Experimental and virus-specific drivers of EC50 variability in antiviral assays evaluated using mathematical modeling

The half-maximal effective concentrations (EC<sub>50</sub>) reported for specific antiviral agents often vary widely across in vitro studies. The cause for this may be due to differences in viral strains, cell types, and experimental design choices. Variability in EC<sub>50</sub> estimates complicates potency interpretation and cross-study comparison. In this study, we applied a mechanism-based mathematical target cell-limited model to examine the impact of virus-specific parameters and different experimental design choices on EC<sub>50</sub> estimation. Empirical EC<sub>50</sub> values were estimated from simulated concentration-response experiments for different virus-specific properties and experimental conditions. Among viral parameters, EC<sub>50</sub> changed more than 20-fold across the range of infection rate (β) and over 50-fold across viral production rate (ρ), whereas clearance rate had only minor effects. Among experimental factors, higher initial cell number (T₀) and later sampling time changed EC<sub>50</sub> by more than 15-fold, while delayed time of adding drug increased EC<sub>50</sub> by approximately 50 %. When both β and ρ were high, EC<sub>50</sub> changed nearly 900-fold. Overall, our findings demonstrate that EC<sub>50</sub> is highly sensitive to several virus-specific parameters and experimental design choices, and provides quantitative directions which may guide the design and interpretation of antiviral in vitro assays evaluating pharmacological activity.

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Publication Details

Journal
European Journal of Pharmaceutical Sciences
Published
2026-02-19
DOI
https://doi.org/10.1016/j.ejps.2026.107481
Primary Topic
Virus-based gene therapy research
Type
article
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article

Experimental and virus-specific drivers of EC50 variability in antiviral assays evaluated using mathematical modeling

Chenyu Wang, Qinhao Wu, Xuanlin Liu, J.G.C. van Hasselt et al.
European Journal of Pharmaceutical Sciences
Virus-based gene therapy research
article

Experimental and virus-specific drivers of EC50 variability in antiviral assays evaluated using mathematical modeling

Chenyu Wang, Qinhao Wu, Xuanlin Liu, J.G.C. van Hasselt, Anne-Grete Märtson, Lalitya M. Sudarsono
article en

Abstract

The half-maximal effective concentrations (EC<sub>50</sub>) reported for specific antiviral agents often vary widely across in vitro studies. The cause for this may be due to differences in viral strains, cell types, and experimental design choices. Variability in EC<sub>50</sub> estimates complicates potency interpretation and cross-study comparison. In this study, we applied a mechanism-based mathematical target cell-limited model to examine the impact of virus-specific parameters and different experimental design choices on EC<sub>50</sub> estimation. Empirical EC<sub>50</sub> values were estimated from simulated concentration-response experiments for different virus-specific properties and experimental conditions. Among viral parameters, EC<sub>50</sub> changed more than 20-fold across the range of infection rate (β) and over 50-fold across viral production rate (ρ), whereas clearance rate had only minor effects. Among experimental factors, higher initial cell number (T₀) and later sampling time changed EC<sub>50</sub> by more than 15-fold, while delayed time of adding drug increased EC<sub>50</sub> by approximately 50 %. When both β and ρ were high, EC<sub>50</sub> changed nearly 900-fold. Overall, our findings demonstrate that EC<sub>50</sub> is highly sensitive to several virus-specific parameters and experimental design choices, and provides quantitative directions which may guide the design and interpretation of antiviral in vitro assays evaluating pharmacological activity.

European Journal of Pharmaceutical SciencesVol. 220
Leiden University (NL), Centre for Human Drug Research (NL)
Openalex Percentile: Top 48%
Virus-based gene therapy research
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Experimental and virus-specific drivers of EC50 variability in antiviral assays evaluated using mathematical modeling — Chenyu Wang, Qinhao Wu, et al. · European Journal of Pharmaceutical Sciences (2026) | TGRS Research Map | TGRS