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  5. Characterising viral clearance kinetics in acute influenza

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Preprint
English
2025

Characterising viral clearance kinetics in acute influenza

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0 Files

English
2025
medRxiv (Cold Spring Harbor Laboratory)
DOI: 10.1101/2025.03.07.25323547

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Sir Nicholas White
Sir Nicholas White

University Of Cambridge

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Phrutsamon Wongnak
Timothy Seers
Podjanee Jittamala
+4 more

Abstract

Pharmacometric assessment of antiviral efficacy in acute influenza informs treatment decisions and pandemic preparedness. We assessed natural viral clearance in untreated acute influenza to guide clinical trial design. Standardized duplicate oropharyngeal swabs were collected daily over 14 days from 80 untreated low-risk Thai adults, with viral densities measured using qPCR. We evaluated three models to describe viral clearance: exponential, bi-exponential, and growth-and-decay. The growth-and-decay model provided the best fit, but the exponential decay model was the most parsimonious. The median viral clearance half-life was 10.3 hours (interquartile range [IQR]: 6.8-15.4), varying by influenza type: 9.6 hours (IQR: 6.2-13.0) for influenza A and 14.0 (IQR: 10.3-19.3) hours for influenza B. Simulated trials using clearance parameters from the exponential decay model, showed that 120 patients per arm provide over 90% power to detect treatments accelerating viral clearance by 40%. However, variation in clearance rates strongly impacted the statistical power; doubling this variation would require 240 patients per arm for an antiviral with a 60% effect size. An alternative sampling strategy with four swabs per day reduces the required sample size to 80 per arm while maintaining over 80% power. We recommend this approach to assess and compare current anti-influenza drugs.

How to cite this publication

Phrutsamon Wongnak, Timothy Seers, Podjanee Jittamala, Mallika Imwong, William HK Schilling, James A Watson, Sir Nicholas White (2025). Characterising viral clearance kinetics in acute influenza. medRxiv (Cold Spring Harbor Laboratory), DOI: 10.1101/2025.03.07.25323547.

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Publication Details

Type

Preprint

Year

2025

Authors

7

Datasets

0

Total Files

0

Language

English

Journal

medRxiv (Cold Spring Harbor Laboratory)

DOI

10.1101/2025.03.07.25323547

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