Evidence mapPaperPMID 41995349Full record

ReviewJournal of virology2026

Clinical trial simulation of antiviral drugs.

Joshua T Schiffer, Daniel B Reeves, Bryan Mayer, Lucero Rodriguez Rodriguez, Elizabeth R Duke, Beatrix Haddock, Ugo Avila-Ponce de Leon, Shingo Iwami, Katherine Owens, Shadi Esmaeili-Wellman

Abstract readReview
In one paragraph

Review in Journal of virology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

10 authors.

Joshua T SchifferFred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division, Seattle, Washington, USA.ORCID 0000-0002-2598-1621
Daniel B ReevesFred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division, Seattle, Washington, USA.ORCID 0000-0001-5684-9538
Bryan MayerFred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division, Seattle, Washington, USA.
Lucero Rodriguez RodriguezFred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division, Seattle, Washington, USA.
Elizabeth R DukeFred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division, Seattle, Washington, USA.
Beatrix HaddockFred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division, Seattle, Washington, USA.
Ugo Avila-Ponce de LeonFred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division, Seattle, Washington, USA.ORCID 0000-0002-8463-5091
Shingo IwamiInterdisciplinary Biology Laboratory (iBLab), Division of Biological Science, Graduate School of Science, Nagoya University, Nagoya, Japan.
Katherine OwensFred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division, Seattle, Washington, USA.
Shadi Esmaeili-WellmanFred Hutchinson Cancer Center, Vaccine and Infectious Diseases Division, Seattle, Washington, USA.

Funding

Mathematical modeling of optimal therapeutic combinations for HIV cureR01AI150500 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Joshua Tisdell Schiffer · 2022 to 2024
$1.0M
Phylodynamic mechanisms of HIV reservoir seeding and maintenanceR01AI186721 · FRED HUTCHINSON CANCER CENTER · 2025 to 2025
$861k
National Institute of Allergy and Infectious Diseases R01AI77512NIAID NIH HHS R01 AI150500NIAID NIH HHS R01 AI186721
6 · The paper itself

Abstract

Antiviral clinical trial simulation (CTS) is a type of mathematical modeling that couples viral- immune dynamics (VID) unique to each human viral pathogen, with mechanistic, pharmacokinetic (PK), and pharmacodynamic (PD) drug characteristics. Validation is achieved by matching model output to detailed viral load trajectories from trials. Antiviral CTS can be applied at all stages of drug development to viruses with distinct shedding patterns. Models can capture the activity of small molecules, neutralizing antibodies, and cellular therapies, as well as combination strategies to enhance potency and avoid drug resistance. Several principles are observed across antiviral CTS models. First, PK and PD models that recapitulate drug levels and concentration-dependent antiviral activity are often necessary, but never sufficient to predict trial results. VID equations are also required to guide optimal treatment timing because expanding immune responses synergistically eliminate infection but are deleterious if too sustained or intense. Therefore, equivalent antiviral doses may have different efficacy if given during different infection stages. Second, antiviral CTS models identify effective plasma drug concentrations in humans, which are often poorly predicted by

Indexed as

Antiviral AgentsClinical Trials as TopicVirus DiseasesComputer SimulationHumansModels, BiologicalModels, TheoreticalViral LoadAntiviral Agentsantiviral drugsclinical trialmathematical modeling

Identifiers

PMID41995349
PMCPMC13185621

What Socratic 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 Socratic graph.