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<p>The COVID-19 pandemic showed that heterogeneous antiviral assay designs, endpoints and reporting practices can obscure which candidate drugs and combinations are genuinely promising. As antiviral discovery expands from acute infections to chronic and latent viral diseases, the field needs a compact, reproducible and biologically interpretable set of response metrics. In this Personal View, we argue that EC₅₀ and the selectivity index should be retained for pharmacological interpretation but systematically complemented by drug sensitivity scores (DSS), which integrate potency and efficacy across the tested concentration range, and by ΔDSS, calculated as DSS_antiviral minus DSS_toxicity from matched efficacy and viability curves. We propose standardized modules for resistance passaging, sequencing and host-side-effect profiling so that monotherapies are assessed not only for antiviral potency but also for durability and host-cell perturbation. For combinations, we discuss Bliss, ZIP, HSA and Loewe models as complementary tools for identifying additive or synergistic regimens while accounting for toxicity, resistance suppression and drug-drug interactions. Finally, we outline how harmonized metrics can support organoid, animal and clinical prioritization, improve machine-learning datasets and guide pandemic response, including rapid monotherapy testing for some DNA viruses and early combination testing for RNA and reverse-transcribing viruses.</p>

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Standardizing antiviral response metrics for mono- and combination therapies in acute, chronic and latent viral infections

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月25日

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  • Pavlo Petakh,
  • Erlend Ravlo,
  • Qiuwei Pan,
  • Roberto Bruzzone,
  • Valentyn Oksenych,
  • Markus Vähä-Koskela,
  • Oleksandr Kamyshnyi,
  • Denis E. Kainov

摘要

The COVID-19 pandemic showed that heterogeneous antiviral assay designs, endpoints and reporting practices can obscure which candidate drugs and combinations are genuinely promising. As antiviral discovery expands from acute infections to chronic and latent viral diseases, the field needs a compact, reproducible and biologically interpretable set of response metrics. In this Personal View, we argue that EC₅₀ and the selectivity index should be retained for pharmacological interpretation but systematically complemented by drug sensitivity scores (DSS), which integrate potency and efficacy across the tested concentration range, and by ΔDSS, calculated as DSS_antiviral minus DSS_toxicity from matched efficacy and viability curves. We propose standardized modules for resistance passaging, sequencing and host-side-effect profiling so that monotherapies are assessed not only for antiviral potency but also for durability and host-cell perturbation. For combinations, we discuss Bliss, ZIP, HSA and Loewe models as complementary tools for identifying additive or synergistic regimens while accounting for toxicity, resistance suppression and drug-drug interactions. Finally, we outline how harmonized metrics can support organoid, animal and clinical prioritization, improve machine-learning datasets and guide pandemic response, including rapid monotherapy testing for some DNA viruses and early combination testing for RNA and reverse-transcribing viruses.