A Prototype QSP Model of the Immune Response to SARS‐CoV‐2 for Community Development. (21st December 2020)

• Record Type: Journal Article
• Authors: Dai, Wei; Rao, Rohit; Sher, Anna; Tania, Nessy; Musante, Cynthia J.; Allen, Richard
• Is Part Of: CPT: pharmacometrics & systems pharmacology. Volume 10:Number 1(2021)
• Page Start: 18
• Page End: 29
• Publication Date: 2020-12-21
• Subjects: Pharmacokinetics -- Periodicals; Pharmacology -- Periodicals; Pharmacokinetics; Periodicals; 615.05
• DOI: 10.1002/psp4.12574
• Languages: English
• ISSNs: 2163-8306

Abstract

Abstract : The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) pandemic requires the rapid development of efficacious treatments for patients with life‐threatening coronavirus disease 2019 (COVID‐19). Quantitative systems pharmacology (QSP) models are mathematical representations of pathophysiology for simulating and predicting the effects of existing or putative therapies. The application of model‐based approaches, including QSP, have accelerated the development of some novel therapeutics. Nevertheless, the development of disease‐scale mechanistic models can be a slow process, often taking years to be validated and considered mature. Furthermore, emerging data may make any QSP model quickly obsolete. We present a prototype QSP model to facilitate further development by the scientific community. The model accounts for the interactions between viral dynamics, the major host immune response mediators and tissue damage and regeneration. The immune response is determined by viral activation of innate and adaptive immune processes that regulate viral clearance and cell damage. The prototype model captures two physiologically relevant outcomes following infection: a "healthy" immune response that appropriately defends against the virus, and an uncontrolled alveolar inflammatory response that is characteristic of acute respiratory distress syndrome. We aim to significantly shorten the typical QSP model development and validation timeline by encouraging community use, testing, and refinement of this prototype model. It is our expectation that the model will be further advanced in an open science approach (i.e., by multiple contributions toward a validated quantitative platform in an open forum), with the ultimate goal of informing and accelerating the development of safe and effective treatment options for patients.