Evidence map›Paper›PMID 17372687›Full record

ArticlePharmaceutical research2007

Mechanistic approaches to volume of distribution predictions: understanding the processes.

Trudy Rodgers, Malcolm Rowland

Abstract read
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In one paragraph

Article in Pharmaceutical research, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 175 papers.

0numbers the graph read from it
0cells of the map it votes in
175citing papers in PubMed
16.8field-weighted citation impact, top 1% of its field
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

175 citing papers in PubMed, 411 citations in OpenAlex.

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115 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 at 1 institution in 1 country.

Trudy RodgersCentre for Applied Pharmacokinetic Research, School of Pharmacy, University of Manchester, Stopford Building, Oxford Road, Manchester, M13 9PT, UK. trudy.rodgers@manchester.ac.uk
Malcolm Rowland
University of Manchester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo use recently developed mechanistic equations to predict tissue-to-plasma water partition coefficients (Kpus), apply these predictions to whole body unbound volume of distribution at steady state (Vu(ss)) determinations, and explain the differences in the extent of drug distribution both within and across the various compound classes. MATERIALS AND

methodsVu(ss) values were predicted for 92 structurally diverse compounds in rats and 140 in humans by two approaches. The first approach incorporated Kpu values predicted for 13 tissues whereas the second was restricted to muscle.

resultsThe prediction accuracy was good for both approaches in rats and humans, with 64-78% and 82-92% of the predicted Vu(ss) values agreeing with in vivo data to within factors of +/-2 and 3, respectively.

conclusionsGeneric distribution processes were identified as lipid partitioning and dissolution where the former is higher for lipophilic unionised drugs. In addition, electrostatic interactions with acidic phospholipids can predominate for ionised bases when affinities (reflected by binding to constituents within blood) are high. For acidic drugs albumin binding dominates when plasma protein binding is high. This ability to explain drug distribution and link it to physicochemical properties can help guide the compound selection process.

Indexed as

AlgorithmsModels, BiologicalAnimalsComputer SimulationDrug DesignHumansKineticsPharmaceutical PreparationsRatsTechnology, PharmaceuticalTissue DistributionPharmaceutical Preparations

Identifiers

PMID17372687
OpenAlexW2028165836

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.