sparse sampling conditions when the dosing interval is less than the terminal half-life of the compound, and the underlying kinetics are monoexponential. Additional effects due to noncompliance with dosing events are not explored and it is assumed that the structural model and reasonable initial estimates of the model parameters are known. Under the conditions of our simulations, with structural model CV % ranging from ~20 to 60 %, parameter estimation inaccuracy derived from error in reported dosing times was largely controlled around 10 % on average. Given that no observed dosing was included in the design and sparse sampling was utilized, we believe these error results represent a practical ceiling given the variability and parameter estimates for the one-compartment model. The findings suggest additional investigations may be of interest and are noteworthy given the inability of current PK software platforms to accommodate error in dosing times.

Indexed as

Models, BiologicalModels, StatisticalPharmacokineticsAlgorithmsBayes TheoremComputer SimulationDrug Administration ScheduleHalf-LifeHumansLinear ModelsMetabolic Clearance RatePharmaceutical PreparationsSoftwareStochastic ProcessesPharmaceutical PreparationsDosing inaccuraciesParameter EstimationPopulation pharmacokineticsReporting errorSimulation

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.