Evidence map›Paper›PMID 32150643›Full record

ArticleClinical pharmacology and therapeutics2020

A Simple Methodology to Differentiate Changes in Bioavailability From Changes in Clearance Following Oral Dosing of Metabolized Drugs.

Jasleen K Sodhi, Leslie Z Benet

Open access · greenAbstract read
In one paragraph

Article in Clinical pharmacology and therapeutics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 19% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Article
  6. Article
  7. 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

2 authors at 1 institution in 1 country.

Jasleen K SodhiDepartment of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, San Francisco, California, USA.
Leslie Z BenetDepartment of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, San Francisco, California, USA.
University of California, San Francisco · US

Funding

UCSF Liver Core CenterP30DK026743 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Jennifer Y. Chen · 1986 to 2026
$30.7M
Maximizing Opportunities for Research Excellence - Evaluation Training SupplementR25GM056847 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI DUNCAN, D'ANNE S., SELLO, JASON K · 1998 to 2023
$14.1M
NIDDK NIH HHS P30 DK026743NIGMS NIH HHS R25 GM056847
6 · The paper itself

Abstract

Accurately discriminating changes in clearance (CL) from changes in bioavailability (F) following an oral drug-drug interaction is difficult without carrying out an intravenous interaction study. This may be true for drugs that are clinically significant transporter substrates; however, for interactions that are strictly metabolic, it has been recognized that volume of distribution remains unchanged between both phases of the interaction study. With the understanding that changes in volume of distribution will be minimal for metabolized drugs, the inverse of the change in apparent volume of distribution can provide adequate estimates of the change in bioavailability alone. Utilization of this estimate of F change in tandem with the observed apparent clearance (CL/F) change in an oral drug-drug interaction can provide an estimate of the change in clearance alone. Here, we examine drug-drug interactions involving five known inhibitors and inducers of cytochrome P450 3A4 isozyme on victim drugs midazolam and apixaban for which the interaction was carried out both orally and intravenously, allowing for evaluation of this methodology. Predictions of CL and F changes based on oral data were reasonably close to observed changes based on intravenous studies, demonstrating that this simple yet powerful methodology can reasonably differentiate changes in F from changes in CL for oral metabolic drug interactions when only oral data are available. Utilization of this relatively simple methodology to evaluate DDIs for orally dosed drugs will have a significant impact on how DDIs are interpreted from a drug development and regulatory perspective.

Indexed as

Models, BiologicalAdministration, IntravenousAdministration, OralBiological AvailabilityBiotransformationCytochrome P-450 CYP3ACytochrome P-450 CYP3A InducersCytochrome P-450 CYP3A InhibitorsDrug InteractionsHumansMetabolic Clearance RateMidazolamRisk AssessmentCYP3A4 protein, humanCytochrome P-450 CYP3ACytochrome P-450 CYP3A InducersCytochrome P-450 CYP3A InhibitorsMidazolam

Identifiers

PMID32150643
PMCPMC7478330
OpenAlexW3010480539

What OpenQuestion holds

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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.