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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\n                      <jats:italic toggle=\"yes\">in vitro<\/jats:italic>\n                      assays. Finally, models that do not consider drug mechanisms lead to incorrect efficacy estimates. Data-validated CTS is increasingly used to inform drug dose and dosing interval, treatment timing and duration, virologic endpoint selection, and sample size, particularly when applied to detailed phase 1 and 2 trial data. 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