PPP-COMPUTE: A Pandemic Pharmacology Platform for COMPUTational Evaluation of Anti-infectives in Pandemic Preparedness

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Abstract

A global pandemic requires accelerated strategies to mitigate public healthcare risks and preserve societal stability, either by repurposing existing drugs or by rapidly developing novel drug candidates. Computational platforms have accelerated candidate identification for both routes. A critical gap is the translation from in vitro potency to predicted clinical efficacy, which determines whether a prioritized candidate can achieve therapeutic effect under realistic dosing. To address this, we developed the Pandemic Pharmacology Platform for COMPUTational Evaluation of anti-infectives (PPP-COMPUTE), a comprehensive pharmacokinetic/pharmacodynamic (PK/PD) simulation platform designed to support evaluation and prioritization of drug candidates and clinical trial design during a pandemic. PPP-COMPUTE integrates experimentally derived anti-infective potency data (e.g., EC 50 ) with PK/PD modeling to evaluate whether clinical dosing regimens can achieve sufficient exposure for therapeutic efficacy in patients. The platform incorporates mechanism-based dynamic models with a focus on viral pathogens to simulate time-dependent viral load trajectories under various treatment scenarios, enabling quantitative assessment of antiviral response and optimization of dosing strategies. Probability of target attainment analyses further support evaluation of regimen feasibility against predefined pharmacological targets. The clinical trial module generates simulated virological endpoints to evaluate candidate clinical study designs. PPP-COMPUTE is an accessible and quantitative framework that links PK and preclinical anti-infective potency data with predicted clinical benefit, thereby supporting rapid drug evaluation during future pandemics.

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