Evidence map›Paper›PMID 17385020›Full record

ArticlePharmaceutical research2007

Predicting effect of food on extent of drug absorption based on physicochemical properties.

Chong-Hui Gu, Hua Li, Jaquan Levons, Kimberley Lentz, Rajesh B Gandhi, Krishnaswamy Raghavan, Ronald L Smith

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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. An erratum has been issued. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

45 citing papers in PubMed.

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4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

7 authors.

Chong-Hui GuBiopharmaceutics R&D, Bristol-Myers Squibb Co., New Brunswick, New Jersey, USA. chong-hui_gu@vrtx.com
Hua Li
Jaquan Levons
Kimberley Lentz
Rajesh B Gandhi
Krishnaswamy Raghavan
Ronald L Smith

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo develop a statistical model for predicting effect of food on the extent of absorption (area under the curve of time-plasma concentration profile, AUC) of drugs based on physicochemical properties. MATERIALS AND

methodsLogistic regression was applied to establish the relationship between the effect of food (positive, negative or no effect) on AUC of 92 entries and physicochemical parameters, including clinical doses used in the food effect study, solubility (pH 7), dose number (dose/solubility at pH 7), calculated Log D (pH 7), polar surface area, total surface area, percent polar surface area, number of hydrogen bond donor, number of hydrogen bond acceptors, and maximum absorbable dose (MAD).

resultsFor compounds with MAD >or= clinical dose, the food effect can be predicted from the dose number category and Log D category, while for compounds with MAD < clinical dose, the food effect can be predicted from the dose number category alone. With cross validation, 74 out of 92 entries (80%) were predicted into the correct category. The correct predictions were 97, 79 and 68% for compounds with positive, negative and no food effect, respectively.

conclusionsA logistic regression model based on dose, solubility, and permeability of compounds is developed to predict the food effect on AUC. Statistically, solubilization effect of food primarily accounted for the positive food effect on absorption while interference of food with absorption caused negative effect on absorption of compounds that are highly hydrophilic and probably with narrow window of absorption.

Indexed as

Food-Drug InteractionsPharmacokineticsArea Under Curve

Identifiers

What OpenQuestion holds

Textmetadata
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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.