GithubHelp home page GithubHelp logo

cptbern / sars2-viral-kinetics Goto Github PK

View Code? Open in Web Editor NEW
2.0 1.0 0.0 984 KB

Simulate effects of drug treatment regimens on the viral kinetics of SARS-CoV-2 to explore repurposing treatments in Covid-19

License: GNU General Public License v3.0

covid-19 sars-cov-2 pharmacometrics pharmacology monolix gnu-r

sars2-viral-kinetics's Introduction

Viral kinetics models for SARS-CoV-2 drug repurposing

A collection of R scripts to model the within-host viral kinetics of SARS-CoV-2 and drug effects to inform drug repurposing. You can explore your own drugs by re-running the scripts with simulations or actual experimental data. We supply concentration profiles for several proposed treatments along with Monolix / mlxR code to repeat our simulations or build your own.

We fitted the viral kinetics to data published by Young et al. in early 2020. Additionally, we allow for acquired immunity to develop over the course of 1-2 weeks based on reports by Long et al., Nat. Med. 2020 and To et al., Lancet Inf. Dis. 2020. For a detailed description, please refer to "Modeling of SARS-CoV-2 Treatment Effects for Informed Drug Repurposing" (Kern et al., Front. Pharmacol. 2021).

Model

The underlying model is the standard target-cell limited model extended with developing acquired immunity and drug effects, both represented by sigmoidal Emax models. Virus particles V infect a pool of susceptible (target) cells T with the cellular infection rate β. Infected cells I begin shedding virions at a production rate p. The effects of pharmacological treatments by different modes of action are described by the following variables:

  • inhibition of viral entry into susceptible cells,
  • by decreasing the cellular infection rate with effectiveness η,
  • and/or by blocking viral production rate within infected cells with effectiveness ε.

Sample simulations

The following figure shows simulated viral kinetic profiles following treatment with hydroxychloroquine, lopinavir/ritonavir, ivermectin, artemisinin, or nitazoxanide.

Viral load profiles of SARS-CoV-2 following different drug treatments

Viral load profiles of SARS-CoV-2 following different treatment regimens and initiation of treatment (green: untreated, blue: on positivity (5.4 days after infection), and red: on peak (10.2 days after infection)). Lines may overlap so that only one color is visible; simulations were always run for all time points. Ct: serial cycle threshold values; ART: artemisinin; HCQ: hydroxychloroquine; IVM: ivermectin; LPV/r: lopinavir/ritonavir; NTZ: nitazoxanide. Dosing of different modeled treatment regimens: IVM 300: 300 μg/kg every 24 h for 3 days; IVM 600: IVM 600 μg/kg every day for 3 days; HCQ 200: 200 mg every 8 h for 10 days; HCQ 800/400: 800 mg every 12 h for 1 day, then 400 mg every 12 h for 9 days; NTZ 1200: NTZ 1200 mg every 6 h for 5 days; NTZ 2900: NTZ 2900 mg every 12 h for 5 days; LPV/r 400/100: LPV/r 400/100 mg every 12 h for 14 days; ART 500: ART 500 mg once a day for 5 days.

sars2-viral-kinetics's People

Contributors

ch4kern avatar cptbern avatar fhammann avatar

Stargazers

 avatar  avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.