LATE TREATMENT INITIATION LEADS TO REDUCED ANTIVIRAL POTENCY OF NIRMATRELVIR AND GS-441524 AGAINST IN VITRO SARS-COV-2 INFECTION

Xuanlin Liu ¹, Evelyn J. Franco ^2,4, Sean N. Avedissian ³, Kaley C. Hanrahan ², Jeremie Guedj ⁵, J. G. Coen van Hasselt ¹, Ashley N. Brown ^2,4, Anne-Grete Märtson ¹

1 Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden University (Leiden, The Netherlands), 2 Institute for Therapeutic Innovation, Department of Medicine, College of Medicine, University of Florida (, USA), 3 Antiviral Pharmacology Laboratory, UNMC Center for Drug Discovery (Omaha, USA), 4 Department of Pharmaceutics, College of Pharmacy, University of Florida (, USA), 5 Université de Paris, IAME, INSERM (Paris, France)

Introduction: The timing of initiation is critical in antiviral treatment. Viral dynamic (VD) modeling is widely used to study the within-host viral load changes and evaluate antiviral treatment effects. Previous simulation studies have shown that early treatment initiation is critical to maximize the therapeutic response in an acute viral infection. However, for simulations of varying treatment initiation time, most VD model studies have only considered the effect of initial condition (i.e., state of virus and cell populations when the therapy started), the loss of drug potency has been under-investigated. This may overestimate the antiviral effect, potentially resulting in suboptimal dose selection. To this end, we aimed to characterize the relationship between the apparent drug potency (EC₅₀) and the timing of drug addition, using nirmatrelvir and GS-441524 (remdesivir) against SARS-CoV-2 as an example.
Methods: In vitro experiments were conducted and viral load data were obtained with various drug concentrations and treatment initiated between 0 to 3 days post infection (DPI). Apparent EC₅₀ values were calculated from each treatment initiation group using an experimental-based approach (concentration-response curve fitting) and a model-based approach (viral dynamic modeling). To test the hypothesis that EC₅₀ is a time-varying parameter rather than a fixed parameter, we considered two candidate models to study the SARS-CoV-2 viral dynamics with varying times of treatment initiation: a target-cell limited (TCL) model with a constant EC₅₀ versus one with a time-varying EC₅₀. Model performance was evaluated by objective function value drop using a likelihood ratio test. The viral dynamic modelling was performed using the R package nlmixr2.
Results: The experiment-based EC₅₀ increased from 0.12 μg/mL to 15.02 μg/mL for nirmatrelvir when the treatment initiated from 0- DPI to 3 -DPI. As for GS-441524, there was no significant difference in EC₅₀ when the treatment started at 0-, 1-, 2-DPI, which were 2.72 μM, 2.92 μM, and 2.86 μM respectively. However, the EC₅₀ increased to 12.27 μM when the treatment started at 3- DPI. In the model-based approach, nirmatrelvir exhibited similar apparent EC₅₀ when the drug was added at 0-, 1-, 2-DPI, with a constant EC₅₀ serving as a baseline. The apparent EC₅₀ increased dramatically when the drug was added at 3-DPI. For GS-441524, the same trend was observed in one of the experiments. Mechanistic modeling demonstrated that a TCL model with constant EC₅₀ failed to capture viral trajectories when treatment started at 3 DPI. Incorporating a time-varying EC₅₀ significantly improved the model fit. Our study confirmed that late therapy initiation can lead to diminished antiviral potency as EC₅₀ increased alongside the timing of treatment initiation in both approaches. Further simulations indicated that a constant EC₅₀ model overestimated the antiviral efficacy when treatment is delayed, potentially misguiding dose selection for patients presenting late during the viral infection.
Conclusions: The study showed that the antiviral effect for SARS-CoV-2 was largely suppressed due to delayed therapy initiation time. These findings highlighted the importance of considering the time-dependent apparent EC₅₀ shift of antivirals when optimizing dosage regimens for patients for whom treatment is started late.

References:
[1] Gonçalves A, Bertrand J, Ke R, Comets E, De Lamballerie X, Malvy D, Pizzorno A, Terrier O, Rosa Calatrava M, Mentré F, Smith P, Perelson AS, Guedj J. 2020. Timing of Antiviral Treatment Initiation is Critical to Reduce SARS-CoV-2 Viral Load. CPT Pharmacom & Syst Pharma 9:509–514.
[2] Zhang S, Agyeman AA, Hadjichrysanthou C, Standing JF. 2023. SARS-CoV-2 viral dynamic modeling to inform model selection and timing and efficacy of antiviral therapy. CPT: Pharmacometrics & Systems Pharmacology 12:1450–1460.

Reference: PAGE 34 (2026) Abstr 12250 [www.page-meeting.org/?abstract=12250]

Poster: Drug/Disease Modelling - Infection