Evidence map›Paper›PMID 32767755›Full record

ArticleClinical pharmacology and therapeutics2020

Physiologically-Based Pharmacokinetic Modeling to Predict the Clinical Efficacy of the Coadministration of Lopinavir and Ritonavir against SARS-CoV-2.

Aarzoo Thakur, Shawn Pei Feng Tan, James Chun Yip Chan

Open access · bronzeAbstract 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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

6 citing papers in PubMed, 11 citations in OpenAlex.

  1. An open-label randomized controlled trial of the effect of lopinavir/ritonavir, lopinavir/ritonavir plus IFN-β-1a and hydroxychloroquine in hospitalized patients with COVID-19.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2021
    Trial
  2. Review
  3. Article
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  5. Review
  6. 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

3 authors at 2 institutions in 1 country.

Aarzoo ThakurInnovations in Food and Chemical Safety, Agency for Science, Technology, and Research, Singapore City, Singapore.
Shawn Pei Feng TanInnovations in Food and Chemical Safety, Agency for Science, Technology, and Research, Singapore City, Singapore.
James Chun Yip ChanInnovations in Food and Chemical Safety, Agency for Science, Technology, and Research, Singapore City, Singapore.
Agency for Science, Technology and Research · SGSingapore Institute for Clinical Sciences · SG

Funding

Agency for Science, Technology and Research (A*STAR) H18/01/a0/J14
6 · The paper itself

Abstract

Lopinavir/ritonavir, originally developed for treating HIV, is currently undergoing clinical studies for treating the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although recent reports suggest that lopinavir exhibits in vitro efficacy against SARS-CoV-2, it is a highly protein-bound drug and it remains unknown if it reaches adequate in vivo unbound (free) concentrations in lung tissue. We built a physiologically-based pharmacokinetic model of lopinavir/ritonavir in white and Chinese populations. Our aim was to perform pharmacokinetic/pharmacodynamic correlations by comparing simulated free plasma and lung concentration values achieved using different dosing regimens of lopinavir/ritonavir with unbound half-maximal effective concentration (EC

Indexed as

COVID-19 Drug TreatmentAntiviral AgentsArea Under CurveAsian PeopleDose-Response Relationship, DrugHalf-LifeHIV InfectionsHumansLopinavirLungMetabolic Clearance RateModels, BiologicalRitonavirSARS-CoV-2White PeopleAntiviral AgentsLopinavirRitonavir

Identifiers

PMID32767755
PMCPMC7436510
OpenAlexW3048048231

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.