Evidence map›Paper›PMID 17211713›Full record

Trial reportJournal of pharmacokinetics and pharmacodynamics2007

Estimation of population pharmacokinetic parameters of saquinavir in HIV patients with the MONOLIX software.

Marc Lavielle, France Mentré

Abstract readClinical Trial
In one paragraph

Trial report in Journal of pharmacokinetics and pharmacodynamics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers.

0numbers the graph read from it
0cells of the map it votes in
77citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

77 citing papers in PubMed.

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  16. A Framework for Quantitative Systems Pharmacology Model Execution.Handbook of experimental pharmacology · 2025
    Review
  17. Model-informed drug discovery and development approaches to inform clinical trial design and regulatory decisions: A primer for the MENA region.Saudi pharmaceutical journal : SPJ : the official publication of the Saudi Pharmaceutical Society · 2024
    Review
  18. Article
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17 more citing papers are in PubMed but not listed here.

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.

Marc LavielleDepartment of Mathematics, University Paris 5; University Paris 11, Orsay, France. Marc.Lavielle@math.u-psud.fr
France Mentré

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In nonlinear mixed-effects models, estimation methods based on a linearization of the likelihood are widely used although they have several methodological drawbacks. Kuhn and Lavielle (Comput. Statist. Data Anal. 49:1020-1038 (2005)) developed an estimation method which combines the SAEM (Stochastic Approximation EM) algorithm, with a MCMC (Markov Chain Monte Carlo) procedure for maximum likelihood estimation in nonlinear mixed-effects models without linearization. This method is implemented in the Matlab software MONOLIX which is available at http://www.math.u-psud.fr/~lavielle/monolix/logiciels. In this paper we apply MONOLIX to the analysis of the pharmacokinetics of saquinavir, a protease inhibitor, from concentrations measured after single dose administration in 100 HIV patients, some with advance disease. We also illustrate how to use MONOLIX to build the covariate model using the Bayesian Information Criterion. Saquinavir oral clearance (CL/F) was estimated to be 1.26 L/h and to increase with body mass index, the inter-patient variability for CL/F being 120%. Several methodological developments are ongoing to extend SAEM which is a very promising estimation method for population pharmacockinetic/pharmacodynamic analyses.

Indexed as

HIV-1Models, BiologicalSoftwareAdministration, OralAlgorithmsBayes TheoremHIV InfectionsHIV Protease InhibitorsHumansLikelihood FunctionsMarkov ChainsMonte Carlo MethodNonlinear DynamicsPopulation SurveillanceProspective StudiesReproducibility of ResultsHIV Protease InhibitorsSaquinavir

Identifiers

PMID17211713
PMCPMC1974848

What OpenQuestion holds

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Registered trials

None linked

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.