In silico evaluation of Paxlovid's pharmacometrics for SARS-CoV-2: a multiscale approach

TL;DR

This paper presents a hybrid multiscale in silico model to evaluate Paxlovid's pharmacometrics for SARS-CoV-2, successfully replicating experimental results and highlighting the importance of early intervention and component necessity.

Contribution

It introduces a novel multiscale mathematical framework for detailed in silico assessment of Paxlovid, linking in vitro, in vivo, and clinical insights.

Findings

Model replicates in vitro experiment outcomes

Verifies necessity of Paxlovid's main components

Identifies critical timing for interventions

Abstract

Paxlovid is a promising, orally bioavailable novel drug for SARS--CoV--2 with excellent safety profiles. Our main goal here is to explore the pharmacometric features of this new antiviral. To provide a detailed assessment of Paxlovid, we propose a hybrid multiscale mathematical approach. We demonstrate that the results of the present \textit{in silico} evaluation match the clinical expectations remarkably well: on the one hand, our computations successfully replicate the outcome of an actual \textit{in vitro} experiment; on the other hand we verify both the sufficiency and the necessity of Paxlovid's two main components (nirmatrelvir and ritonavir) for a simplified \textit{in vivo} case. Moreover, in the simulated context of our computational framework we visualize the importance of early interventions, and identify the time window where a unit--length delay causes the highest level of tissue damage. Finally, the results' sensitivity to the diffusion coefficient of the virus is explored in details.