Evidence map›Paper›PMID 31482303›Full record

ArticleDrugs in R&D2019

Prediction of Drug-Drug Interactions Between Opioids and Overdosed Benzodiazepines Using Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation.

Beihong Ji, Shuhan Liu, Ying Xue, Xibing He, Viet Hoang Man, Xiang-Qun Xie, Junmei Wang

Open access · goldAbstract read
In one paragraph

Article in Drugs in R&D, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.9field-weighted citation impact, top 10% 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

9 citing papers in PubMed, 21 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

Beihong JiDepartment of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, 3501 Terrace, St Pittsburgh, PA, 15261, USA.
Shuhan LiuDepartment of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, 3501 Terrace, St Pittsburgh, PA, 15261, USA.
Ying XueDepartment of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, 3501 Terrace, St Pittsburgh, PA, 15261, USA.
Xibing HeDepartment of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, 3501 Terrace, St Pittsburgh, PA, 15261, USA.
Viet Hoang ManDepartment of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, 3501 Terrace, St Pittsburgh, PA, 15261, USA.
Xiang-Qun XieDepartment of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, 3501 Terrace, St Pittsburgh, PA, 15261, USA. xix15@pitt.edu.
Junmei WangDepartment of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, 3501 Terrace, St Pittsburgh, PA, 15261, USA. junmei.wang@pitt.edu.ORCID http://orcid.org/0000-0002-9607-8229
University of Pittsburgh · US

Funding

NIDA Center of Excellence OF Computational Drug Abuse Research (CDAR)P30DA035778 · NIDA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BAHAR, IVET, XIE, XIANG-QUN · 2014 to 2018
$5.4M
AMBER force field consortium: a coherent biomolecular simulation platformR01GM079383 · NIGMS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI CIEPLAK, PIOTR, DUAN, YONG · 2007 to 2017
$4.7M
Foundation for the National Institutes of Health DOD W81XWH-16-1-0490:412288Foundation for the National Institutes of Health P30 DA035778-01A1Foundation for the National Institutes of Health R01GM79383Foundation for the National Institutes of Health (US) ULITR001857NIDA NIH HHS P30 DA035778NIGMS NIH HHS R01 GM079383
6 · The paper itself

Abstract

backgroundResearchers have long been interested in the potential drug-drug interactions (DDIs) between opioids and benzodiazepines. However, much remains unknown concerning the interactions between these two drug classes. The objective of this work is to study the mechanism underlying the DDIs between opioids and benzodiazepines from the perspective of their pharmacokinetic (PK) interactions. A PK interaction occurs when two drugs are metabolized by the same cytochrome P450 enzymes and is one of the most common reasons for DDIs.

methodsWe quantitatively predicted the DDIs between three opioids (fentanyl, oxycodone and buprenorphine) and four benzodiazepines (alprazolam, diazepam, midazolam and triazolam) using a physiologically based pharmacokinetic (PBPK) modeling approach. A set of PBPK models was first constructed for these common opioids and benzodiazepines using SimCYP software, and the DDIs between them were then explored at various dosages.

resultsOur simulation results suggested there were no PK interactions between normal doses of opioids and benzodiazepines; but weak interactions can be expected with the combination of opioids and overdosed benzodiazepines. Particular attention should be given to the combination of fentanyl and overdosed alprazolam since a PK interaction can be observed between them.

conclusionOur results appear to indicate that pharmacodynamics may play a more important role than PKs in causing DDIs between opioids and benzodiazepines. This study also demonstrated that molecular modeling can be a very useful tool to mitigate the problem of "missing metabolic reaction parameters" in PK modeling and simulation.

Indexed as

Analgesics, OpioidBenzodiazepinesComputer SimulationCytochrome P-450 Enzyme SystemDrug InteractionsHumansModels, BiologicalAnalgesics, OpioidBenzodiazepinesCytochrome P-450 Enzyme System

Identifiers

PMID31482303
PMCPMC6738369
OpenAlexW2971865384

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.