UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Comparative assessment of viral dynamic models for SARS-CoV-2 for pharmacodynamic assessment in early treatment trials

Agyeman, Akosua A; You, Tao; Chan, Phylinda LS; Lonsdale, Dagan O; Hadjichrysanthou, Christoforos; Mahungu, Tabitha; Wey, Emmanuel Q; ... Standing, Joseph F; + view all (2022) Comparative assessment of viral dynamic models for SARS-CoV-2 for pharmacodynamic assessment in early treatment trials. British Journal of Clinical Pharmacology , 88 (12) pp. 5428-5433. 10.1111/bcp.15518. Green open access

[thumbnail of Comparative assessment of viral dynamic models.pdf]
Preview
Text
Comparative assessment of viral dynamic models.pdf - Accepted Version

Download (932kB) | Preview

Abstract

Pharmacometric analyses of time series viral load data may detect drug effects with greater power than approaches using single time points. Because SARS-CoV-2 viral load rapidly rises and then falls, viral dynamic models have been used. We compared different modelling approaches when analysing Phase II-type viral dynamic data. Using two SARS-CoV-2 datasets of viral load starting within 7 days of symptoms, we fitted the slope-intercept exponential decay (SI), reduced target cell limited (rTCL), target cell limited (TCL) and TCL with eclipse phase (TCLE) models using nlmixr. Model performance was assessed via Bayesian information criterion (BIC), visual predictive checks (VPCs), goodness-of-fit plots, and parameter precision. The most complex (TCLE) model had the highest BIC for both datasets. The estimated viral decline rate was similar for all models except the TCL model for dataset A with a higher rate [median (range) day-1 : dataset A; 0.63 (0.56 - 1.84); dataset B: 0.81 (0.74-0.85)]. Our findings suggest simple models should be considered during pharmacodynamic model development.

Type: Article
Title: Comparative assessment of viral dynamic models for SARS-CoV-2 for pharmacodynamic assessment in early treatment trials
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1111/bcp.15518
Publisher version: https://doi.org/10.1111/bcp.15518
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: COVID-19, SARS-COV-2, model performance, pharmacometrics, viral dynamics
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Infection, Immunity and Inflammation Dept
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Respiratory Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Infection and Immunity
URI: https://discovery.ucl.ac.uk/id/eprint/10155562
Downloads since deposit
27Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item