Evidence map›Paper›PMID 25907346›Full record

ReviewNature reviews. Drug discovery2015

Predicting drug metabolism: experiment and/or computation?

Johannes Kirchmair, Andreas H Göller, Dieter Lang, Jens Kunze, Bernard Testa, Ian D Wilson, Robert C Glen, Gisbert Schneider

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Drug discovery, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 192 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
192citing papers in PubMed, 2 pooled it
–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

192 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Drug-likeness prioritised selection identifies anti-Journal of enzyme inhibition and medicinal chemistry · 2026
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  16. MetaInternational journal of molecular sciences · 2025
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132 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

8 authors.

Johannes KirchmairDepartment of Chemistry and Applied Biosciences, Institute of Pharmaceutical Sciences, ETH Zürich, 8093 Zürich, Switzerland; and the Center for Bioinformatics, University of Hamburg, 20146 Hamburg, Germany.
Andreas H GöllerGlobal Drug Discovery, Bayer Pharma AG, 42096 Wuppertal, Germany.
Dieter LangDrug Metabolism, Bayer Pharma AG, 42096 Wuppertal, Germany.
Jens KunzeDepartment of Chemistry and Applied Biosciences, Institute of Pharmaceutical Sciences, ETH Zürich, 8093 Zürich, Switzerland.
Bernard TestaDepartment of Pharmacy, Lausanne University Hospital, CH-1011 Lausanne, Switzerland.
Ian D WilsonDepartment of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK.
Robert C GlenDepartment of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, UK; and The Centre for Molecular Informatics, Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
Gisbert SchneiderDepartment of Chemistry and Applied Biosciences, Institute of Pharmaceutical Sciences, ETH Zürich, 8093 Zürich, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug metabolism can produce metabolites with physicochemical and pharmacological properties that differ substantially from those of the parent drug, and consequently has important implications for both drug safety and efficacy. To reduce the risk of costly clinical-stage attrition due to the metabolic characteristics of drug candidates, there is a need for efficient and reliable ways to predict drug metabolism in vitro, in silico and in vivo. In this Perspective, we provide an overview of the state of the art of experimental and computational approaches for investigating drug metabolism. We highlight the scope and limitations of these methods, and indicate strategies to harvest the synergies that result from combining measurement and prediction of drug metabolism.

Indexed as

Drug DesignAnimalsComputational BiologyDrug DiscoveryForecastingHumansPharmaceutical PreparationsPharmaceutical Preparations

Identifiers

PMID25907346

What OpenQuestion holds

Textmetadata
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.