Evidence map›Paper›PMID 28058041›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2017

Integration of pharmacometabolomics with pharmacokinetics and pharmacodynamics: towards personalized drug therapy.

Vasudev Kantae, Elke H J Krekels, Michiel J Van Esdonk, Peter Lindenburg, Amy C Harms, Catherijne A J Knibbe, Piet H Van der Graaf, Thomas Hankemeier

Open access · hybridAbstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 1 pooled it
11.9field-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

47 citing papers in PubMed, 1 synthesis or guideline pooled it, 92 citations in OpenAlex.

  1. Pooled it
  2. Pharmacometabolomics applied to zonisamide pharmacokinetic parameter prediction.Metabolomics : Official journal of the Metabolomic Society · 2018
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  20. Chemotherapy-Induced Peripheral Neuropathy.Handbook of experimental pharmacology · 2023
    Article
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

8 authors at 3 institutions in 3 countries.

Vasudev Kantae *Division of Analytical Biosciences, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands.
Elke H J Krekels *Division of Pharmacology, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
Michiel J Van EsdonkDivision of Pharmacology, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
Peter LindenburgDivision of Analytical Biosciences, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands.
Amy C HarmsDivision of Analytical Biosciences, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands.
Catherijne A J KnibbeDivision of Pharmacology, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
Piet H Van der GraafDivision of Pharmacology, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
Thomas HankemeierDivision of Analytical Biosciences, Systems Pharmacology Cluster, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC Leiden, The Netherlands.
Centre for Human Drug Research · NLLeiden University · NLAnalytical Biosciences (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Personalized medicine, in modern drug therapy, aims at a tailored drug treatment accounting for inter-individual variations in drug pharmacology to treat individuals effectively and safely. The inter-individual variability in drug response upon drug administration is caused by the interplay between drug pharmacology and the patients' (patho)physiological status. Individual variations in (patho)physiological status may result from genetic polymorphisms, environmental factors (including current/past treatments), demographic characteristics, and disease related factors. Identification and quantification of predictors of inter-individual variability in drug pharmacology is necessary to achieve personalized medicine. Here, we highlight the potential of pharmacometabolomics in prospectively informing on the inter-individual differences in drug pharmacology, including both pharmacokinetic (PK) and pharmacodynamic (PD) processes, and thereby guiding drug selection and drug dosing. This review focusses on the pharmacometabolomics studies that have additional value on top of the conventional covariates in predicting drug PK. Additionally, employing pharmacometabolomics to predict drug PD is highlighted, and we suggest not only considering the endogenous metabolites as static variables but to include also drug dose and temporal changes in drug concentration in these studies. Although there are many endogenous metabolite biomarkers identified to predict PK and more often to predict PD, validation of these biomarkers in terms of specificity, sensitivity, reproducibility and clinical relevance is highly important. Furthermore, the application of these identified biomarkers in routine clinical practice deserves notable attention to truly personalize drug treatment in the near future.

Indexed as

BiomarkerMetabolomicsPersonalized medicinePharmacodynamicsPharmacokineticsPharmacologyPharmacometabolomics

Identifiers

PMID28058041
PMCPMC5165030
OpenAlexW2561901336

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.