Evidence map›Paper›PMID 27620173›Full record

ArticlePharmaceutical research2016

Projecting ADME Behavior and Drug-Drug Interactions in Early Discovery and Development: Application of the Extended Clearance Classification System.

Ayman F El-Kattan, Manthena V Varma, Stefan J Steyn, Dennis O Scott, Tristan S Maurer, Arthur Bergman

Abstract read
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Article in Pharmaceutical research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.8field-weighted citation impact, top 8% 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

8 citing papers in PubMed, 41 citations in OpenAlex.

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  6. In Vitro-In Vivo Inaccuracy: The CYP3A4 Anomaly.Drug metabolism and disposition: the biological fate of chemicals · 2019
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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

6 authors at 1 institution in 1 country.

Ayman F El-KattanPharmacokinetcis, Dynamics and Metabolism, Pfizer Inc., Cambridge, Massachusetts, USA. Ayman.El-Kattan@pfizer.com.
Manthena V VarmaPharmacokinetcis, Dynamics and Metabolism, Pfizer Inc., Groton, Connecticut, USA.
Stefan J SteynPharmacokinetcis, Dynamics and Metabolism, Pfizer Inc., Cambridge, Massachusetts, USA.
Dennis O ScottPharmacokinetcis, Dynamics and Metabolism, Pfizer Inc., Cambridge, Massachusetts, USA.
Tristan S MaurerPharmacokinetcis, Dynamics and Metabolism, Pfizer Inc., Cambridge, Massachusetts, USA.
Arthur BergmanClinical Pharmacology, Pfizer Inc., Groton, Connecticut, USA.
Pfizer (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo assess the utility of Extended Clearance Classification System (ECCS) in understanding absorption, distribution, metabolism, and elimination (ADME) attributes and enabling victim drug-drug interaction (DDI) predictions.

methodsA database of 368 drugs with relevant ADME parameters, main metabolizing enzymes, uptake transporters, efflux transporters, and highest change in exposure (%AUC) in presence of inhibitors was developed using published literature. Drugs were characterized according to ECCS using ionization, molecular weight and estimated permeability.

resultsAnalyses suggested that ECCS class 1A drugs are well absorbed and systemic clearance is determined by metabolism mediated by CYP2C, esterases, and UGTs. For class 1B drugs, oral absorption is high and the predominant clearance mechanism is hepatic uptake mediated by OATP transporters. High permeability neutral/basic drugs (class 2) showed high oral absorption, with metabolism mediated generally by CYP3A, CYP2D6 and UGTs as the predominant clearance mechanism. Class 3A/4 drugs showed moderate absorption with dominant renal clearance involving OAT/OCT2 transporters. Class 3B drugs showed low to moderate absorption with hepatic uptake (OATPs) and/or renal clearance as primary clearance mechanisms. The highest DDI risk is typically seen with class 2/1B/3B compounds manifested by inhibition of either CYP metabolism or active hepatic uptake. Class 2 showed a wider range in AUC change likely due to a variety of enzymes involved. DDI risk for class 3A/4 is small and associated with inhibition of renal transporters.

conclusionsECCS provides a framework to project ADME profiles and further enables prediction of victim DDI liabilities in drug discovery and development.

Indexed as

Computer SimulationDatabases, ChemicalModels, BiologicalAdsorptionDrug DiscoveryDrug InteractionsHumansIonsKidneyKineticsLiverMolecular WeightPermeabilityPharmaceutical PreparationsIonsPharmaceutical Preparationsactive hepatic uptakeclearance mechanismDDImetabolismrenal elimination

Identifiers

PMID27620173
OpenAlexW2520665752

What OpenQuestion holds

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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.