Evidence map›Paper›PMID 30699105›Full record

ArticlePLoS computational biology2019

Mechanistic framework predicts drug-class specific utility of antiretrovirals for HIV prophylaxis.

Sulav Duwal, Laura Dickinson, Saye Khoo, Max von Kleist

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.6field-weighted citation impact, top 18% 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

13 citing papers in PubMed, 22 citations in OpenAlex.

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  11. Modeling HIV Pre-Exposure Prophylaxis.Frontiers in pharmacology · 2019
    Review
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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

4 authors at 2 institutions in 2 countries.

Sulav DuwalDepartment of Mathematics & Computer Science, Freie Universität Berlin, Germany.ORCID 0000-0002-8772-6706
Laura DickinsonInstitute of Translational Medicine, University of Liverpool, United Kingdom.ORCID 0000-0001-5557-9396
Saye KhooInstitute of Translational Medicine, University of Liverpool, United Kingdom.ORCID 0000-0002-2769-0967
Max von KleistDepartment of Mathematics & Computer Science, Freie Universität Berlin, Germany.ORCID 0000-0001-6587-6394
Freie Universität Berlin · DEUniversity of Liverpool · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Currently, there is no effective vaccine to halt HIV transmission. However, pre-exposure prophylaxis (PrEP) with the drug combination Truvada can substantially decrease HIV transmission in individuals at risk. Despite its benefits, Truvada-based PrEP is expensive and needs to be taken once-daily, which often leads to inadequate adherence and incomplete protection. These deficits may be overcome by next-generation PrEP regimen, including currently investigated long-acting formulations, or patent-expired drugs. However, poor translatability of animal- and ex vivo/in vitro experiments, and the necessity to conduct long-term (several years) human trials involving considerable sample sizes (N>1000 individuals) are major obstacles to rationalize drug-candidate selection. We developed a prophylaxis modelling tool that mechanistically considers the mode-of-action of all available drugs. We used the tool to screen antivirals for their prophylactic utility and identify lower bound effective concentrations that can guide dose selection in PrEP trials. While in vitro measurable drug potency usually guides PrEP trial design, we found that it may over-predict PrEP potency for all drug classes except reverse transcriptase inhibitors. While most drugs displayed graded concentration-prophylaxis profiles, protease inhibitors tended to switch between none- and complete protection. While several treatment-approved drugs could be ruled out as PrEP candidates based on lack-of-prophylactic efficacy, darunavir, efavirenz, nevirapine, etravirine and rilpivirine could more potently prevent infection than existing PrEP regimen (Truvada). Notably, some drugs from this candidate set are patent-expired and currently neglected for PrEP repurposing. A next step is to further trim this candidate set by ruling out compounds with ominous safety profiles, to assess different administration schemes in silico and to test the remaining candidates in human trials.

Indexed as

Models, StatisticalPre-Exposure ProphylaxisAnti-Retroviral AgentsComputational BiologyHIV-1HIV InfectionsHumansAnti-Retroviral Agents

Identifiers

PMID30699105
PMCPMC6370240
OpenAlexW2911976827

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.